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Allan Timmermann

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.

    Mentioned in:

    1. Combining Forecasts
      by Clive Jones in Business Forecasting on 2012-06-26 00:30:56
  2. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.

    Mentioned in:

    1. Forecasting GDP in the presence of breaks: when is the past is a good guide to the future?
      by bankunderground in Bank Underground on 2015-08-20 11:30:00
    2. Forecasting GDP in the presence of breaks: when is the past a good guide to the future?
      by Guest Author in The Big Picture on 2015-09-01 14:00:11
  3. Author Profile
    1. Top Forecasting Institutions and Researchers According to IDEAS!
      by Clive Jones in Business Forecasting on 2013-06-28 01:43:46
    2. Ranking California Economists as of May 2015
      by Matthew Kahn in Environmental and Urban Economics on 2015-06-04 02:25:00
    3. Peers at Work as of August 2016
      by Matthew Kahn in Environmental and Urban Economics on 2016-09-04 19:36:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.

    Mentioned in:

    1. > Econometrics > Forecasting

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Allan Timmermann & Massimo Guidolin, 2006. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 1-22.

    Mentioned in:

    1. An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns (Journal of Applied Econometrics 2006) in ReplicationWiki ()
  2. Timmermann, Allan, 1995. "Cointegration Tests of Present Value Models with a Time-Varying Discount Factor," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 17-31, Jan.-Marc.

    Mentioned in:

    1. Cointegration tests of present value models with a time-varying discount factor (Journal of Applied Econometrics 1995) in ReplicationWiki ()

Working papers

  1. Simon Smith & Allan Timmermann & Jonathan H. Wright, 2023. "Breaks in the Phillips Curve: Evidence from Panel Data," NBER Working Papers 31153, National Bureau of Economic Research, Inc.

    Cited by:

    1. Barbara Rossi & Atsushi Inoue & Yiru Wang, 2024. "Has the Phillips curve flattened?," French Stata Users' Group Meetings 2024 22, Stata Users Group.
    2. Ferri, Piero & Cristini, Annalisa & Tramontana, Fabio, 2023. "Meta-models of the Phillips curve and income distribution," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 215-232.
    3. Pierpaolo Benigno & Gauti B. Eggertsson, 2023. "It’s Baaack: The Surge in Inflation in the 2020s and the Return of the Non-Linear Phillips Curve," NBER Working Papers 31197, National Bureau of Economic Research, Inc.

  2. Peter Reinhard HANSEN & Allan TIMMERMANN, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," Economics Working Papers ECO2012/10, European University Institute.

    Cited by:

    1. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Tae-Hwy Lee & Weiping Yang, 2012. "Money–Income Granger-Causality in Quantiles," Advances in Econometrics, in: 30th Anniversary Edition, pages 385-409, Emerald Group Publishing Limited.
    4. Fabian Baetje & Lukas Menkhoff, 2016. "Equity Premium Prediction: Are Economic and Technical Indicators Unstable?," Discussion Papers of DIW Berlin 1552, DIW Berlin, German Institute for Economic Research.
    5. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    6. Li, Chenchen & Wang, Yudong & Wu, Chongfeng, 2022. "Oil implied volatility and expected stock returns along the worldwide supply chain," Energy Economics, Elsevier, vol. 114(C).
    7. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    8. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    9. Goodness C. Aye & Frederick W. Deale & Rangan Gupta, 2016. "Does Debt Ceiling and Government Shutdown Help in Forecasting the US Equity Risk Premium?," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 63(3), pages 273-291.
    10. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    11. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," Economics Discussion / Working Papers 20-06, The University of Western Australia, Department of Economics.
    12. Wang, Cindy Shin-Huei & Bauwens, Luc & Hsiao, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 171-184.
    13. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    14. Peter Reinhard Hansen & Allan Timmermann, 2012. "Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics," CREATES Research Papers 2012-45, Department of Economics and Business Economics, Aarhus University.
    15. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    16. Biqing Cai & Jiti Gao, 2017. "A simple nonlinear predictive model for stock returns," Monash Econometrics and Business Statistics Working Papers 18/17, Monash University, Department of Econometrics and Business Statistics.
    17. Pönkä, Harri, 2014. "Predicting the direction of US stock markets using industry returns," MPRA Paper 62942, University Library of Munich, Germany.
    18. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    19. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    20. Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 110(C).
    21. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
    22. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
    23. Hatice Gökçe Karasoy Can & Çağlar Yüncüler, 2018. "The Explanatory Power and the Forecast Performance of Consumer Confidence Indices for Private Consumption Growth in Turkey," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(9), pages 2136-2152, July.
    24. John Cotter & Emmanuel Eyiah-Donkor & Valerio Potì, 2023. "Commodity futures return predictability and intertemporal asset pricing," Post-Print hal-04192933, HAL.
    25. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    26. Brooks, Chris & Burke, Simon P. & Stanescu, Silvia, 2016. "Finite sample weighting of recursive forecast errors," International Journal of Forecasting, Elsevier, vol. 32(2), pages 458-474.
    27. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    28. Ignacio Garr'on & C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "International vulnerability of inflation," Papers 2410.20628, arXiv.org, revised Oct 2024.
    29. Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019. "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 210-227.
    30. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    31. Markiewicz, Agnieszka & Pick, Andreas, 2014. "Adaptive learning and survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 685-707.
    32. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    33. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    34. Fang, Jiali & Jacobsen, Ben & Qin, Yafeng, 2014. "Predictability of the simple technical trading rules: An out-of-sample test," Review of Financial Economics, Elsevier, vol. 23(1), pages 30-45.
    35. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    36. Liang, Chao & Wang, Lu & Duong, Duy, 2024. "More attention and better volatility forecast accuracy: How does war attention affect stock volatility predictability?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 1-19.
    37. Ruan, Xinfeng & Zhang, Jin E., 2018. "Risk-neutral moments in the crude oil market," Energy Economics, Elsevier, vol. 72(C), pages 583-600.
    38. Corradi, Valentina & Swanson, Norman R., 2014. "Testing for structural stability of factor augmented forecasting models," Journal of Econometrics, Elsevier, vol. 182(1), pages 100-118.
    39. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    40. Khan, Faridoon & Muhammadullah, Sara & Sharif, Arshian & Lee, Chien-Chiang, 2024. "The role of green energy stock market in forecasting China's crude oil market: An application of IIS approach and sparse regression models," Energy Economics, Elsevier, vol. 130(C).
    41. Christian Hutter, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-10, December.
    42. Kolev, Gueorgui I. & Karapandza, Rasa, 2017. "Out-of-sample equity premium predictability and sample split–invariant inference," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 188-201.
    43. Chiang, I-Hsuan Ethan & Liao, Yin & Zhou, Qing, 2021. "Modeling the cross-section of stock returns using sensible models in a model pool," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 56-73.
    44. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Documents de travail du Centre d'Economie de la Sorbonne 13080, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    45. He, Kaijian & Wang, Lijun & Zou, Yingchao & Lai, Kin Keung, 2014. "Value at risk estimation with entropy-based wavelet analysis in exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 62-71.
    46. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
    47. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    48. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    49. Huang, Dashan & Li, Jiangyuan & Wang, Liyao & Zhou, Guofu, 2020. "Time series momentum: Is it there?," Journal of Financial Economics, Elsevier, vol. 135(3), pages 774-794.
    50. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
    51. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    52. Algaba, Andres & Boudt, Kris, 2017. "Generalized financial ratios to predict the equity premium," Economic Modelling, Elsevier, vol. 66(C), pages 244-257.
    53. Swasti R. Khuntia & Jose L. Rueda & Mart A.M.M. Van der Meijden, 2018. "Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model," Energies, MDPI, vol. 11(12), pages 1-19, November.
    54. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    55. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    56. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    57. Richard A. Ashley & Kwok Ping Tsang, 2014. "Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach," Econometrics, MDPI, vol. 2(1), pages 1-20, March.
    58. He, Kaijian & Yu, Lean & Tang, Ling, 2015. "Electricity price forecasting with a BED (Bivariate EMD Denoising) methodology," Energy, Elsevier, vol. 91(C), pages 601-609.
    59. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    60. Li, Xiaowei & Wu, Zhengyu & Zhang, Hao & Zhang, Lu, 2024. "Risk-neutral skewness and stock market returns: A time-series analysis," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    61. Hui Chen & Scott Joslin & Sophie X. Ni, 2019. "Demand for Crash Insurance, Intermediary Constraints, and Risk Premia in Financial Markets," NBER Working Papers 25573, National Bureau of Economic Research, Inc.
    62. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
    63. Ewa Feder-Sempach & Piotr Szczepocki & Wiesław Dębski, 2023. "What if beta is not stable? Applying the Kalman filter to risk estimates of top US companies over the long time horizon," Bank i Kredyt, Narodowy Bank Polski, vol. 54(1), pages 25-44.
    64. Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Reprint: Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 114(C).
    65. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers 17/13, Monash University, Department of Econometrics and Business Statistics.
    66. Jing Tian & Qing Zhou, 2018. "Improving equity premium forecasts by incorporating structural break uncertainty," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 619-656, November.
    67. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
    68. He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.
    69. James Lightwood & Steve Anderson & Stanton A Glantz, 2020. "Predictive validation and forecasts of short-term changes in healthcare expenditure associated with changes in smoking behavior in the United States," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.

  3. Timmermann, Allan & Patton, Andrew, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," CEPR Discussion Papers 8194, C.E.P.R. Discussion Papers.

    Cited by:

    1. Wright, Jonathan H., 2019. "Some observations on forecasting and policy," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1186-1192.
    2. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    3. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    4. Stan Hurn & Jing Tian & Lina Xu, 2021. "Assessing the Informational Content of Official Australian Bureau of Meteorology Forecasts of Wind Speed," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 525-547, December.
    5. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
    6. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    7. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
    8. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
    9. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
    10. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
    11. Qu, Ritong & Timmermann, Allan & Zhu, Yinchu, 2024. "Comparing forecasting performance with panel data," International Journal of Forecasting, Elsevier, vol. 40(3), pages 918-941.
    12. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    13. Hajo Holzmann & Matthias Eulert, 2014. "The role of the information set for forecasting - with applications to risk management," Papers 1404.7653, arXiv.org.
    14. Barbara Rossi & Tatevik Sekhposyan, 2014. "Forecast rationality tests in the presence of instabilities, with applications to Federal Reserve and survey forecasts," Economics Working Papers 1426, Department of Economics and Business, Universitat Pompeu Fabra, revised Nov 2014.
    15. Natsuki Arai, 2016. "Evaluating the Efficiency of the FOMC's New Economic Projections," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 1019-1049, August.
    16. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    17. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2014. "Unemployment Rate Hysteresis and the Great Recession: Exploring the Metropolitan Evidence," Working Papers 1403, University of Nevada, Las Vegas , Department of Economics.
    18. Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2023. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 355-387, July.
    19. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    20. Boussios, David & Skorbiansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," Economic Research Report 327201, United States Department of Agriculture, Economic Research Service.
    21. Jeff Messina & Tara M. Sinclair & Herman O. Stekler, 2014. "What Can We Learn From Revisions To The Greenbook Forecasts?," Working Papers 2014-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    22. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    23. Ardia, David & Hoogerheide, Lennart F., 2014. "GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts," Economics Letters, Elsevier, vol. 123(2), pages 187-190.
    24. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    25. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    26. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Aug 2024.
    27. Goodwin, Thomas & Tian, Jing, 2017. "A state space approach to evaluate multi-horizon forecasts," Working Papers 2017-15, University of Tasmania, Tasmanian School of Business and Economics.
    28. Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
    29. Xavier D'Haultfoeuille & Christophe Gaillac & Arnaud Maurel, 2021. "Rationalizing rational expectations: Characterizations and tests," Quantitative Economics, Econometric Society, vol. 12(3), pages 817-842, July.
    30. Boussios, David & Skoriansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309619, United States Department of Agriculture.
    31. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
    32. Manganelli, Simone, 2016. "Deciding with judgment," Working Paper Series 1947, European Central Bank.
    33. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    34. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    35. Heinisch, Katja, 2024. "Step by step - A quarterly evaluation of EU Commission's GDP forecasts," IWH Discussion Papers 22/2024, Halle Institute for Economic Research (IWH).
    36. Clements, Michael P. & Reade, J. James, 2020. "Forecasting and forecast narratives: The Bank of England Inflation Reports," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1488-1500.
    37. Nathan Goldstein & Ben‐Zion Zilberfarb, 2023. "The closer we get, the better we are?," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 364-376, April.
    38. Jing Tian & Firmin Doko Tchatoka & Thomas Goodwin, 2022. "Are internally consistent forecasts rational?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1338-1355, November.
    39. Han Liu & Yongjing Wang & Haiyan Song & Ying Liu, 2023. "Measuring tourism demand nowcasting performance using a monotonicity test," Tourism Economics, , vol. 29(5), pages 1302-1327, August.
    40. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    41. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
    42. Manganelli, Simone, 2021. "Statistical decision functions with judgment," Working Paper Series 2512, European Central Bank.
    43. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2023. "The accuracy and informativeness of agricultural baselines," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1116-1148, August.
    44. Roberto Casarin, 2014. "A Note on Tractable State-Space Model for Symmetric Positive-Definite Matrices," Working Papers 2014:23, Department of Economics, University of Venice "Ca' Foscari".
    45. Lennart F. Hoogerheide & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann," Tinbergen Institute Discussion Papers 11-131/4, Tinbergen Institute.
    46. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
    47. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    48. Xie, Zixiong & Hsu, Shih-Hsun, 2016. "Time varying biases and the state of the economy," International Journal of Forecasting, Elsevier, vol. 32(3), pages 716-725.
    49. Barbara Rossi, 2011. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 25-29, August.
    50. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
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    123. Glen Livingston & Darfiana Nur, 2020. "Bayesian inference of smooth transition autoregressive (STAR)(k)–GARCH(l, m) models," Statistical Papers, Springer, vol. 61(6), pages 2449-2482, December.
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    127. Ayben Koy, 2017. "Modelling Nonlinear Dynamics of Oil Futures Market," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(1), pages 23-42, June.
    128. Heni Boubaker & Nadia Sghaier, 2015. "On the Dynamic Dependence between US and other Developed Stock Markets: An Extreme-value Time-varying Copula Approach," Bankers, Markets & Investors, ESKA Publishing, issue 136-137, pages 80-93, May-June.
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    131. Samet G nay, 2015. "Markov Regime Switching Generalized Autoregressive Conditional Heteroskedastic Model and Volatility Modeling for Oil Returns," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 979-985.
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    135. Focardi, Sergio M. & Fabozzi, Frank J. & Mazza, Davide, 2019. "Modeling local trends with regime shifting models with time-varying probabilities," International Review of Financial Analysis, Elsevier, vol. 66(C).
    136. Ali Nasir & Ambreen Khursheed & Kazim Ali & Faisal Mustafa, 2021. "A Markov Decision Process Model for Optimal Trade of Options Using Statistical Data," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 327-346, August.
    137. Chavez-Demoulin, V. & Embrechts, P. & Sardy, S., 2014. "Extreme-quantile tracking for financial time series," Journal of Econometrics, Elsevier, vol. 181(1), pages 44-52.
    138. Chauvet, Marcelle & Jiang, Cheng, 2023. "Nonlinear relationship between monetary policy and stock returns: Evidence from the U.S," Global Finance Journal, Elsevier, vol. 55(C).
    139. Shi, Yanlin & Ho, Kin-Yip & Liu, Wai-Man, 2016. "Public information arrival and stock return volatility: Evidence from news sentiment and Markov Regime-Switching Approach," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 291-312.
    140. Iulia LUPU & Adina CRISTE & Anca Dana DRAGU & Teodora Daniela ALBU, 2024. "Volatility Transitions in European Stock Markets: A Clustering-Based Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 65-80, October.
    141. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    142. Gębka, Bartosz & Serwa, Dobromił, 2015. "The elusive nature of motives to trade: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 147-157.
    143. Huang, Yan & Kou, Gang & Peng, Yi, 2017. "Nonlinear manifold learning for early warnings in financial markets," European Journal of Operational Research, Elsevier, vol. 258(2), pages 692-702.
    144. Laura Arenas & Ana Maria Gil-Lafuente, 2021. "Regime Switching in High-Tech ETFs: Idiosyncratic Volatility and Return," Mathematics, MDPI, vol. 9(7), pages 1-25, March.
    145. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    146. David Hallac & Peter Nystrup & Stephen Boyd, 2019. "Greedy Gaussian segmentation of multivariate time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 727-751, September.
    147. Lim, Bryan & Arık, Sercan Ö. & Loeff, Nicolas & Pfister, Tomas, 2021. "Temporal Fusion Transformers for interpretable multi-horizon time series forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1748-1764.
    148. Jana Vychytilová, 2014. "Intermarket Technical Research of the U.S. Capital Markets and the Czech Stock Market Performance," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 62(6), pages 1509-1519.
    149. Alexandre Carbonneau & Fr'ed'eric Godin, 2021. "Deep equal risk pricing of financial derivatives with non-translation invariant risk measures," Papers 2107.11340, arXiv.org.
    150. Timotheos Angelidis & Nikolaos Tessaromatis, 2014. "Global portfolio management under state dependent multiple risk premia," Proceedings of Economics and Finance Conferences 0400966, International Institute of Social and Economic Sciences.
    151. Shi, Yanlin & Feng, Lingbing, 2016. "A discussion on the innovation distribution of the Markov regime-switching GARCH model," Economic Modelling, Elsevier, vol. 53(C), pages 278-288.
    152. Monfort, A. & Renne, J-P., 2011. "Credit and liquidity risks in euro area sovereign yield curves," Working papers 352, Banque de France.
    153. Shaw, Charles, 2018. "Regime-Switching And Levy Jump Dynamics In Option-Adjusted Spreads," MPRA Paper 94154, University Library of Munich, Germany, revised 27 May 2019.
    154. Guidolin, Massimo & Pedio, Manuela, 2017. "Identifying and measuring the contagion channels at work in the European financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 117-134.
    155. An, Sufang & An, Feng & Gao, Xiangyun & Wang, Anjian, 2023. "Early warning of critical transitions in crude oil price," Energy, Elsevier, vol. 280(C).
    156. Mathieu Gatumel & Florian Ielpo, 2011. "The Number of Regimes Across Asset Returns: Identification and Economic Value," Post-Print halshs-00658540, HAL.
    157. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    158. Abhishek Pal Majumder, 2024. "Long time behavior of semi-Markov modulated perpetuity and some related processes," Papers 2410.15824, arXiv.org.
    159. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.
    160. Hasan, Md. Tanvir, 2022. "The sum of all SCARES COVID-19 sentiment and asset return," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 332-346.
    161. Nabil Maghrebi & Mark J. Holmes & Kosuke Oya, 2014. "Financial instability and the short-term dynamics of volatility expectations," Applied Financial Economics, Taylor & Francis Journals, vol. 24(6), pages 377-395, March.
    162. Marcelo Lewin & Carlos Heitor Campani, 2023. "Constrained portfolio strategies in a regime-switching economy," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(1), pages 27-59, March.
    163. Mustafa, Andy Ali & Lin, Ching-Yang & Kakinaka, Makoto, 2022. "Detecting market pattern changes: A machine learning approach," Finance Research Letters, Elsevier, vol. 47(PA).
    164. Nikolaos Papanikolaou, 2020. "Markov-Switching Model of Family Income Quintile Shares," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 48(2), pages 207-222, June.
    165. Khalifa, Ahmed A.A. & Otranto, Edoardo & Hammoudeh, Shawkat & Ramchander, Sanjay, 2016. "Volatility transmission across currencies and commodities with US uncertainty measures," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 63-83.
    166. Zhang, Xiaoyuan & Zhang, Tianqi, 2022. "Barrier option pricing under a Markov Regime switching diffusion model," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 273-280.
    167. Antonello Maruotti & Antonio Punzo, 2021. "Initialization of Hidden Markov and Semi‐Markov Models: A Critical Evaluation of Several Strategies," International Statistical Review, International Statistical Institute, vol. 89(3), pages 447-480, December.
    168. Dichtl, Hubert & Drobetz, Wolfgang & Otto, Tizian, 2023. "Forecasting Stock Market Crashes via Machine Learning," Journal of Financial Stability, Elsevier, vol. 65(C).
    169. Andrea Eross & Andrew Urquhart & Simon Wolfe, 2019. "Investigating risk contagion initiated by endogenous liquidity shocks: evidence from the US and eurozone interbank markets," The European Journal of Finance, Taylor & Francis Journals, vol. 25(1), pages 35-53, January.
    170. Tihana Skrinjaric, 2023. "Leading indicators of financial stress in Croatia: a regime switching approach," Public Sector Economics, Institute of Public Finance, vol. 47(2), pages 205-232.
    171. Timothy M. Christensen, 2020. "Existence and uniqueness of recursive utilities without boundedness," Papers 2008.00963, arXiv.org, revised Aug 2021.
    172. Pedro Braga & Georgios Chionas & Piotr Krysta & Stefanos Leonardos & Georgios Piliouras & Carmine Ventre, 2024. "MEV Sharing with Dynamic Extraction Rates," Papers 2402.15849, arXiv.org, revised Sep 2024.
    173. Razvan Oprisor & Roy Kwon, 2020. "Multi-Period Portfolio Optimization with Investor Views under Regime Switching," JRFM, MDPI, vol. 14(1), pages 1-31, December.
    174. Mittelstaedt, Christian & Baumgärtner, Stefan, 2022. "Attribution of Collective Causal Responsibility to Individual Actors in a Stochastic System," VfS Annual Conference 2022 (Basel): Big Data in Economics 264051, Verein für Socialpolitik / German Economic Association.
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    178. Yao, Haixiang & Li, Danping & Wu, Huiling, 2022. "Dynamic trading with uncertain exit time and transaction costs in a general Markov market," International Review of Financial Analysis, Elsevier, vol. 84(C).

  5. Kenny, Geoff & Genre, Véronique & Meyler, Aidan & Timmermann, Allan, 2010. "Combining the forecasts in the ECB survey of professional forecasters: can anything beat the simple average?," Working Paper Series 1277, European Central Bank.

    Cited by:

    1. Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
    2. Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    3. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.
    4. Hubrich, Kirstin & Skudelny, Frauke, 2016. "Forecast combination for euro area inflation: a cure in times of crisis?," Working Paper Series 1972, European Central Bank.
    5. Jung, Alexander & El-Shagi, Makram & Giesen, Sebastian, 2013. "Does Central Bank Staff Beat Private Forecasters?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79925, Verein für Socialpolitik / German Economic Association.
    6. Kurmas Akdogan & Selen Baser & Meltem Gulenay Chadwick & Dilara Ertug & Timur Hulagu & Sevim Kosem & Fethi Ogunc & M. Utku Ozmen & Necati Tekatli, 2012. "Short-Term Inflation Forecasting Models For Turkey and a Forecast Combination Analysis," Working Papers 1209, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    7. Gianni Amisano & Andreas Beyer & Michele Lenza, 2010. "Enhancing monetary analysis," Research Bulletin, European Central Bank, vol. 11, pages 2-6.
    8. Clements, Michael P., 2012. "Subjective and Ex Post Forecast Uncertainty: US Inflation and Output Growth," Economic Research Papers 270629, University of Warwick - Department of Economics.
    9. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    10. Gary Koop & Luca Onorante, 2011. "Estimating Phillips Curves in Turbulent Times using the ECBs Survey of Professional Forecasters," Working Papers 1109, University of Strathclyde Business School, Department of Economics.
    11. Martin Scheicher, 2010. "“Return-free risk”? Market pricing in credit risk markets," Research Bulletin, European Central Bank, vol. 11, pages 7-8.
    12. Luis E. Rojas, 2011. "Professional Forecasters: How to Understand and Exploit Them Through a DSGE Model," Borradores de Economia 664, Banco de la Republica de Colombia.
    13. Schnatz, Bernd & D'Agostino, Antonello, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.
    14. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    15. Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.
    16. Geoff Kenny, 2010. "Macroeconomic forecasting: can forecast combination help?," Research Bulletin, European Central Bank, vol. 11, pages 9-12.
    17. Oinonen, Sami & Paloviita, Maritta, 2014. "Analysis of aggregated inflation expectations based on the ECB SPF survey," Bank of Finland Research Discussion Papers 29/2014, Bank of Finland.

  6. Timmermann, Allan & Aiolfi, Marco & Catão, Luís, 2010. "Common Factors in Latin America?s Business Cycles," CEPR Discussion Papers 7671, C.E.P.R. Discussion Papers.

    Cited by:

    1. Luis A. V. Catao & Ana Fostel & Sandeep Kapur, 2008. "Persistent Gaps and Default Traps," Birkbeck Working Papers in Economics and Finance 0803, Birkbeck, Department of Economics, Mathematics & Statistics.
    2. Melisso Boschi & Alessandro Girardi, 2008. "The contribution of domestic, regional, and international factors to Latin America’s business cycle," ISAE Working Papers 105, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    3. Spinola, Danilo, 2023. "Instability constraints and development traps: an empirical analysis of growth cycles and economic volatility in Latin America," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    4. Pontines, Victor, 2017. "The financial cycles in four East Asian economies," Economic Modelling, Elsevier, vol. 65(C), pages 51-66.
    5. Sumru Altuğ & Melike Bildirici, 2010. "Business Cycles around the Globe: A Regime Switching Approach," Working Papers 0032, Yildiz Technical University, Department of Economics, revised Mar 2010.
    6. Nauro F. Campos & Menelaos G. Karanasos & Michail Karoglou & Panagiotis Koutroumpis & Constantin Zopounidis & Apostolos Christopoulos, 2022. "Apocalypse now, apocalypse when? Economic growth and structural breaks in Argentina (1886–2003)," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 30(1), pages 3-32, January.
    7. Luciano Campos & Jesús Ruiz Andújar, 2022. "Common and idiosyncratic components of Latin American business cycles connectedness," Journal of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 691-722, December.
    8. Rodriguez, Diego & Gonzalez, Andres & Fernandez, Andres, 2015. "Sharing a Ride on the Commodities Roller Coaster: Common Factors in Business Cycles of Emerging Economies," IDB Publications (Working Papers) 7382, Inter-American Development Bank.
    9. Guglielmo Maria Caporale & Alessandro Girardi, 2012. "Business Cycles, International Trade and Capital Flows: Evidence from Latin America," Discussion Papers of DIW Berlin 1254, DIW Berlin, German Institute for Economic Research.
    10. Jean-Pierre Allegret & Alain Sand-Zantman, 2009. "Does a Monetary Union protect again shocks? An assessment of Latin American integration," Post-Print halshs-00371069, HAL.
    11. Mejía-Reyes, Pablo & Rendón-Rojas, Liliana & Vergara-González, Reyna & Aroca, Patricio, 2018. "International synchronization of the Mexican states business cycles: Explaining factors," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 278-288.
    12. Allegret, Jean-Pierre & Sand-Zantman, Alain, 2009. "Does a Monetary Union protect against external shocks?: An assessment of Latin American integration," Journal of Policy Modeling, Elsevier, vol. 31(1), pages 102-118.
    13. Issler, Joao Victor & Notini, Hilton & Rodrigues, Claudia & Soares, Ana Flávia, 2013. "Constructing coincident indices of economic activity for the Latin American economy," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    14. Christian Rohe, 2016. "On shock symmetry in South America: New evidence from intra-Brazilian real exchange rates," CQE Working Papers 5316, Center for Quantitative Economics (CQE), University of Muenster.
    15. Delalibera, Bruno Ricardo & Issler, João Victor & Branco, Roberto da Cunha Castello, 2017. "Using common features to investigate common growth cycles for BRICS Countries," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 784, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    16. Alfredo M. Leone & Jorge I. Canales Kriljenko & Rodolfo Maino, 2023. "The Long and Widening Gap: Analyzing Structural Breaks in Argentina’s Economic Decline," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 29(4), pages 243-259, November.
    17. Timmermann, Allan & Aiolfi, Marco & Catão, Luís, 2010. "Common Factors in Latin America?s Business Cycles," CEPR Discussion Papers 7671, C.E.P.R. Discussion Papers.
    18. Gonzalo Hernández & María Alejandra Prieto, 2020. "Terms of trade shocks and taxation in developing countries," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 39(81), pages 613-634, July.
    19. Andrea Bonilla, 2014. "An Examination of the Convergence in the Output of South American Countries: The Influence of the Region's Integration Projects," Working Papers halshs-01069353, HAL.
    20. Mr. Jeromin Zettelmeyer, 2006. "Growth and Reforms in Latin America: A Survey of Facts and Arguments," IMF Working Papers 2006/210, International Monetary Fund.
    21. Matthias Morys & Martin Ivanov, 2013. "The emergence of a European region: Business cycles in South-East Europe from political independence to World War II," Centre for Historical Economics and Related Research at York (CHERRY) Discussion Papers 13/01, CHERRY, c/o Department of Economics, University of York.
    22. Jean-Pierre Allegret & Alain Sand-Zantman, 2008. "Does a Monetary Union protect again foreign shocks? An assessment of Latin American integration using a Bayesian VAR," Post-Print halshs-00269122, HAL.
    23. Matthias Morys & Martin Ivanov, 2009. "Common factors in South-East Europe’s business cycles 1899 - 1989," SEEMHN papers 1, National Bank of Serbia.
    24. Gannon, Gerard L. & Thuraisamy, Kannan S., 2017. "Sovereign risk and the impact of crisis: Evidence from Latin AmericaAuthor-Name: Batten, Jonathan A," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 328-350.
    25. Campos, Nauro F. & Karanasos, Menelaos G. & Tan, Bin, 2012. "Two to tangle: Financial development, political instability and economic growth in Argentina," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 290-304.
    26. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "An information diffusion-based model of oil futures price," Energy Economics, Elsevier, vol. 36(C), pages 518-525.
    27. Ibarra-Ramírez Raúl, 2010. "Forecasting Inflation in Mexico Using Factor Models: Do Disaggregated CPI Data Improve Forecast Accuracy?," Working Papers 2010-01, Banco de México.
    28. Sebastian Fossati, 2017. "Output Growth And Structural Reform In Latin America: Have Business Cycles Changed?," Contemporary Economic Policy, Western Economic Association International, vol. 35(1), pages 62-75, January.
    29. Mr. Anoop Singh, 2006. "Macroeconomic Volatility: The Policy Lessons from Latin America," IMF Working Papers 2006/166, International Monetary Fund.
    30. Andrea Bonilla Bolanos, 2014. "An Examination of the Convergence in the Output of South American Countries: The Influence of the Region’s Integration Projects," Working Papers 1424, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    31. Carlos Barros & Guglielmo Maria Caporale & Luis Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73.
    32. James N. Blignaut & Jan H. van Heerden, 2015. "Is Water Shedding Next?," Working Papers 50, Economic Research Southern Africa.
    33. Hallin, Marc & Liska, Roman, 2011. "Dynamic factors in the presence of blocks," Journal of Econometrics, Elsevier, vol. 163(1), pages 29-41, July.
    34. Gutiérrez, Mario A., 2007. "Economic growth in Latin America and the Caribbean: growth transitions rather than steady states," Macroeconomía del Desarrollo 5425, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    35. Andrea Bonilla BOLAÑOS, 2017. "Are South American Countries Really Converging?: The Influence of the Region's Integration Projects," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 130-149, September.

  7. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Maurin, Laurent & Drechsel, Katja, 2008. "Flow of conjunctural information and forecast of euro area economic activity," Working Paper Series 925, European Central Bank.
    2. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    3. Kakuho Furukawa & Ryohei Hisano & Yukio Minoura & Tomoyuki Yagi, 2022. "A Nowcasting Model of Industrial Production using Alternative Data and Machine Learning Approaches," Bank of Japan Working Paper Series 22-E-16, Bank of Japan.
    4. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    5. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    6. Nucera, Federico & Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2016. "The information in systemic risk rankings," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 461-475.
    7. Yannick Viossat & Andriy Zapechelnyuk, 2013. "No-regret Dynamics and Fictitious Play," Post-Print hal-00713871, HAL.
    8. Carlo Altavilla & Matteo Ciccarelli, 2006. "Inflation Forecasts, Monetary Policy and Unemployment Dynamics: Evidence from the US and the Euro Area," Discussion Papers 7_2006, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
    9. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
    10. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    11. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    12. Narayan Kundan Kishor, 2021. "Forecasting real‐time economic activity using house prices and credit conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 213-227, March.
    13. Menkhoff, Lukas & Sakha, Sahra, 2017. "Estimating risky behavior with multiple-item risk measures," Journal of Economic Psychology, Elsevier, vol. 59(C), pages 59-86.
    14. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
    15. Ghysels, Eric & Ozkan, Nazire, 2015. "Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1009-1020.
    16. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    17. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    18. Massimiliano Marcellino, 2007. "Pooling‐Based Data Interpolation and Backdating," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(1), pages 53-71, January.
    19. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    20. Wilson, Kevin J., 2017. "An investigation of dependence in expert judgement studies with multiple experts," International Journal of Forecasting, Elsevier, vol. 33(1), pages 325-336.
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    2. Sebastian Bunnenberg & Martin Rohleder & Hendrik Scholz & Marco Wilkens, 2019. "Jensen's alpha and the market‐timing puzzle," Review of Financial Economics, John Wiley & Sons, vol. 37(2), pages 234-255, April.
    3. Michael A.S. Joyce & Zhuoshi Liu & Ian Tonks, 2017. "Institutional Investors and the QE Portfolio Balance Channel," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(6), pages 1225-1246, September.
    4. Platanakis, Emmanouil & Sutcliffe, Charles & Ye, Xiaoxia, 2021. "Horses for courses: Mean-variance for asset allocation and 1/N for stock selection," European Journal of Operational Research, Elsevier, vol. 288(1), pages 302-317.
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    7. Joyce, Michael & Liu, Zhuoshi & Tonks, Ian, 2014. "Institutional investor portfolio allocation, quantitative easing and the global financial crisis," Bank of England working papers 510, Bank of England.
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    9. Andonov, Aleksandar & Eichholtz, Piet & Kok, Nils, 2015. "Intermediated investment management in private markets: Evidence from pension fund investments in real estate," Journal of Financial Markets, Elsevier, vol. 22(C), pages 73-103.
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    14. Rossi, Alberto G. & Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2015. "Network centrality and pension fund performance," CFR Working Papers 15-16, University of Cologne, Centre for Financial Research (CFR).
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    23. Matteo Bonetti, 2021. "Pension Fund Equity Performance: Herding Does Not Pay Off," Working Papers 729, DNB.
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    25. Xu, Ruihui & Zhang, Xuliang & Gozgor, Giray & Lau, Chi Keung Marco & Yan, Cheng, 2023. "Investor flow-chasing and price–performance puzzle: Evidence from global infrastructure funds," Research in International Business and Finance, Elsevier, vol. 65(C).
    26. Timmermann, Allan & Lunde, Asger & Groenborg, Niels & Wermers, Russ, 2017. "Picking Funds with Confidence," CEPR Discussion Papers 11896, C.E.P.R. Discussion Papers.
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    30. Yue Xu, 2021. "Spillovers of Senior Mutual Fund Managers’ Capital Raising Ability," CREATES Research Papers 2022-03, Department of Economics and Business Economics, Aarhus University.
    31. Gordon Cookson & Tim Jenkinson & Howard Jones & Jose Vicente Martinez, 2022. "Virtual Reality? Investment Consultants’ Claims About Their Own Performance," Management Science, INFORMS, vol. 68(11), pages 8301-8318, November.
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    35. Sabri Boubaker & Dimitrios Gounopoulos & Duc Khuong Nguyen & Nikos Paltalidis, 2016. "Assessing the Effects of Unconventional Monetary Policy on Pension Funds Risk Incentives," Working Papers 2016-005, Department of Research, Ipag Business School.
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    1. Baghestani, Hamid & Khallaf, Ashraf, 2012. "Predictions of growth in U.S. corporate profits: Asymmetric vs. symmetric loss," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 222-229.

  10. Pesaran, M.H. & Pick, A. & Timmermann, A., 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," Cambridge Working Papers in Economics 0901, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Lobanov, Mikhail (Лобанов, Михаил) & Zvezdvanovic-Lobanova, Jelena (Звезданович-Лобанова, Елена), 2017. "Specifics of Agricultural Policy in the Countries of Central-Eastern and South-Eastern Europe in 1990–2010s [Особенности Аграрной Политики В Странах Центрально- И Юго-Восточной Европы В 1990-2010-Х," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 3, pages 150-173, June.

  11. Carlos Capistrán & Allan Timmermann, 2008. "Disagreement and Biases in Inflation Expectations," CREATES Research Papers 2008-56, Department of Economics and Business Economics, Aarhus University.

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    1. Bernd Hayo & Florian Neumeier, 2018. "Households’ Inflation Perceptions and Expectations: Survey Evidence from New Zealand," ifo Working Paper Series 255, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
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    3. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    4. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
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    6. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
    7. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    8. Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," Bank of Israel Working Papers 2020.11, Bank of Israel.
    9. Ahrens, Steffen & Lustenhouwer, Joep & Tettamanzi, Michele, 2017. "The Stabilizing Role of Forward Guidance: A Macro Experiment," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168063, Verein für Socialpolitik / German Economic Association.
    10. Boonlert Jitmaneeroj & Michael Lamla, 2018. "The Implications of Central Bank Transparency for Uncertainty and Disagreement," KOF Working papers 18-445, KOF Swiss Economic Institute, ETH Zurich.
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    126. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2013. "A note on forecasting the prices of gold and silver: Asymmetric loss and forecast rationality," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(3), pages 294-301.
    127. Gbaguidi, David, 2012. "La courbe de Phillips : temps d’arbitrage et/ou arbitrage de temps," L'Actualité Economique, Société Canadienne de Science Economique, vol. 88(1), pages 87-119, mars.
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    129. Ryan Banerjee & Aaron Mehrotra, 2021. "Disagreeing during Deflations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(7), pages 1867-1885, October.
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  12. Davide Pettenuzzo & Allan G. Timmermann & Rossen I. Valkanov, 2008. "Return Predictability under Equilibrium Constraints on the Equity Premium," Working Papers 37, Brandeis University, Department of Economics and International Business School.

    Cited by:

    1. Rangan Gupta & Mampho P. Modise & Josine Uwilingiye, 2011. "Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors," Working Papers 201122, University of Pretoria, Department of Economics.

  13. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
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    3. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    4. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    5. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    6. Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
    7. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    8. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
    9. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    10. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    11. Narayan Kundan Kishor, 2021. "Forecasting real‐time economic activity using house prices and credit conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 213-227, March.
    12. Menkhoff, Lukas & Sakha, Sahra, 2017. "Estimating risky behavior with multiple-item risk measures," Journal of Economic Psychology, Elsevier, vol. 59(C), pages 59-86.
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    Cited by:

    1. Pfajfar, D. & Zakelj, B., 2012. "Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of CentER DP 2011-053)," Discussion Paper 2012-072, Tilburg University, Center for Economic Research.
    2. Pfajfar, D. & Zakelj, B., 2012. "Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of EBC DP 2011-014)," Other publications TiSEM 2b92a09f-918e-4614-978d-0, Tilburg University, School of Economics and Management.
    3. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    4. Pfajfar, D. & Zakelj, B., 2012. "Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of CentER DP 2011-053)," Other publications TiSEM 38fac5ce-fe8f-4b61-a679-f, Tilburg University, School of Economics and Management.
    5. Fernandes, Marcelo & Thiele, Eduardo, 2015. "The Macroeconomic Determinants of the Term Structure of Inflation Expectations in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    6. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.

  15. Allan Timmermann & Bruce N. Lehmann, 2007. "Performance Measurement and Evaluation," FMG Discussion Papers dp604, Financial Markets Group.

    Cited by:

    1. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2016. "A review of behavioural and management effects in mutual fund performance," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 162-176.
    2. Cuthbertson, Keith & Nitzsche, Dirk, 2013. "Performance, stock selection and market timing of the German equity mutual fund industry," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 86-101.

  16. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.

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    1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    2. Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," Papers 2010.08463, arXiv.org, revised Nov 2021.
    3. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    4. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    5. Luca Brugnolini, 2018. "Forecasting Deflation Probability in the EA: A Combinatoric Approach," CBM Working Papers WP/01/2018, Central Bank of Malta.
    6. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    7. Anwen Yin, 2022. "Does the kitchen‐sink model work forecasting the equity premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 223-247, March.
    8. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2024. "Tests for equal forecast accuracy under heteroskedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 850-869, August.
    9. Kilian, Lutz & Alquist, Ron, 2007. "What Do We Learn from the Price of Crude Oil Futures?," CEPR Discussion Papers 6548, C.E.P.R. Discussion Papers.
    10. Ghysels, Eric & Ozkan, Nazire, 2015. "Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1009-1020.
    11. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    12. Massimiliano Marcellino, 2007. "Pooling‐Based Data Interpolation and Backdating," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(1), pages 53-71, January.
    13. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    14. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    15. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    16. Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2020. "Nonlinear forecast combinations: An example using euro-area real GDP growth," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 579-589.
    17. Brice Corgnet & Cary Deck & Mark Desantis & David Porter, 2022. "Forecasting Skills in Experimental Market : Illusion or Reality?," Post-Print hal-04325544, HAL.
    18. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    19. Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
    20. Jin, Xiaoye, 2022. "Performance of intraday technical trading in China’s gold market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    21. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
    22. Qiu, Yue & Zheng, Yuchen, 2023. "Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations," Economic Modelling, Elsevier, vol. 125(C).
    23. Shahzad Ahmad & Farooq Pasha, 2015. "A Pragmatic Model for Monetary Policy Analysis I: The Case of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 1-42.
    24. Becker, Sascha & Nautz, Dieter, 2010. "Inflation, price dispersion and market integration through the lens of a monetary search model," Discussion Papers 2010/2, Free University Berlin, School of Business & Economics.
    25. Medel, Carlos A., 2017. "Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy," MPRA Paper 78439, University Library of Munich, Germany.
    26. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    27. Pinto, Jeronymo Marcondes & Marçal, Emerson Fernandes, 2019. "Cross-validation based forecasting method: a machine learning approach," Textos para discussão 498, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    28. Oleg Korenok & Stanislav Radchenko & Norman R. Swanson, 2010. "International evidence on the efficacy of new‐Keynesian models of inflation persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 31-54, January.
    29. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    30. Masayoshi Hayashi, 2012. "Forecasting Welfare Caseloads: The Case of the Japanese Public Assistance Program," CIRJE F-Series CIRJE-F-846, CIRJE, Faculty of Economics, University of Tokyo.
    31. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
    32. Edda Claus, 2011. "Seven Leading Indexes of New Zealand Employment," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 76-89, March.
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    178. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    179. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The University of Manchester.
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    195. Xiaoye Jin, 2022. "Evaluating the predictive power of intraday technical trading in China's crude oil market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1416-1432, November.
    196. David Schröder, 2020. "The role of market efficiency on implied cost of capital estimates: an international perspective," Annals of Finance, Springer, vol. 16(4), pages 463-499, December.
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    200. Catherine L. Kling & Raymond W. Arritt & Gray Calhoun & David A. Keiser, 2017. "Integrated Assessment Models of the Food, Energy, and Water Nexus: A Review and an Outline of Research Needs," Annual Review of Resource Economics, Annual Reviews, vol. 9(1), pages 143-163, October.
    201. Bizer, Kilian & Meub, Lukas & Proeger, Till & Spiwoks, Markus, 2014. "Strategic coordination in forecasting: An experimental study," University of Göttingen Working Papers in Economics 195, University of Goettingen, Department of Economics.
    202. Kuangyu Wen, 2023. "A semiparametric spatio‐temporal model of crop yield trend and its implication to insurance rating," Agricultural Economics, International Association of Agricultural Economists, vol. 54(5), pages 662-673, September.
    203. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    204. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    205. Kaiji Motegi & Xiaojing Cai & Shigeyuki Hamori & Haifeng Xu, 2020. "Moving average threshold heterogeneous autoregressive (MAT‐HAR) models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1035-1042, November.
    206. Leonard I. Nakamura & Tom Stark, 2007. "Mismeasured personal saving and the permanent income hypothesis," Working Papers 07-8, Federal Reserve Bank of Philadelphia.
    207. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    208. Todd E. Clark & Taisuke Nakata, 2006. "The trend growth rate of employment : past, present, and future," Economic Review, Federal Reserve Bank of Kansas City, vol. 91(Q I), pages 43-85.
    209. Nicolas Sirven & Brigitte Santos-Eggimann & Jacques Spagnoli, 2008. "Comparability of Health Care Responsiveness in Europe using anchoring vignettes from SHARE," Working Papers DT15, IRDES institut for research and information in health economics, revised Sep 2008.
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    215. Bennedsen, Mikkel & Lunde, Asger & Shephard, Neil & Veraart, Almut E.D., 2023. "Inference and forecasting for continuous-time integer-valued trawl processes," Journal of Econometrics, Elsevier, vol. 236(2).
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  17. Timmermann, Allan & Guidolin, Massimo, 2007. "Forecasts of US Short-term Interest Rates: A Flexible Forecast Combination Approach," CEPR Discussion Papers 6188, C.E.P.R. Discussion Papers.

    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    2. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova & Michael Obersteiner, 2024. "Regime‐dependent commodity price dynamics: A predictive analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2822-2847, November.
    3. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
    4. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2014. "Understanding the Impact of Monetary Policy Shocks on the Corporate Bond Market in Good and Bad Times: A Markov Switching Model," BAFFI CAREFIN Working Papers 1623, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    5. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    6. Verena Monschang & Bernd Wilfling, 2022. "A procedure for upgrading linear-convex combination forecasts with an application to volatility prediction," CQE Working Papers 9722, Center for Quantitative Economics (CQE), University of Muenster.
    7. John M. Maheu & Qiao Yang, 2015. "An Infinite Hidden Markov Model for Short-term Interest Rates," Working Paper series 15-05, Rimini Centre for Economic Analysis.
    8. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    9. Marco Del Negro & Raiden B. Hasegawa & Frank Schorfheide, 2014. "Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance," PIER Working Paper Archive 14-034, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    10. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2015. "The Impact of Monetary Policy on Corporate Bonds under Regime Shifts," Working Papers 562, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    11. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    12. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    13. Apostolos Thomadakis, 2012. "Contagion or Flight-to-Quality Phenomena in Stock and Bond Returns," School of Economics Discussion Papers 0612, School of Economics, University of Surrey.
    14. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.
    15. Massimo Guidolin & Federica Ria, 2010. "Regime shifts in mean-variance efficient frontiers: some international evidence," Working Papers 2010-040, Federal Reserve Bank of St. Louis.
    16. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    17. Avino, Davide & Nneji, Ogonna, 2014. "Are CDS spreads predictable? An analysis of linear and non-linear forecasting models," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 262-274.
    18. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
    19. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    20. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    21. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    22. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    23. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    24. Miguel Belmonte & Gary Koop, 2013. "Model Switching and Model Averaging in Time-Varying Parameter Regression Models," Working Papers 1302, University of Strathclyde Business School, Department of Economics.
    25. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    26. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    27. Chen, Ying & Niu, Linlin, 2014. "Adaptive dynamic Nelson–Siegel term structure model with applications," Journal of Econometrics, Elsevier, vol. 180(1), pages 98-115.
    28. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    29. Sadayuki Ono, 2007. "Term Structure Dynamics in a Monetary Economy with Learning," Discussion Papers 07/29, Department of Economics, University of York.
    30. Daniel L. Thornton, 2005. "Predictions of short-term rates and the expectations hypothesis of the term structure of interest rates," Working Papers 2004-010, Federal Reserve Bank of St. Louis.
    31. Safari, Ali & Davallou, Maryam, 2018. "Oil price forecasting using a hybrid model," Energy, Elsevier, vol. 148(C), pages 49-58.
    32. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    33. Hamid Baghestani & Mohammad Arzaghi & Ilker Kaya, 2015. "On the accuracy of Blue Chip forecasts of interest rates and country risk premiums," Applied Economics, Taylor & Francis Journals, vol. 47(2), pages 113-122, January.
    34. Michiel D. de Pooter & Francesco Ravazzolo & Dick van Dijk, 2007. "Predicting the Term Structure of Interest Rates: Incorporating Parameter Uncertainty, Model Uncertainty and Macroeconomic Information," Tinbergen Institute Discussion Papers 07-028/4, Tinbergen Institute.
    35. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    36. Zhu, Xiaoneng & Rahman, Shahidur, 2015. "A regime-switching Nelson–Siegel term structure model of the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 1-17.
    37. Jia Liu & John M. Maheu, 2018. "Improving Markov switching models using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 297-318, April.
    38. Massimo Guidolin & Stuart Hyde, 2008. "Equity portfolio diversification under time-varying predictability and comovements: evidence from Ireland, the US, and the UK," Working Papers 2008-005, Federal Reserve Bank of St. Louis.
    39. Ravazzolo, F. & van Dijk, H.K. & Verbeek, M.J.C.M., 2007. "Predictive gains from forecast combinations using time-varying model weights," Econometric Institute Research Papers EI 2007-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    40. Xiaojing Xi & Rogemar Mamon, 2014. "Capturing the Regime-Switching and Memory Properties of Interest Rates," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 307-337, October.
    41. Lin-Yee Hin & Nikolai Dokuchaev, 2016. "Short Rate Forecasting Based On The Inference From The Cir Model For Multiple Yield Curve Dynamics," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-33, March.
    42. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
    43. Guidolin, Massimo & Pedio, Manuela, 2019. "Forecasting and trading monetary policy effects on the riskless yield curve with regime switching Nelson–Siegel models," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    44. Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014. "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 21-54.
    45. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.

  18. Timmermann, Allan & Patton, Andrew, 2007. "Learning in Real Time: Theory and Empirical Evidence from the Term Structure of Survey Forecasts," CEPR Discussion Papers 6526, C.E.P.R. Discussion Papers.

    Cited by:

    1. Kajal Lahiri & Xuguang Sheng, 2008. "Measuring Forecast Uncertainty by Disagreement: The Missing Link," ifo Working Paper Series 60, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
    3. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

  19. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Theofanis Archontakis & Wolfgang Lemke, 2008. "Threshold Dynamics of Short‐term Interest Rates: Empirical Evidence and Implications for the Term Structure," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 37(1), pages 75-117, February.
    2. Lütkebohmert, Eva & Gordy, Michael B., 2007. "Granularity adjustment for Basel II," Discussion Paper Series 2: Banking and Financial Studies 2007,01, Deutsche Bundesbank.
    3. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, December.
    4. Philip Vermeulen & Daniel Dias & Maarten Dossche & Erwan Gautier & Ignacio Hernando & Roberto Sabbatini & Harald Stahl, 2007. "Price setting in the euro area : some stylised facts from individual producer price data," Working Paper Research 111, National Bank of Belgium.
    5. Ramb, Fred, 2007. "Corporate marginal tax rate, tax loss carryforwards and investment functions: empirical analysis using a large German panel data set," Discussion Paper Series 1: Economic Studies 2007,21, Deutsche Bundesbank.
    6. Frey, Rainer & Hussinger, Katrin, 2006. "The Role of Technology in M&As: A Firm Level Comparison of Cross-Border and Domestic Deals," ZEW Discussion Papers 06-069, ZEW - Leibniz Centre for European Economic Research.
    7. Schmieder, Christian & Reinschmidt, Timo & Mager, Ferdinand & Gerke, Wolfgang, 2006. "Empirical risk analysis of pension insurance: the case of Germany," Discussion Paper Series 2: Banking and Financial Studies 2006,07, Deutsche Bundesbank.
    8. Klaus Adam & Albert Marcet, 2011. "Internal Rationality, Imperfect Market Knowledge and Asset Prices," CEP Discussion Papers dp1068, Centre for Economic Performance, LSE.
    9. Pausch, Thilo, 2007. "Endogenous credit derivatives and bank behavior," Discussion Paper Series 2: Banking and Financial Studies 2007,16, Deutsche Bundesbank.
    10. Aoki, Kosuke & Kimura, Takeshi, 2007. "Uncertainty about perceived inflation target and monetary policy," Discussion Paper Series 1: Economic Studies 2007,18, Deutsche Bundesbank.
    11. Heijdra, B.J. & Ligthart, J.E., 2006. "The Transitional Dynamics of Fiscal Policy in Small Open Economies," Other publications TiSEM 0012a555-1a7d-464e-baae-c, Tilburg University, School of Economics and Management.
    12. Kick, Thomas & Koetter, Michael, 2007. "Slippery slopes of stress: Ordered failure events in German banking," Journal of Financial Stability, Elsevier, vol. 3(2), pages 132-148, July.
    13. Dasgupta, Partha, 2010. "The Place of Nature in Economic Development," Handbook of Development Economics, in: Dani Rodrik & Mark Rosenzweig (ed.), Handbook of Development Economics, edition 1, volume 5, chapter 0, pages 4977-5046, Elsevier.
    14. Gandré, Pauline, 2015. "Asset prices and information disclosure under recency-biased learning," CEPREMAP Working Papers (Docweb) 1515, CEPREMAP.
    15. Koetter, Michael & Karmann, Alexander & Fiorentino, Elisabetta, 2006. "The cost efficiency of German banks: a comparison of SFA and DEA," Discussion Paper Series 2: Banking and Financial Studies 2006,10, Deutsche Bundesbank.
    16. Sascha Becker & Marc-Andreas Muendler & Sascha O. Becker, 2006. "The Effect of FDI on Job Separation," CESifo Working Paper Series 1864, CESifo.
    17. Beck, Günter W. & Wieland, Volker, 2006. "Money in monetary policy design under uncertainty: The two-pillar Phillips curve versus ECB-style cross-checking," CFS Working Paper Series 2007/17, Center for Financial Studies (CFS).
    18. T M Niguez & I Paya & D Peel & J Perote, 2011. "On the stability of the CRRA utility under high degrees of uncertainty," Working Papers 615773, Lancaster University Management School, Economics Department.
    19. Tödter, Karl-Heinz & Manzke, Bernhard, 2007. "The welfare effects of inflation: a cost-benefit perspective," Discussion Paper Series 1: Economic Studies 2007,33, Deutsche Bundesbank.
    20. Lemke, Wolfgang, 2007. "An affine macro-finance term structure model for the euro area," Discussion Paper Series 1: Economic Studies 2007,13, Deutsche Bundesbank.
    21. Binder, Michael & Offermanns, Christian J., 2007. "International investment positions and exchange rate dynamics: a dynamic panel analysis," Discussion Paper Series 1: Economic Studies 2007,23, Deutsche Bundesbank.
    22. Christian Schoder & Christian R. Proaño & Willi Semmler, 2012. "Are the current account imbalances between EMU countries sustainable?," IMK Working Paper 90-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    23. Raabe, K. & Arnold, I.J.M. & Kool, C.J.M., 2006. "Industries and the bank lending effects of bank credit demand and monetary policy in Germany," Research Memorandum 006, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    24. Hashem M. Pesaran & Ron P. Smith, 2011. "Beyond the DSGE Straitjacket," CESifo Working Paper Series 3447, CESifo.
    25. Ziegler, Christina & Eickmeier, Sandra, 2006. "How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Discussion Paper Series 1: Economic Studies 2006,42, Deutsche Bundesbank.
    26. Faria, Pedro & Schmidt, Tobias, 2007. "International cooperation on innovation: empirical evidence for German and Portuguese firms," Discussion Paper Series 1: Economic Studies 2007,30, Deutsche Bundesbank.
    27. Hakenes, Hendrik & Fecht, Falko, 2006. "Money market derivatives and the allocation of liquidity risk in the banking sector," Discussion Paper Series 2: Banking and Financial Studies 2006,12, Deutsche Bundesbank.
    28. M. Hashem Pesaran & Ron P. Smith, 2006. "Macroeconometric Modelling with a Global Perspective," CESifo Working Paper Series 1659, CESifo.
    29. Loretan, Michael Stanislaus & Kurz-Kim, Jeong-Ryeol, 2007. "A note on the coefficient of determination in regression models with infinite-variance variables," Discussion Paper Series 1: Economic Studies 2007,10, Deutsche Bundesbank.
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    1. Axel Stahmer, 2015. "Fund flows inducing mispricing of risk in competitive financial markets," ESMT Research Working Papers ESMT-15-04, ESMT European School of Management and Technology.
    2. Vayanos, Dimitri & Jiang, Hao & Zheng, Lu, 2020. "Tracking Biased Weights: Asset Pricing Implications of Value-Weighted Indexing," CEPR Discussion Papers 15563, C.E.P.R. Discussion Papers.
    3. Opazo, Luis & Raddatz, Claudio & Schmukler, Sergio L., 2014. "Institutional investors and long-term investment : evidence from Chile," Policy Research Working Paper Series 6922, The World Bank.
    4. Stracca, Livio, 2005. "Delegated portfolio management: a survey of the theoretical literature," Working Paper Series 520, European Central Bank.
    5. Johnson, Timothy C., 2016. "Rethinking reversals," Journal of Financial Economics, Elsevier, vol. 120(2), pages 211-228.
    6. Don U. A. Galagedera & John Watson, 2015. "Benchmarking superannuation funds based on relative performance," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2959-2973, June.
    7. Buffa, Andrea & Vayanos, Dimitri & Woolley, Paul, 2014. "Asset management contracts and equilibrium prices," LSE Research Online Documents on Economics 119026, London School of Economics and Political Science, LSE Library.
    8. Luis Opazo & Claudio Raddatz & Sergio Schmukler, 2009. "The Long And The Short Of Emerging Market Debt," Working Papers Central Bank of Chile 530, Central Bank of Chile.
    9. Gehrig, Thomas P. & Lütje, Torben & Menkhoff, Lukas, 2008. "Bonus Payments and Fund Managers' Behavior: Trans-Atlantic Evidence," Hannover Economic Papers (HEP) dp-411, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    10. Galagedera, Don U.A. & Watson, John & Premachandra, I.M. & Chen, Yao, 2016. "Modeling leakage in two-stage DEA models: An application to US mutual fund families," Omega, Elsevier, vol. 61(C), pages 62-77.
    11. Huang, Shiyang & Jiang, Ying & Qiu, Zhigang & Ye, Zhiqiang, 2019. "An equilibrium model of risk management spillover," Journal of Banking & Finance, Elsevier, vol. 107(C), pages 1-1.
    12. Michael Sockin & Mindy Z Xiaolan, 2023. "Delegated Learning and Contract Commonality in Asset Management," Review of Finance, European Finance Association, vol. 27(6), pages 1931-1975.
    13. Premachandra, I.M. & Zhu, Joe & Watson, John & Galagedera, Don U.A., 2012. "Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3302-3317.
    14. Cuoco, Domenico & Kaniel, Ron, 2009. "Equilibrium Prices in the Presence of Delegated Portfolio Management," CEPR Discussion Papers 7453, C.E.P.R. Discussion Papers.
    15. Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2010. "Decentralized investment management: evidence from the pension fund industry," MPRA Paper 35767, University Library of Munich, Germany.
    16. Huang, Shiyang & Qiu, Zhigang & Shang, Qi & Tang, Ke, 2013. "Asset pricing with heterogeneous beliefs and relative performance," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4107-4119.
    17. Pablo Solórzano-Taborga & Ana Belén Alonso-Conde & Javier Rojo-Suárez, 2020. "Data Envelopment Analysis and Multifactor Asset Pricing Models," IJFS, MDPI, vol. 8(2), pages 1-18, April.
    18. Liu, Xiangbo & Qiu, Zhigang & Xiong, Yan, 2013. "VaR constrained asset pricing with relative performance," Economics Letters, Elsevier, vol. 121(2), pages 174-178.
    19. Raddatz, Claudio & Schmukler, Sergio L., 2011. "Deconstructing herding : evidence from pension fund investment behavior," Policy Research Working Paper Series 5700, The World Bank.
    20. Jean-Daniel Guigou & Patrick De Lamirande & Bruno Lovat, 2011. "Strategic delegation and collusion: Do incentive schemes matter?," LSF Research Working Paper Series 11-02, Luxembourg School of Finance, University of Luxembourg.

  22. Kosowski, Robert & Timmermann, Allan & Wermers, Russ & White, Hal, 2005. "Can mutual fund stars really pick stocks? New evidence from a bootstrap analysis," CFR Working Papers 05-14, University of Cologne, Centre for Financial Research (CFR).

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    1. Wei-Xing Zhou & Guo-Hua Mu & Si-Wei Chen & Didier Sornette, "undated". "Strategies used as Spectroscopy of Financial Markets Reveal New Stylized Facts," Working Papers ETH-RC-11-005, ETH Zurich, Chair of Systems Design.
    2. Mohammad (Vahid) Irani & Hugh Hoikwang Kim, 2023. "The consequences of non‐trading institutional investors," Financial Management, Financial Management Association International, vol. 52(3), pages 433-481, September.
    3. Enareta Kurtbegu & Juliana Caicedo-llano, 2014. "European equity fund managers: luck or skill?!," Economics Bulletin, AccessEcon, vol. 34(4), pages 2340-2350.
    4. Charles Cao & Grant Farnsworth & Hong Zhang, 2021. "The Economics of Hedge Fund Startups: Theory and Empirical Evidence," Journal of Finance, American Finance Association, vol. 76(3), pages 1427-1469, June.
    5. D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.
    6. Jezek, M., 2009. "Passive Investors, Active Traders and Strategic Delegation of Price Discovery," Cambridge Working Papers in Economics 0951, Faculty of Economics, University of Cambridge.
    7. Andrei Semenov, 2009. "Risk factor beta conditional value-at-risk," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(6), pages 549-558.
    8. Keith Cuthbertson & Dirk Nitzsche & Niall O’Sullivan, 2023. "UK mutual funds: performance persistence and portfolio size," Journal of Asset Management, Palgrave Macmillan, vol. 24(4), pages 284-298, July.
    9. Campbell R. Harvey & Yan Liu, 2022. "Luck versus Skill in the Cross Section of Mutual Fund Returns: Reexamining the Evidence," Journal of Finance, American Finance Association, vol. 77(3), pages 1921-1966, June.
    10. Nicolae B. Gârleanu & Lasse H. Pedersen, 2015. "Efficiently Inefficient Markets for Assets and Asset Management," NBER Working Papers 21563, National Bureau of Economic Research, Inc.
    11. Angelidis, Timotheos & Giamouridis, Daniel & Tessaromatis, Nikolaos, 2012. "Revisiting Mutual Fund Performance Evaluation," MPRA Paper 36644, University Library of Munich, Germany.
    12. Dirk Brounen & Piet Eichholtz & David Ling, 2007. "Trading Intensity and Real Estate Performance," The Journal of Real Estate Finance and Economics, Springer, vol. 35(4), pages 449-474, November.
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    17. Solórzano-Taborga, Pablo & Alonso-Conde, Ana Belén & Rojo-Suárez, Javier, 2018. "Efficiency and Persistence of Spanish Absolute Return Funds || Eficiencia y persistencia de los fondos de retorno absolutos españoles," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 25(1), pages 186-214, Junio.
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    20. H. Pierre Hsieh & Imen Tebourbi & Wen‐Min Lu & Nai‐Yu Liu, 2020. "Mutual fund performance: The decision quality and capital magnet efficiencies," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(5), pages 861-872, July.
    21. Favilukis, Jack & Lin, Xiaoji, 2016. "Does wage rigidity make firms riskier? Evidence from long-horizon return predictability," Journal of Monetary Economics, Elsevier, vol. 78(C), pages 80-95.
    22. Francis In & Sangbae Kim & Philip I Ji, 2014. "On timing ability in Australian managed funds," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 93-106, February.
    23. Artamonov, Nikita & Voronina, Anna & Emelyanov, Nikita & Kurbatskii, Aleksei, 2020. "Estimation of interest rates’ impact on mutual funds’ performance in the USA," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 55-75.
    24. Huang, Rong & Asteriou, Dimitrios & Pouliot, William, 2020. "A reappraisal of luck versus skill in the cross-section of mutual fund returns," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 166-187.
    25. Witkowska Dorota, 2012. "Measurement of the Efficiency of Mutual Funds Operating on the Pan-European Market," Folia Oeconomica Stetinensia, Sciendo, vol. 12(2), pages 126-146, December.
    26. Kim, Sangbae & In, Francis & Ji, Philip Inyeob & Park, Raphael Jonghyeon, 2014. "False discoveries in the performance of Australian managed funds," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 244-256.
    27. Gallefoss, Kristoffer & Hansen, Helge Hoff & Haukaas, Eirik Solli & Molnár, Peter, 2015. "What daily data can tell us about mutual funds: Evidence from Norway," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 117-129.
    28. Jung‐Soon Shin & Minki Kim & Dongjun Oh & Tong Suk Kim, 2019. "Do hedge funds time market tail risk? Evidence from option‐implied tail risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(2), pages 205-237, February.
    29. Almeida, Caio & Ardison, Kym & Garcia, René, 2020. "Nonparametric assessment of hedge fund performance," Journal of Econometrics, Elsevier, vol. 214(2), pages 349-378.
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    32. Wang, Xiaoxiao, 2023. "Bank affiliation and mutual funds’ trading strategy distinctiveness," International Review of Financial Analysis, Elsevier, vol. 88(C).
    33. Cao, Charles & Simin, Timothy T. & Wang, Ying, 2013. "Do mutual fund managers time market liquidity?," Journal of Financial Markets, Elsevier, vol. 16(2), pages 279-307.
    34. Fernando Chague & Rodrigo De Losso, Bruno Giovannetti, 2017. "Uncovering Skilled Short-sellers," Working Papers, Department of Economics 2017_01, University of São Paulo (FEA-USP).
    35. Jha, Ranjini & Korkie, Bob & Turtle, Harry J., 2009. "Measuring performance in a dynamic world: Conditional mean-variance fundamentals," Journal of Banking & Finance, Elsevier, vol. 33(10), pages 1851-1859, October.
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    37. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "The Term Structure of Systematic and Idiosyncratic Risk," Hannover Economic Papers (HEP) dp-618, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
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    41. Michael Busack & Wolfgang Drobetz & Jan Tille, 2017. "Can investors benefit from the performance of alternative UCITS funds?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(1), pages 69-111, February.
    42. Dimitrios G. Konstantinides & Georgios C. Zachos, 2019. "Exhibiting Abnormal Returns Under a Risk Averse Strategy," Methodology and Computing in Applied Probability, Springer, vol. 21(2), pages 551-566, June.
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    237. Adams, John C. & Mansi, Sattar A. & Nishikawa, Takeshi, 2012. "Are mutual fund fees excessive?," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2245-2259.
    238. Vidal, Marta & Vidal-García, Javier & Lean, Hooi Hooi & Uddin, Gazi Salah, 2015. "The relation between fees and return predictability in the mutual fund industry," Economic Modelling, Elsevier, vol. 47(C), pages 260-270.
    239. Benoît Dewaele, 2013. "Leverage and Alpha: The Case of Funds of Hedge Funds," Working Papers CEB 13-033, ULB -- Universite Libre de Bruxelles.
    240. M. Kabir Hassan & William J. Hippler III, 2014. "Partial Adjustment Toward Equilibrium Mutual Fund Allocations: Evidence from U.S.-based Equity Mutual Funds," NFI Working Papers 2014-WP-01, Indiana State University, Scott College of Business, Networks Financial Institute.
    241. H. J. Turtle & Kainan Wang, 2017. "The Value In Fundamental Accounting Information," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 40(1), pages 113-140, March.
    242. Kaserer Christoph & Hanauer Matthias X., 2017. "25 Jahre Fama-French-Modell: Erklärungsgehalt, Anomalien und praktische Implikationen," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 18(2), pages 98-116, June.
    243. Monika Mościbrodzka, 2021. "Alternative investment funds – the evaluation of managers’ abilities in the light of the amendments to the Act on Investment Fund," Bank i Kredyt, Narodowy Bank Polski, vol. 52(6), pages 517-544.
    244. Cheng, Tingting & Yan, Cheng, 2017. "Evaluating the size of the bootstrap method for fund performance evaluation," Economics Letters, Elsevier, vol. 156(C), pages 36-41.
    245. Yi, Li & Liu, Zilan & He, Lei & Qin, Zilong & Gan, Shunli, 2018. "Do Chinese mutual funds time the market?," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 1-19.
    246. Aiken, Adam L. & Kang, Minjeong, 2023. "Hedge fund manager timing and selectivity skill over time. A holdings-based estimate," Finance Research Letters, Elsevier, vol. 58(PB).
    247. Keith Pilbeam & Hamish Preston, 2019. "An Empirical Investigation of the Performance of Japanese Mutual Funds: Skill or Luck?," IJFS, MDPI, vol. 7(1), pages 1-16, January.
    248. Nuttall, John, 2007. "Flaw in the fund skill/luck test method of Cuthbertson et al," MPRA Paper 1584, University Library of Munich, Germany.
    249. Günster, N.K. & Kole, H.J.W.G. & Jacobsen, B., 2009. "Riding Bubbles," ERIM Report Series Research in Management ERS-2009-058-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    250. Sandeep Dahiya & David Yermack, 2018. "Investment Returns and Distribution Policies of Non-Profit Endowment Funds," NBER Working Papers 25323, National Bureau of Economic Research, Inc.
    251. Benoît Dewaele & Hugues Pirotte & N. Tuchschmid & E. Wallerstein, 2011. "Assessing the Performance of Funds of Hedge Funds," Working Papers CEB 11-041, ULB -- Universite Libre de Bruxelles.
    252. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Papers 2006.04269, arXiv.org.
    253. Timothy B. Riley, 2021. "Portfolios of actively managed mutual funds," The Financial Review, Eastern Finance Association, vol. 56(2), pages 205-230, May.
    254. Yuan, Jia & Sun, Guang-Zhen & Siu, Ricardo, 2014. "The lure of illusory luck: How much are people willing to pay for random shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 269-280.
    255. Huang, Jing-Zhi & Wang, Ying, 2013. "Should investors invest in hedge fund-like mutual funds? Evidence from the 2007 financial crisis," Journal of Financial Intermediation, Elsevier, vol. 22(3), pages 482-512.
    256. Abramov, Alexander (Абрамов, Александр) & Akshentseva, Kseniya (Акшенцева, Ксения) & Radygin, Alexander (Радыгин, Александр), 2015. "The effectiveness of mutual funds: theoretical approaches and the experience of Russia [Эффективность Паевых Инвестиционных Фондов: Теоретические Подходы И Опыт России]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 4, pages 60-86.
    257. Anarkulova, Aizhan & Cederburg, Scott & O’Doherty, Michael S., 2022. "Stocks for the long run? Evidence from a broad sample of developed markets," Journal of Financial Economics, Elsevier, vol. 143(1), pages 409-433.
    258. Terrill Keasler & Chris McNeil, 2010. "Mad Money stock recommendations: market reaction and performance," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 34(1), pages 1-22, January.
    259. Zaremba Adam & Konieczka Przemysław, 2017. "Size, Value, and Momentum in Polish Equity Returns: Local or International Factors?," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 53(3), pages 26-47, September.
    260. Benoît Dewaele, 2013. "Portfolio Optimization for Hedge Funds through Time-Varying Coefficients," Working Papers CEB 13-032, ULB -- Universite Libre de Bruxelles.
    261. Onur Kemal Tosun & Liang Jin & Richard Taffler & Arman Eshraghi, 2022. "Fund manager skill: selling matters more!," Review of Quantitative Finance and Accounting, Springer, vol. 59(3), pages 969-994, October.
    262. Alda, Mercedes & Andreu, Laura & Sarto, José Luis, 2017. "Learning about individual managers’ performance in UK pension funds: The importance of specialization," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 654-667.
    263. El Ammari, Anis & Vidal, Marta & Vidal-García, Javier, 2023. "European market timing," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    264. Yuan Zhao & Bryan D. Macgregor & Rainer Schulz, 2013. "Can US Real Estate Mutual Funds Beat the Market? New Evidence," ERES eres2013_335, European Real Estate Society (ERES).
    265. Eduardo Sandoval & Paula Urrutia, 2011. "El Efecto De La Crisis Financiera Subprime En Los Mercados Accionarios Desarrollados. Estimaciones Aparentemente No Relacionadas Sur Versus Garch (1,1)," Revista Internacional Administracion & Finanzas, The Institute for Business and Finance Research, vol. 4(1), pages 1-17.
    266. Jonathan Fletcher & Andrew Marshall, 2005. "An Empirical Examination of U.K. International Unit Trust Performance," Journal of Financial Services Research, Springer;Western Finance Association, vol. 27(2), pages 183-206, April.
    267. Stefan Jonsson, 2009. "Refraining from Imitation: Professional Resistance and Limited Diffusion in a Financial Market," Organization Science, INFORMS, vol. 20(1), pages 172-186, February.
    268. Elyasiani, Elyas & Rytchkov, Oleg & Stetsyuk, Ivan, 2022. "Do real estate mutual fund managers create value?," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 396-406.
    269. Y. Chung & Thomas Kim, 2015. "The win–loss ratio as an ability signal of mutual fund managers: a measure that is less influenced by luck," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 29(4), pages 301-335, November.
    270. Ekholm, Anders G., 2012. "Portfolio returns and manager activity: How to decompose tracking error into security selection and market timing," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 349-358.
    271. Jonathan B. Berk & Jules H. van Binsbergen, 2012. "Measuring Managerial Skill in the Mutual Fund Industry," NBER Working Papers 18184, National Bureau of Economic Research, Inc.
    272. Broeders, Dirk W.G.A. & van Oord, Arco & Rijsbergen, David R., 2019. "Does it pay to pay performance fees? Empirical evidence from Dutch pension funds," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 299-312.
    273. Zhi Da & Pengjie Gao & Ravi Jagannathan, 2008. "Informed Trading, Liquidity Provision, and Stock Selection by Mutual Funds," NBER Working Papers 14609, National Bureau of Economic Research, Inc.
    274. Ayadi, Mohamed A. & Kryzanowski, Lawrence, 2011. "Fixed-income fund performance: Role of luck and ability in tail membership," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 379-392, June.
    275. Božović, Miloš, 2022. "Recent evidence on the short-term and long-term performance persistence of emerging-market mutual fund returns," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    276. Vidal-García, Javier, 2013. "The persistence of European mutual fund performance," Research in International Business and Finance, Elsevier, vol. 28(C), pages 45-67.
    277. Yue Xu, 2022. "Reallocation of Mutual Fund Managers and Capital Raising Ability," CREATES Research Papers 2022-11, Department of Economics and Business Economics, Aarhus University.
    278. Sermpinis, Georgios & Hassanniakalager, Arman & Stasinakis, Charalampos & Psaradellis, Ioannis, 2021. "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    279. Cumming, Douglas & Johan, Sofia & Zhang, Yelin, 2019. "What is mutual fund flow?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 222-251.
    280. Barber, Brad M. & Odean, Terrance, 2013. "The Behavior of Individual Investors," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1533-1570, Elsevier.
    281. Stanisław Urbański, 2017. "Short-, medium- and long-run performance persistence of investment funds in Poland," Bank i Kredyt, Narodowy Bank Polski, vol. 48(4), pages 343-374.
    282. Andriy Bodnaruk & Bekhan Chokaev & Andrei Simonov, 2019. "Downside Risk Timing by Mutual Funds," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 9(1), pages 171-196.
    283. Huazhu Zhang & Cheng Yan, 2018. "A skeptical appraisal of the bootstrap approach in fund performance evaluation," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 27(2), pages 49-86, May.
    284. Kosowski, Robert & Naik, Narayan Y. & Teo, Melvyn, 2007. "Do hedge funds deliver alpha? A Bayesian and bootstrap analysis," Journal of Financial Economics, Elsevier, vol. 84(1), pages 229-264, April.
    285. Herrmann, Ulf & Rohleder, Martin & Scholz, Hendrik, 2016. "Does style-shifting activity predict performance? Evidence from equity mutual funds," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 112-130.
    286. Jorge Sainz & Pilar Grau & Luis Miguel Doncel & Javier Otamendi, 2008. "An evaluation on the true statistical relevance of Jensen's alpha trough simulation: An application for Germany," Economics Bulletin, AccessEcon, vol. 7(10), pages 1-9.
    287. Jun Huang & Albert Y. Wang, 2015. "The Predictability of Managerial Heterogeneities in Mutual Funds," Financial Management, Financial Management Association International, vol. 44(4), pages 947-979, October.
    288. Brooks, Chris & Fernandez-Perez, Adrian & Miffre, Joëlle & Nneji, Ogonna, 2016. "Commodity risks and the cross-section of equity returns," The British Accounting Review, Elsevier, vol. 48(2), pages 134-150.
    289. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.
    290. Abdelsalam, Omneya & Duygun, Meryem & Matallín-Sáez, Juan Carlos & Tortosa-Ausina, Emili, 2014. "Do ethics imply persistence? The case of Islamic and socially responsible funds," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 182-194.
    291. Breloer, Bernhard & Scholz, Hendrik & Wilkens, Marco, 2014. "Performance of international and global equity mutual funds: Do country momentum and sector momentum matter?," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 58-77.
    292. Sabbaghi, Omid, 2022. "The impact of news on the volatility of ESG firms," Global Finance Journal, Elsevier, vol. 51(C).
    293. Bangassa, Kenbata & Su, Chen & Joseph, Nathan L., 2012. "Selectivity and timing performance of UK investment trusts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1149-1175.
    294. Jiang, George J. & Zaynutdinova, Gulnara R. & Zhang, Huacheng, 2021. "Stock-selection timing," Journal of Banking & Finance, Elsevier, vol. 125(C).
    295. Yang, Junmin & Cao, Zhiguang & Han, Qiheng & Wang, Qiyu, 2019. "Tactical asset allocation on technical trading rules and data snooping," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    296. George Aragon & Bing Liang & Hyuna Park, 2014. "Onshore and Offshore Hedge Funds: Are They Twins?," Management Science, INFORMS, vol. 60(1), pages 74-91, January.

  23. Massimo Guidolin, University of Virginia & Allan Timmermann, 2004. "Strategic Asset Allocation and Consumption Decisions under Multivariate Regime Switching," Econometric Society 2004 Australasian Meetings 349, Econometric Society.

    Cited by:

    1. Massimo Guidolin & Allan Timmerman, 2006. "Asset allocation under multivariate regime switching," Working Papers 2005-002, Federal Reserve Bank of St. Louis.
    2. Fernando Alexandre & Vasco J. Gabriel & Pedro Bação, 2007. "The Consumption-Wealth Ratio Under Asymmetric Adjustment," NIPE Working Papers 15/2007, NIPE - Universidade do Minho.
    3. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
    4. J. Sa‐Aadu & James Shilling & Ashish Tiwari, 2010. "On the Portfolio Properties of Real Estate in Good Times and Bad Times1," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 38(3), pages 529-565, September.
    5. Meenagh, David & Minford, Patrick & Peel, David, 2007. "Simulating stock returns under switching regimes - A new test of market efficiency," Economics Letters, Elsevier, vol. 94(2), pages 235-239, February.
    6. Bernd Scherer, 2009. "A note on portfolio choice for sovereign wealth funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 23(3), pages 315-327, September.
    7. John Powell & Rubén Roa & Jing Shi & Viliphonh Xayavong, 2007. "A Test for Long-Term Cyclical Clustering of Stock Market Regimes," Australian Journal of Management, Australian School of Business, vol. 32(2), pages 205-221, December.
    8. Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, August.
    9. Marie Brière & Ombretta Signori, 2011. "Inflation hedging portfolios in different regimes," BIS Papers chapters, in: Bank for International Settlements (ed.), Portfolio and risk management for central banks and sovereign wealth funds, volume 58, pages 139-163, Bank for International Settlements.
    10. Marie Brière & Ombretta Signori, 2012. "Inflation-Hedging Portfolios : Economic Regimes Matter," Post-Print hal-01494498, HAL.
    11. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla I. & Masih, A. Mansur M., 2014. "The Role of Islamic Asset Classes in the Diversified Portfolios: Mean Variance Spanning Test," MPRA Paper 56857, University Library of Munich, Germany.
    12. Roger Bowden & Jennifer Zhu, 2010. "Multi-scale variation, path risk and long-term portfolio management," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 783-796.
    13. Mark E. Wohar & David E. Rapach, 2005. "Return Predictability and the Implied Intertemporal Hedging Demands for Stocks and Bonds: International Evidence," Computing in Economics and Finance 2005 329, Society for Computational Economics.
    14. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 015-031, June.

  24. Timmermann, Allan & Catão, Luís, 2004. "Country and Industry Dynamics in Stock Returns," CEPR Discussion Papers 4368, C.E.P.R. Discussion Papers.

    Cited by:

    1. L’Her, Jean-François & Le Moigne, Cécile & Savaria, Patrick, 2007. "Importance relative des effets pays et secteurs dans les marchés développés," L'Actualité Economique, Société Canadienne de Science Economique, vol. 83(2), pages 201-226, juin.
    2. Geert Bekaert & Robert J. Hodrick & Xiaoyan Zhang, 2005. "International Stock Return Comovements," NBER Working Papers 11906, National Bureau of Economic Research, Inc.
    3. Bai, Ye & Green, Christopher J. & Leger, Lawrence, 2012. "Industry and country factors in emerging market returns: Did the Asian crisis make a difference?," Emerging Markets Review, Elsevier, vol. 13(4), pages 559-580.
    4. Carrieri, Francesca & Errunza, Vihang & Sarkissian, Sergei, 2006. "The Dynamics of Geographic versus Sectoral Diversification: Is There a Link to the Real Economy?," Working Papers 06-4, University of Pennsylvania, Wharton School, Weiss Center.
    5. John Ammer & Jon Wongswan, 2007. "Cash Flows and Discount Rates, Industry and Country Effects and Co‐Movement in Stock Returns," The Financial Review, Eastern Finance Association, vol. 42(2), pages 211-226, May.

  25. Pesaran, M.H. & Timmermann, A., 2004. "‘Real Time Econometrics’," Cambridge Working Papers in Economics 0432, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Cécile Denis & Daniel Grenouilleau & Kieran Mc Morrow & Werner Röger, 2006. "Calculating potential growth rates and output gaps - A revised production function approach," European Economy - Economic Papers 2008 - 2015 247, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    2. Hashem Pesaran & Paolo Zaffaroni & Banca d'Italia), 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," Money Macro and Finance (MMF) Research Group Conference 2004 101, Money Macro and Finance Research Group.
    3. Bernd Brandl & Christian Keber & Matthias Schuster, 2006. "An automated econometric decision support system: forecasts for foreign exchange trades," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(4), pages 401-415, December.
    4. Taipalus, Katja, 2012. "Signaling asset price bubbles with time-series methods," Bank of Finland Research Discussion Papers 7/2012, Bank of Finland.
    5. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    6. Richard G. Anderson, 2006. "Replicability, real-time data, and the science of economic research: FRED, ALFRED, and VDC," Review, Federal Reserve Bank of St. Louis, vol. 88(Jan), pages 81-93.
    7. Chee Kian Leong, 2016. "Credit Risk Scoring with Bayesian Network Models," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 423-446, March.
    8. Heij, Christiaan & van Dijk, Dick & Groenen, Patrick J.F., 2011. "Real-time macroeconomic forecasting with leading indicators: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 27(2), pages 466-481, April.
    9. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.
    10. M. Hashem Pesaran, 2010. "Predictability of Asset Returns and the Efficient Market Hypothesis," CESifo Working Paper Series 3116, CESifo.
    11. Timmermann, Allan & Patton, Andrew, 2007. "Learning in Real Time: Theory and Empirical Evidence from the Term Structure of Survey Forecasts," CEPR Discussion Papers 6526, C.E.P.R. Discussion Papers.
    12. Roberto Golinelli & Giuseppe Parigi, 2013. "Tracking world trade and GDP in real time," Temi di discussione (Economic working papers) 920, Bank of Italy, Economic Research and International Relations Area.
    13. Bahram Pesaran & M. Hashem Pesaran, 2010. "Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market Crash," CESifo Working Paper Series 3023, CESifo.
    14. Phillips, Peter C.B., 2005. "Automated Discovery In Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 3-20, February.
    15. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    16. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    17. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo.
    18. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    19. Heij, C. & van Dijk, D.J.C. & Groenen, P.J.F., 2009. "Macroeconomic forecasting with real-time data: an empirical comparison," Econometric Institute Research Papers EI 2009-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
    21. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.
    22. Pesaran, B. & Pesaran, M.H., 2007. "Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," Cambridge Working Papers in Economics 0734, Faculty of Economics, University of Cambridge.

  26. Timmermann, Allan & Guidolin, Massimo, 2004. "Term Structure of Risk Under Alternative Econometric Specifications," CEPR Discussion Papers 4645, C.E.P.R. Discussion Papers.

    Cited by:

    1. Thomas Conlon & John Cotter & Chenglu Jin, 2019. "Co-skewness across Return Horizons," Working Papers 201910, Geary Institute, University College Dublin.
    2. C. James Hueng & Ruey Yau, 2006. "Investor preferences and portfolio selection: is diversification an appropriate strategy?," Quantitative Finance, Taylor & Francis Journals, vol. 6(3), pages 255-271.
    3. Okimoto, Tatsuyoshi, 2014. "Asymmetric increasing trends in dependence in international equity markets," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 219-232.
    4. Massimo Guidolin & Allan Timmerman, 2006. "Asset allocation under multivariate regime switching," Working Papers 2005-002, Federal Reserve Bank of St. Louis.
    5. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    6. Li, Leon, 2017. "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 116-135.
    7. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    8. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    9. Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    11. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
    12. BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Chrétien, Stéphane & Coggins, Frank, 2010. "Performance and conservatism of monthly FHS VaR: An international investigation," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 323-333, December.
    14. Alejandro Bernales & Diether W. Beuermann & Gonzalo Cortazar, 2014. "Thinly traded securities and risk management," Estudios de Economia, University of Chile, Department of Economics, vol. 41(1 Year 20), pages 5-48, June.
    15. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc.
    16. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    17. Kuang-Liang Chang, 2011. "The optimal value-at-risk hedging strategy under bivariate regime switching ARCH framework," Applied Economics, Taylor & Francis Journals, vol. 43(21), pages 2627-2640.
    18. Bauwens Luc & Storti Giuseppe, 2009. "A Component GARCH Model with Time Varying Weights," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-33, May.
    19. Danielsson, Jon & Zigrand, Jean-Pierre, 2006. "On time-scaling of risk and the square-root-of-time rule," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2701-2713, October.
    20. Lorán Chollete & Andréas Heinen & Alfonso Valdesogo, 2009. "Modeling International Financial Returns with a Multivariate Regime-switching Copula," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 437-480, Fall.
    21. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    22. Huang Dashan & Yu Baimin & Lu Zudi & Fabozzi Frank J. & Focardi Sergio & Fukushima Masao, 2010. "Index-Exciting CAViaR: A New Empirical Time-Varying Risk Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-26, March.
    23. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    24. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    25. Henryk Gurgul & Robert Syrek, 2010. "Polish stock market and some foreign markets - dependence analysis by regime-switching copulas," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 8, pages 21-39.
    26. Bakshi, Gurdip & Panayotov, George, 2010. "First-passage probability, jump models, and intra-horizon risk," Journal of Financial Economics, Elsevier, vol. 95(1), pages 20-40, January.
    27. Ono, Sadayuki, 2019. "Term structure dynamics in a monetary economy with learning," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 730-745.
    28. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
    29. Solange Berstein & Rómulo Chumacero, 2008. "VaR Limits for Pension Funds: An Evaluation," Working Papers 26, Superintendencia de Pensiones, revised May 2008.
    30. Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
    31. Xu, Yanyan & Liu, Jing & Ma, Feng & Chu, Jielei, 2024. "Liquidity and realized volatility prediction in Chinese stock market: A time-varying transitional dynamic perspective," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 543-560.
    32. Penaranda, Francisco, 2007. "Portfolio choice beyond the traditional approach," LSE Research Online Documents on Economics 24481, London School of Economics and Political Science, LSE Library.
    33. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    34. Taamouti, Abderrahim, 2009. "Analytical Value-at-Risk and Expected Shortfall under regime-switching," Finance Research Letters, Elsevier, vol. 6(3), pages 138-151, September.
    35. Bec, Frédérique & Gollier, Christian, 2014. "Cyclicality and term structure of Value-at-Risk within a threshold autoregression setup," IDEI Working Papers 835, Institut d'Économie Industrielle (IDEI), Toulouse.
    36. Polanski, Arnold & Stoja, Evarist, 2012. "Efficient evaluation of multidimensional time-varying density forecasts, with applications to risk management," International Journal of Forecasting, Elsevier, vol. 28(2), pages 343-352.
    37. Agata Gemzik-Salwach, 2012. "The Use Of A Value At Risk Measure For The Analysis Of Bank Interest Margins," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 8(4), pages 15-29, February.
    38. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2007. "Investing for the Long-run in European Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 34(1), pages 35-80, January.
    39. Aliyu, Shehu Usman Rano & Aminu, Abubakar Wambai, 2018. "Economic regimes and stock market performance in Nigeria: Evidence from regime switching model," MPRA Paper 91430, University Library of Munich, Germany, revised 03 Oct 2018.
    40. Kole, Erik & van Dijk, Dick, 2023. "Moments, shocks and spillovers in Markov-switching VAR models," Journal of Econometrics, Elsevier, vol. 236(2).
    41. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla I. & Masih, A. Mansur M., 2014. "The Role of Islamic Asset Classes in the Diversified Portfolios: Mean Variance Spanning Test," MPRA Paper 56857, University Library of Munich, Germany.
    42. Lönnbark, Carl, 2017. "Long vs. short term asymmetry in volatility and the term structure of risk," Finance Research Letters, Elsevier, vol. 23(C), pages 202-209.
    43. Jun Tu, 2010. "Is Regime Switching in Stock Returns Important in Portfolio Decisions?," Management Science, INFORMS, vol. 56(7), pages 1198-1215, July.
    44. Mike K. P. So & Chi-Ming Wong, 2012. "Estimation of multiple period expected shortfall and median shortfall for risk management," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 739-754, March.
    45. Cortazar, Gonzalo & Beuermann, Diether & Bernales, Alejandro, 2013. "Risk Management with Thinly Traded Securities: Methodology and Implementation," IDB Publications (Working Papers) 4647, Inter-American Development Bank.
    46. Taamouti, Abderrahim, 2012. "Moments of multivariate regime switching with application to risk-return trade-off," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 292-308.
    47. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    48. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 015-031, June.

  27. Timmermann, Allan & Elliott, Graham, 2004. "Optimal Forecast Combination Under Regime Switching," CEPR Discussion Papers 4649, C.E.P.R. Discussion Papers.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    3. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    4. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
    5. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    6. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    7. Favero, Carlo A. & Milani, Fabio, 2005. "Parameter Instability, Model Uncertainty and the Choice of Monetary Policy," CEPR Discussion Papers 4909, C.E.P.R. Discussion Papers.
    8. Barrow, Devon K. & Kourentzes, Nikolaos, 2016. "Distributions of forecasting errors of forecast combinations: Implications for inventory management," International Journal of Production Economics, Elsevier, vol. 177(C), pages 24-33.
    9. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    10. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.
    11. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    12. Jakub Nowotarski, 2013. "Short-term forecasting of electricity spot prices using model averaging (Krótkoterminowe prognozowanie spotowych cen energii elektrycznej z wykorzystaniem uśredniania modeli)," HSC Research Reports HSC/13/17, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    13. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    14. Guérin, Pierre & Leiva-Leon, Danilo, 2017. "Model averaging in Markov-switching models: Predicting national recessions with regional data," Economics Letters, Elsevier, vol. 157(C), pages 45-49.
    15. Lees, Kirdan & Matheson, Troy & Smith, Christie, 2011. "Open economy forecasting with a DSGE-VAR: Head to head with the RBNZ published forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 512-528.
    16. Georgios Papadopoulos & Dionysios Chionis & Nikolaos P. Rachaniotis, 2018. "Macro-financial linkages during tranquil and crisis periods: evidence from stressed economies," Risk Management, Palgrave Macmillan, vol. 20(2), pages 142-166, May.
    17. Martinez-Martin Jaime & Morris Richard & Onorante Luca & Piersanti Fabio Massimo, 2024. "Merging Structural and Reduced-Form Models for Forecasting," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 399-437, January.
    18. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    19. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    20. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    21. Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
    22. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    23. A.S.M. Arroyo & A. de Juan Fern¨¢ndez, 2014. "Split-then-Combine Method for out-of-sample Combinations of Forecasts," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 3(1), pages 19-37, April.
    24. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Fotios Petropoulos, 2015. "Forecasting with Temporal Hierarchies," Monash Econometrics and Business Statistics Working Papers 16/15, Monash University, Department of Econometrics and Business Statistics.
    25. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
    26. Zhe Huang & Franck Martin, 2017. "Optimal pairs trading strategies in a cointegration framework," Working Papers halshs-01566803, HAL.
    27. Rianne Legerstee & Philip Hans Franses, 2010. "Does Disagreement amongst Forecasters have Predictive Value?," Tinbergen Institute Discussion Papers 10-088/4, Tinbergen Institute.
    28. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    29. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    30. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012. "Is there an Optimal Forecast Combination? A Stochastic Dominance Approach to Forecast Combination Puzzle," Working Paper series 17_12, Rimini Centre for Economic Analysis.
    31. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    32. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
    33. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    34. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    35. Gaglianone, Wagner Piazza & Issler, João Victor, 2019. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 813, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    36. Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
    37. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    38. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    39. Kenwin Maung, 2021. "Estimating high-dimensional Markov-switching VARs," Papers 2107.12552, arXiv.org.
    40. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
    41. Timmermann, Allan & Guidolin, Massimo, 2007. "Forecasts of US Short-term Interest Rates: A Flexible Forecast Combination Approach," CEPR Discussion Papers 6188, C.E.P.R. Discussion Papers.
    42. Steff De Visscher & Markus Eberhardt & Gerdie Everaert, 2017. "Measuring productivity and absorptive capacity evolution," Discussion Papers 2017-11, University of Nottingham, GEP.
    43. Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
    44. Ayadi, Mohamed A. & Lazrak, Skander & Liao, Yusui & Welch, Robert, 2018. "Performance of fixed-income mutual funds with regime-switching models," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 217-231.
    45. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    46. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    47. Chen Zhuo & Yang Yuhong, 2007. "Time Series Models for Forecasting: Testing or Combining?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(1), pages 1-37, March.

  28. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2004. "‘Forecasting Time Series Subject to Multiple Structural Breaks’," Cambridge Working Papers in Economics 0433, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Bauwens, Luc & Rombouts, Jeroen V.K., 2012. "On marginal likelihood computation in change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3415-3429.
    2. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    3. Brandon J. Bates & Mikkel Plagborg-Møller & James H. Stock & Mark W. Watson, "undated". "Consistent factor estimation in dynamic factor models with structural instability," Working Paper 84631, Harvard University OpenScholar.
    4. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    5. Francesco Bianchi, 2015. "The Great Depression and the Great Recession: A View from Financial Markets," NBER Working Papers 21056, National Bureau of Economic Research, Inc.
    6. Dimitris, Korobilis, 2013. "Forecasting with Factor Models: A Bayesian Model Averaging Perspective," MPRA Paper 52724, University Library of Munich, Germany.
    7. Kyongwook Choi & Wei-Choun Yu & Eric Zivot, 2008. "Long Memory versus Structural Breaks in Modeling and Forecasting Realized Volatility," Working Papers UWEC-2008-20-FC, University of Washington, Department of Economics.
    8. Jan J. J. Groen & Richard Paap & Francesco Ravazzolo, 2009. "Real-time inflation forecasting in a changing world," Staff Reports 388, Federal Reserve Bank of New York.
    9. Nonejad, Nima, 2014. "Particle Gibbs with Ancestor Sampling Methods for Unobserved Component Time Series Models with Heavy Tails, Serial Dependence and Structural Breaks," MPRA Paper 55664, University Library of Munich, Germany.
    10. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
    11. BELMONTE, Miguel A.G. & KOOP, Gary & KOROBILIS, Dimitris, 2011. "Hierarchical shrinkage in time-varying parameter models," LIDAM Discussion Papers CORE 2011036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    13. Ulrich K. Müller & James H. Stock, 2011. "Forecasts in a Slightly Misspecified Finite Order VAR Model," Working Papers 2011-4, Princeton University. Economics Department..
    14. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions," NBER Working Papers 28570, National Bureau of Economic Research, Inc.
    15. Luintel, Kul B. & Khan, Mosahid & Leon-Gonzalez, Roberto & Li, Guangjie, 2016. "Financial development, structure and growth: New data, method and results," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 95-112.
    16. Jia Liu & John M. Maheu & Yong Song, 2024. "Identification and forecasting of bull and bear markets using multivariate returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 723-745, August.
    17. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
    18. Robert Barro & Tao Jin, 2021. "Rare Events and Long-Run Risks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 39, pages 1-25, January.
    19. Dionne, Georges & Maalaoui Chun, Olfa, 2013. "Default and liquidity regimes in the bond market during the 2002-2012 period," Working Papers 13-4, HEC Montreal, Canada Research Chair in Risk Management.
    20. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    21. Geweke, John & Jiang, Yu, 2011. "Inference and prediction in a multiple-structural-break model," Journal of Econometrics, Elsevier, vol. 163(2), pages 172-185, August.
    22. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    23. Lee, Yoonsuk & Brorsen, B. Wade, 2012. "Impacts of Permanent and Transitory Shocks on Optimal Length of Moving Average to Predict Wheat Basis," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125001, Agricultural and Applied Economics Association.
    24. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    25. Smith, Simon C., 2017. "Equity premium estimates from economic fundamentals under structural breaks," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 49-61.
    26. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    27. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    28. Gary Koop & Simon M. Potter, 2009. "Prior Elicitation In Multiple Change-Point Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 751-772, August.
    29. Shawn C. McKay & Alok Chaturvedi & Douglas E. Adams, 2011. "A process for anticipating and shaping adversarial behavior," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(3), pages 255-280, April.
    30. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    31. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020. "Modeling Turning Points In Global Equity Market," DEM Working Papers Series 195, University of Pavia, Department of Economics and Management.
    32. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
    33. John M. Maheu & Qiao Yang, 2015. "An Infinite Hidden Markov Model for Short-term Interest Rates," Working Paper series 15-05, Rimini Centre for Economic Analysis.
    34. Fokin, Nikita & Polbin, Andrey, 2019. "A Bivariate Forecasting Model For Russian GDP Under Structural Changes In Monetary Policy and Long-Term Growth," MPRA Paper 95306, University Library of Munich, Germany, revised Apr 2019.
    35. David Ardia & Arnaud Dufays & Carlos Ordás Criado, 2024. "Linking Frequentist and Bayesian Change-Point Methods," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(4), pages 1155-1168, October.
    36. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    37. Song, Yong & Shi, Shuping, 2012. "Identifying speculative bubbles with an in finite hidden Markov model," MPRA Paper 36455, University Library of Munich, Germany.
    38. Dendramis, Yiannis & Kapetanios, George & Tzavalis, Elias, 2014. "Level shifts in stock returns driven by large shocks," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 41-51.
    39. Caterina Forti Grazzini & Massimo Guidolin, 2013. "Forecasting yield spreads under crisis-induced multiple breakpoints," Applied Economics Letters, Taylor & Francis Journals, vol. 20(18), pages 1656-1664, December.
    40. Adriatik Hoxha, 2016. "The Wage-Price Setting Behavior: Comparing The Evidence from EU28 and EMU," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 19(60), pages 61-102, June.
    41. Brock,W.A. & Durlauf,S.N. & West,K.D., 2004. "Model uncertainty and policy evaluation : some theory and empirics," Working papers 19, Wisconsin Madison - Social Systems.
    42. Kirsten Thompson & Renee Van Eyden & Rangan Gupta, 2015. "Identifying an index of financial conditions for South Africa," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(2), pages 256-274, June.
    43. Chao Du & Chu-Lan Michael Kao & S. C. Kou, 2016. "Stepwise Signal Extraction via Marginal Likelihood," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 314-330, March.
    44. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    45. Jiang, Yu & Song, Zhe & Kusiak, Andrew, 2013. "Very short-term wind speed forecasting with Bayesian structural break model," Renewable Energy, Elsevier, vol. 50(C), pages 637-647.
    46. Eo, Yunjong & Kim, Chang-Jin, 2012. "Markov-Switching Models with Evolving Regime-Specific Parameters: Are Post-War Booms or Recessions All Alike?," Working Papers 2012-04, University of Sydney, School of Economics.
    47. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    48. Eran Raviv & Kees E. Bouwman & Dick van Dijk, 2013. "Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices," Tinbergen Institute Discussion Papers 13-068/III, Tinbergen Institute.
    49. Chatzitzisi, Evanthia & Fountas, Stilianos & Panagiotidis, Theodore, 2021. "Another look at calendar anomalies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 823-840.
    50. Joshua G. Maples & B. Wade Brorsen, 2022. "Handling the discontinuity in futures prices when time series modeling of commodity cash and futures prices," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 70(2), pages 139-152, June.
    51. He, Zhongfang & Maheu, John M., 2010. "Real time detection of structural breaks in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2628-2640, November.
    52. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2009. "On the evolution of the monetary policy transmission mechanism," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 997-1017, April.
    53. Kim, Jaeho, 2015. "Bayesian Inference in a Non-linear/Non-Gaussian Switching State Space Model: Regime-dependent Leverage Effect in the U.S. Stock Market," MPRA Paper 67153, University Library of Munich, Germany.
    54. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    55. Pesaran, M.H. & Assenmacher-Wesche, K., 2007. "Assessing forecast uncertainties in a VECX* model for Switzerland: an exercise in forecast combination across models and observation windows," Cambridge Working Papers in Economics 0746, Faculty of Economics, University of Cambridge.
    56. Lieven Baele, 2010. "The Determinants of Stock and Bond Return Comovements," The Review of Financial Studies, Society for Financial Studies, vol. 23(6), pages 2374-2428, June.
    57. Jana Eklund & George Kapetanios & Simon Price, 2011. "Forecasting in the presence of recent structural change," CAMA Working Papers 2011-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    58. John M Maheu & Thomas H McCurdy, 2007. "How useful are historical data for forecasting the long-run equity return distribution?," Working Papers tecipa-293, University of Toronto, Department of Economics.
    59. Georges Dionne & Olfa Maalaoui Chun, 2013. "Presidential Address: Default and liquidity regimes in the bond market during the 2002–2012 period," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(4), pages 1160-1195, November.
    60. Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
    61. Maheu, John & Song, Yong, 2012. "A new structural break model with application to Canadian inflation forecasting," MPRA Paper 36870, University Library of Munich, Germany.
    62. Rickard Sandberg, 2016. "Testing for unit roots in nonlinear heterogeneous panels with smoothly changing trends: an application to Scandinavian unemployment rates," Empirical Economics, Springer, vol. 51(3), pages 1053-1083, November.
    63. Mwasi Paza Mboya & Philipp Sibbertsen, 2023. "Optimal forecasts in the presence of discrete structural breaks under long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1889-1908, November.
    64. Bianchi, Francesco, 2016. "Methods for measuring expectations and uncertainty in Markov-switching models," Journal of Econometrics, Elsevier, vol. 190(1), pages 79-99.
    65. Castle, Jennifer L. & Fawcett, Nicholas W.P. & Hendry, David F., 2010. "Forecasting with equilibrium-correction models during structural breaks," Journal of Econometrics, Elsevier, vol. 158(1), pages 25-36, September.
    66. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    3. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    4. Stan Hurn & Jing Tian & Lina Xu, 2021. "Assessing the Informational Content of Official Australian Bureau of Meteorology Forecasts of Wind Speed," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 525-547, December.
    5. Metodij Hadzi-Vaskov & Mr. Luca A Ricci & Alejandro M. Werner & Rene Zamarripa, 2021. "Authorities’ Fiscal Forecasts in Latin America: Are They Optimistic?," IMF Working Papers 2021/154, International Monetary Fund.
    6. Pratiti Chatterjee & Fabio Milani, 2020. "Perceived Uncertainty Shocks, Excess Optimism-Pessimism, and Learning in the Business Cycle," Working Papers 202101, University of California-Irvine, Department of Economics.
    7. Benjamin Born & Zeno Enders & Manuel Menkhoff & Gernot J. Müller & Knut Niemann, 2023. "Firm Expectations and News: Micro v Macro," ifo Working Paper Series 400, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    8. Reitz, Stefan & Rülke, Jan & Stadtmann, Georg, 2012. "Nonlinear Expectations in Speculative Markets," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62045, Verein für Socialpolitik / German Economic Association.
    9. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
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    12. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    13. Atsushi Inoue & Lutz Kilian & Fatma Burcu Kiraz, 2009. "Do Actions Speak Louder Than Words? Household Expectations of Inflation Based on Micro Consumption Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1331-1363, October.
    14. Reitz, Stefan & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Nonlinear expectations in speculative markets: Evidence from the ECB survey of professional forecasters," Discussion Papers 311, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    15. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Central banks’ inflation forecasts under asymmetric loss: Evidence from four Latin-American countries," Economics Letters, Elsevier, vol. 129(C), pages 66-70.
    16. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
    17. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
    18. Lutz Kilian & Simone Manganelli, 2008. "The Central Banker as a Risk Manager: Estimating the Federal Reserve's Preferences under Greenspan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(6), pages 1103-1129, September.
    19. Christian Pierdzioch & Jan C Rülke & Georg Stadtmann, 2012. "Forecasting the Dollar/British Pound Exchange Rate: Asymmetric Loss and Forecast Rationality," Economics Bulletin, AccessEcon, vol. 32(3), pages 213-213.
    20. Andrew C. Chang & Trace J. Levinson, 2023. "Raiders of the lost high‐frequency forecasts: New data and evidence on the efficiency of the Fed's forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 88-104, January.
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    Cited by:

    1. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
    2. Romulo A. Chumacero, 2004. "Forecasting Chilean Industrial Production with Automated Procedures," Econometric Society 2004 Latin American Meetings 177, Econometric Society.
    3. Capistrán Carlos & López Moctezuma Gabriel, 2008. "Experts' Macroeconomics Expectations: An Evaluation of Mexican Short-Run Forecasts," Working Papers 2008-11, Banco de México.
    4. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    5. Romulo A. Chumacero, 2004. "Forecasting Chilean Industrial Production and Sales with Automated Procedures," Computing in Economics and Finance 2004 112, Society for Computational Economics.
    6. Timmermann Allan & Capistrán Carlos, 2006. "Disagreement and Biases in Inflation Expectations," Working Papers 2006-07, Banco de México.
    7. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.
    8. Anatolyev, Stanislav, 2009. "Dynamic modeling under linear-exponential loss," Economic Modelling, Elsevier, vol. 26(1), pages 82-89, January.
    9. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    10. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    11. Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
    12. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    13. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    14. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    15. Patton, Andrew J. & Timmermann, Allan, 2005. "Testable implications of forecast optimality," LSE Research Online Documents on Economics 6834, London School of Economics and Political Science, LSE Library.

  31. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.

    Cited by:

    1. Martin Skitmore & Franco K. T. Cheung, 2007. "Explorations in specifying construction price forecast loss functions," Construction Management and Economics, Taylor & Francis Journals, vol. 25(5), pages 449-465.
    2. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    3. Stan Hurn & Ralf Becker, 2006. "Testing for nonlinearity in mean in the presence of heteroskedasticity," Stan Hurn Discussion Papers 2006-02, School of Economics and Finance, Queensland University of Technology.
    4. Siliverstovs, Boriss & Engsted, Tom & Haldrup, Niels, 2002. "Long-Run Forecasting in Multicointegrated Systems," Finance Working Papers 02-14, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    5. Basu, Sudipta & Markov, Stanimir, 2004. "Loss function assumptions in rational expectations tests on financial analysts' earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 38(1), pages 171-203, December.
    6. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    7. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    8. Allan Timmermann & Andrew J. Patton, 2004. "Properties of Optimal Forecasts," Econometric Society 2004 North American Winter Meetings 234, Econometric Society.
    9. Adrian Pagan & Hashem Pesaran, 2007. "Econometric Analysis of Structural Systems with Permanent and Transitory Shocks. Working paper #7," NCER Working Paper Series 7, National Centre for Econometric Research.
    10. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    11. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.

  32. Timmermann, Allan & Lunde, Asger, 2003. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," CEPR Discussion Papers 4104, C.E.P.R. Discussion Papers.

    Cited by:

    1. Don Harding & Adrian Pagan, 2009. "An Econometric Analysis of Some Models for Constructed Binary Time Series," NCER Working Paper Series 39, National Centre for Econometric Research, revised 02 Jul 2009.
    2. Scott M. R. Mahadeo & Reinhold Heinlein & Gabriella Deborah Legrenzi, 2018. "Energy Contagion Analysis: A New Perspective with Application to a Small Petroleum Economy," CESifo Working Paper Series 7279, CESifo.
    3. Jo~ao Nicolau & Paulo M. M. Rodrigues, 2024. "A simple but powerful tail index regression," Papers 2409.13531, arXiv.org.
    4. Stelios D. Bekiros, 2013. "Irrational fads, short‐term memory emulation, and asset predictability," Review of Financial Economics, John Wiley & Sons, vol. 22(4), pages 213-219, November.
    5. Marco Marozzi, 2014. "The multisample Cucconi test," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 209-227, June.
    6. Rose Cunningham & Ilan Kolet, 2007. "Housing Market Cycles and Duration Dependence in the United States and Canada," Staff Working Papers 07-2, Bank of Canada.
    7. Ashraf, Dawood & Mohammad, Nazeeruddin, 2014. "Matching perception with the reality—Performance of Islamic equity investments," Pacific-Basin Finance Journal, Elsevier, vol. 28(C), pages 175-189.
    8. Jia Liu & John M. Maheu & Yong Song, 2024. "Identification and forecasting of bull and bear markets using multivariate returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 723-745, August.
    9. S. Boubaker & Liu, Z. & Zhan, Y., 2021. "Risk management for crude oil futures: an optimal stopping-timing approach," Post-Print hal-03323674, HAL.
    10. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
    11. Laopodis, Nikiforos T., 2016. "Industry returns, market returns and economic fundamentals: Evidence for the United States," Economic Modelling, Elsevier, vol. 53(C), pages 89-106.
    12. Vitor Castro & Boris Fisera, 2022. "Determinants of the Duration of Economic Recoveries: The Role of ´Too Much Finance´," Working Papers IES 2022/33, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Dec 2022.
    13. John M Maheu & Thomas H McCurdy & Yong Song, 2009. "Extracting bull and bear markets from stock returns," Working Papers tecipa-369, University of Toronto, Department of Economics.
    14. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    15. Maheu, John M & McCurdy, Thomas H & Song, Yong, 2020. "Bull and Bear Markets During the COVID-19 Pandemic," MPRA Paper 104504, University Library of Munich, Germany.
    16. Beata Bieszk-Stolorz & Krzysztof Dmytrów, 2021. "Evaluation of Changes on World Stock Exchanges in Connection with the SARS-CoV-2 Pandemic. Survival Analysis Methods," Risks, MDPI, vol. 9(7), pages 1-19, June.
    17. Reinhold Heinlein & Gabriele M. Lepori, 2022. "Do financial markets respond to macroeconomic surprises? Evidence from the UK," Empirical Economics, Springer, vol. 62(5), pages 2329-2371, May.
    18. Ashraf, Dawood & Rizwan, Muhammad Suhail & Ahmad, Ghufran, 2022. "Islamic equity investments and the COVID-19 pandemic," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    19. Chen, Shiu-Sheng, 2010. "Do higher oil prices push the stock market into bear territory?," Energy Economics, Elsevier, vol. 32(2), pages 490-495, March.
    20. James D. Hamilton & Oscar Jorda, "undated". "A model for the federal funds rate target," Department of Economics 99-07, California Davis - Department of Economics.
    21. Mendes, Fernando Henrique de Paula e Silva & Caldeira, João Frois & Moura, Guilherme Valle, 2018. "Evidence of Bull and Bear Markets in the Bovespa index: An application of Markovian regime-switching Models with Duration Dependence," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(1), May.
    22. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
    23. Shiu-Sheng Chen, 2005. "Does Monetary Policy Have Asymmetric Effects on Stock Returns?," Macroeconomics 0502001, University Library of Munich, Germany, revised 01 Feb 2005.
    24. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    25. Don Harding & Adrian Pagan, 2006. "The Econometric Analysis of Constructed Binary Time Series," Department of Economics - Working Papers Series 963, The University of Melbourne.
    26. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
    27. Claessens, Stijn & Kose, M. Ayhan & Terrones, Marco, 2011. "Financial Cycles: What? How? When?," CEPR Discussion Papers 8379, C.E.P.R. Discussion Papers.
    28. Jarno Tikkanen & Janne Äijö, 2018. "Does the F-score improve the performance of different value investment strategies in Europe?," Journal of Asset Management, Palgrave Macmillan, vol. 19(7), pages 495-506, December.
    29. Linh Nguyen & Vilém Novák & Soheyla Mirshahi, 2020. "Trend‐cycle Estimation Using Fuzzy Transform and Its Application for Identifying Bull and Bear Phases in Markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 111-124, July.
    30. Kirby, Chris, 2023. "A closer look at the regime-switching evidence of bull and bear markets," Finance Research Letters, Elsevier, vol. 52(C).
    31. Mahadeo, Scott M.R. & Heinlein, Reinhold & Legrenzi, Gabriella D., 2022. "Contagion testing in frontier markets under alternative stressful S&P 500 market scenarios," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    32. Kurov, Alexander & Olson, Eric & Zaynutdinova, Gulnara R., 2022. "When does the fed care about stock prices?," Journal of Banking & Finance, Elsevier, vol. 142(C).
    33. Woodward, George & Brooks, Robert, 2009. "Do realized betas exhibit up/down market tendencies?," International Review of Economics & Finance, Elsevier, vol. 18(3), pages 511-519, June.
    34. Mohammad, Nazeeruddin & Ashraf, Dawood, 2015. "The Market Timing Ability and Return Performance of Islamic Equities: an Empirical Study," Working Papers 1436-6, The Islamic Research and Teaching Institute (IRTI).
    35. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Papers 2306.14004, arXiv.org, revised May 2024.
    36. Polko-Zając Dominika, 2019. "On Permutation Location–Scale Tests," Statistics in Transition New Series, Statistics Poland, vol. 20(4), pages 153-166, December.
    37. Luca Agnello & Vítor Castro & Ricardo M. Sousa, 2018. "The Legacy and the Tyranny of Time: Exit and Re‐Entry of Sovereigns to International Capital Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(8), pages 1969-1994, December.
    38. Shu-Yi Liao & Sheng-Tung Chen & Mao-Lung Huang, 2016. "Will the oil price change damage the stock market in a bull market? A re-examination of their conditional relationships," Empirical Economics, Springer, vol. 50(3), pages 1135-1169, May.
    39. Dumitriu, Ramona & Stefanescu, Razvan & Nistor, Costel, 2010. "Systematic risks for the financial and for the non-financial Romanian companies," MPRA Paper 41636, University Library of Munich, Germany, revised 28 Feb 2010.
    40. Villena, Marcelo J. & Araneda, Axel A., 2024. "On sectoral market efficiency," Finance Research Letters, Elsevier, vol. 61(C).
    41. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "Amplitude-Duration-Persistence Trade-off Relationship for Long Term Bear Stock Markets," MPRA Paper 54177, University Library of Munich, Germany.
    42. Yaya, OlaOluwa S. & Gil-Alana, Luis A., 2014. "The persistence and asymmetric volatility in the Nigerian stock bull and bear markets," Economic Modelling, Elsevier, vol. 38(C), pages 463-469.
    43. Candelon, Bertrand & Piplack, Jan & Straetmans, Stefan, 2008. "On measuring synchronization of bulls and bears: The case of East Asia," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1022-1035, June.
    44. Chong, Terence Tai-Leung & Cao, Bingqing & Wong, Wing Keung, 2017. "A Principal Component Approach to Measuring Investor Sentiment in Hong Kong," MPRA Paper 77147, University Library of Munich, Germany.
    45. Vitor Castro, 2011. "The Portuguese Stock Market Cycle: Chronology and Duration Dependence," GEMF Working Papers 2011-17, GEMF, Faculty of Economics, University of Coimbra.
    46. Liao, Li-Chuan & Chou, Ray Yeutien & Chiu, Banghan, 2013. "Anchoring effect on foreign institutional investors’ momentum trading behavior: Evidence from the Taiwan stock market," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 72-91.
    47. Nicolau, João, 2016. "Structural change test in duration of bull and bear markets," Economics Letters, Elsevier, vol. 146(C), pages 64-67.
    48. Ichkitidze, Yuri, 2018. "Temporary price trends in the stock market with rational agents," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 103-117.
    49. Zhang, Chuanhai & Zhang, Zhengjun & Xu, Mengyu & Peng, Zhe, 2023. "Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns," Economic Modelling, Elsevier, vol. 119(C).
    50. John M Maheu & Thomas H McCurdy & Yong Song, 2010. "Components of bull and bear markets: bull corrections and bear rallies," Working Papers tecipa-402, University of Toronto, Department of Economics.
    51. de Bruijn, L.P. & Franses, Ph.H.B.F., 2015. "Stochastic levels and duration dependence in US unemployment," Econometric Institute Research Papers EI2015-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    52. Valeriy Zakamulin & Javier Giner, 2020. "Trend following with momentum versus moving averages: a tale of differences," Quantitative Finance, Taylor & Francis Journals, vol. 20(6), pages 985-1007, June.
    53. Chan, Stephen & Chu, Jeffrey & Zhang, Yuanyuan & Nadarajah, Saralees, 2022. "An extreme value analysis of the tail relationships between returns and volumes for high frequency cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
    54. Julian, Inchauspe & Helen, Cabalu, 2013. "What Drives the Shanghai Stock Market? An Examination of its Linkage to Macroeconomic Fundamentals," MPRA Paper 93049, University Library of Munich, Germany.
    55. Maryam Akbari Nasiri, 2020. "How Long Do Housing Cycles Last? A Duration Analysis For Emerging Economies," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 23(2), pages 179-200, July.
    56. Bertrand Candelon & Jameel Ahmed & Stefan Straetmans, 2014. "Predicting and Capitalizing on Stock Market Bears in the U.S," Working Papers 2014-409, Department of Research, Ipag Business School.
    57. Ghysels, Eric & Jagannathan, Ravi & Chabot, Benjamin, 2014. "Momentum Trading, Return Chasing, and Predictable Crashes," CEPR Discussion Papers 10234, C.E.P.R. Discussion Papers.
    58. Alexakis, Christos & Dasilas, Apostolos & Grose, Chris, 2013. "Asymmetric dynamic relations between stock prices and mutual fund units in Japan. An application of hidden cointegration technique," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 1-8.
    59. Fan, Jianqing & Gong, Wenyan & Zhu, Ziwei, 2019. "Generalized high-dimensional trace regression via nuclear norm regularization," Journal of Econometrics, Elsevier, vol. 212(1), pages 177-202.
    60. Agnello, Luca & Castro, Vítor & Sousa, Ricardo M., 2021. "On the duration of sovereign ratings cycle phases," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 512-526.
    61. Asif, Raheel & Frömmel, Michael & Mende, Alexander, 2022. "The crisis alpha of managed futures: Myth or reality?," International Review of Financial Analysis, Elsevier, vol. 80(C).
    62. Mai Shibata, 2014. "The Influence of Japan’s Unsecured Overnight Call Rate on Bull and Bear Markets and Market Turns," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 21(4), pages 331-349, November.
    63. Xiao-Lin Li & Yi-Na Li & Lu Bai, 2019. "Stock Market Cycle and Business Cycle in China: Evidence from a Bootstrap Rolling Window Approach," Review of Economics & Finance, Better Advances Press, Canada, vol. 17, pages 35-50, August.
    64. Fernando López & Mariano Matilla-García & Jesús Mur & Manuel Ruiz Marín, 2021. "Statistical Tests of Symbolic Dynamics," Mathematics, MDPI, vol. 9(8), pages 1-21, April.
    65. Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, August.
    66. Yong Song & Tomasz Wo'zniak, 2020. "Markov Switching," Papers 2002.03598, arXiv.org.
    67. Yehong Liu & Guosheng Yin, 2018. "Average Holding Price," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-20, March.
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    107. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    108. Pedro Pires Ribeiro & José Dias Curto, 2018. "How do zero-coupon inflation swaps predict inflation rates in the euro area? Evidence of efficiency and accuracy on 1-year contracts," Empirical Economics, Springer, vol. 54(4), pages 1451-1475, June.
    109. Abounoori, Abbas Ali & Naderi, Esmaeil & Gandali Alikhani, Nadiya & Amiri, Ashkan, 2013. "Financial Time Series Forecasting by Developing a Hybrid Intelligent System," MPRA Paper 45615, University Library of Munich, Germany.
    110. Kamal, Mona, 2014. "Studying the Validity of the Efficient Market Hypothesis (EMH) in the Egyptian Exchange (EGX) after the 25th of January Revolution," MPRA Paper 54708, University Library of Munich, Germany.
    111. Magdalena Mikolajek-Gocejna & Tomasz Urbas, 2023. "Rational Investors or Rational Expectations in Efficient Market Hypothesis?," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 13(2), pages 167-188.
    112. Babai, M. Zied & Ali, Mohammad M. & Nikolopoulos, Konstantinos, 2012. "Impact of temporal aggregation on stock control performance of intermittent demand estimators: Empirical analysis," Omega, Elsevier, vol. 40(6), pages 713-721.
    113. Parul Bhatia & Priya Gupta, 2020. "Sub-prime Crisis or COVID-19: A Comparative Analysis of Volatility in Indian Banking Sectoral Indices," FIIB Business Review, , vol. 9(4), pages 286-299, December.
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    115. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    116. Rambaccussing, Dooruj, 2015. "Revisiting Shiller's excess volatility hypothesis," SIRE Discussion Papers 2015-33, Scottish Institute for Research in Economics (SIRE).
    117. David Ubilava, 2014. "El Niño Southern Oscillation and the fishmeal–soya bean meal price ratio: regime-dependent dynamics revisited," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(4), pages 583-604.
    118. Konstandinos Chourmouziadis & Dimitra K. Chourmouziadou & Prodromos D. Chatzoglou, 2021. "Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1183-1216, April.
    119. Darko B. Vuković & Sonja D. Radenković & Ivana Simeunović & Vyacheslav Zinovev & Milan Radovanović, 2024. "Predictive Patterns and Market Efficiency: A Deep Learning Approach to Financial Time Series Forecasting," Mathematics, MDPI, vol. 12(19), pages 1-26, September.
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    121. Ogulcan E. Orsel & Sasha S. Yamada, 2022. "Comparative Study of Machine Learning Models for Stock Price Prediction," Papers 2202.03156, arXiv.org.
    122. Mishra, Sasmita & Padhy, Sudarsan & Mishra, Satya Narayan & Misra, Satya Narayan, 2021. "A novel LASSO – TLBO – SVR hybrid model for an efficient portfolio construction," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    123. Strozzi, Fernanda & Comenges, José-Manuel Zaldívar, 2006. "Towards a non-linear trading strategy for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 28(3), pages 601-615.
    124. Aatola, Piia, 2013. "Putting a Price on Carbon – Econometric Essays on the European Union Emissions Trading Scheme and its Impacts," Research Reports P62, VATT Institute for Economic Research.
    125. Barras, Laurent, 2007. "International conditional asset allocation under specification uncertainty," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 443-464, September.
    126. Jun Lu & Danny Ding, 2022. "A Hybrid Approach on Conditional GAN for Portfolio Analysis," Papers 2208.07159, arXiv.org.
    127. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.
    128. Daniel Traian Pele & Miruna Mazurencu-Marinescu & Peter Nijkamp, 2013. "Herding Behaviour, Bubbles and Log Periodic Power Laws in Illiquid Stock Markets. A Case Study on the Bucharest Stock Exchange," Tinbergen Institute Discussion Papers 13-109/VIII, Tinbergen Institute.
    129. Xie Haibin & Zhou Mo & Hu Yi & Yu Mei, 2014. "Forecasting the Crude Oil Price with Extreme Values," Journal of Systems Science and Information, De Gruyter, vol. 2(3), pages 193-205, June.
    130. Becker, Janis & Leschinski, Christian, 2018. "Directional Predictability of Daily Stock Returns," Hannover Economic Papers (HEP) dp-624, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    131. Erol Eğrioğlu & Robert Fildes, 2022. "A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1355-1383, April.
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    133. Abounoori, Esmaiel & Shahrazi, Mahdi & Rasekhi, Saeed, 2012. "An investigation of Forex market efficiency based on detrended fluctuation analysis: A case study for Iran," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3170-3179.
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    135. Yao, Juan & Alles, Lakshman, 2006. "Industry return predictability, timing and profitability," Journal of Multinational Financial Management, Elsevier, vol. 16(2), pages 122-141, April.
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  36. Paye, Bradley S. & Timmermann, Allan, 2002. "How Stable are Financial Prediction Models? Evidence from US and International Stock Market Data," University of California at San Diego, Economics Working Paper Series qt74v515fr, Department of Economics, UC San Diego.

    Cited by:

    1. Danilov, D.L. & Magnus, J.R., 2002. "Forecast Accuracy after Pretesting with an Application to the Stock Market," Other publications TiSEM cb9b9b63-40a9-4035-924e-d, Tilburg University, School of Economics and Management.
    2. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.
    3. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    4. Todd E. Clark & Michael W. McCracken, 2002. "Forecast-based model selection in the presence of structural breaks," Research Working Paper RWP 02-05, Federal Reserve Bank of Kansas City.
    5. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.

  37. Blake, David & Timmermann, Allan, 2002. "International Asset Allocation with Time-Varying Investment Opportunities," CEPR Discussion Papers 3464, C.E.P.R. Discussion Papers.

    Cited by:

    1. Rui Albuquerque & Gregory Bauer & Martin Schneider, 2004. "Characterizing Asymmetric Information in International Equity Markets," International Finance 0405005, University Library of Munich, Germany.
    2. Schneider, Martin & Albuquerque, Rui & ,, 2006. "Global Private Information in International Equity Markets," CEPR Discussion Papers 5819, C.E.P.R. Discussion Papers.
    3. Blake, David & Cairns, Andrew & Dowd, Kevin, 2008. "Turning pension plans into pension planes: What investment strategy designers of defined contribution pension plans can learn from commercial aircraft designers," MPRA Paper 33749, University Library of Munich, Germany.
    4. Rossi, Alberto G. & Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2018. "Network centrality and delegated investment performance," Journal of Financial Economics, Elsevier, vol. 128(1), pages 183-206.
    5. Iwatsubo, Kentaro & Watkins, Clinton, 2021. "The changing role of foreign investors in Tokyo stock price formation," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    6. Nadima El-Hassan & Paul Kofman, 2003. "Tracking Error and Active Portfolio Management," Australian Journal of Management, Australian School of Business, vol. 28(2), pages 183-207, September.
    7. Rossi, Alberto G. & Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2015. "Network centrality and pension fund performance," CFR Working Papers 15-16, University of Cologne, Centre for Financial Research (CFR).
    8. Kirt Butler & Katsushi Okada, 2007. "Bivariate and higher-order terms in models of international equity returns," Applied Financial Economics, Taylor & Francis Journals, vol. 17(9), pages 725-737.
    9. Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2010. "Decentralized investment management: evidence from the pension fund industry," MPRA Paper 35767, University Library of Munich, Germany.
    10. Korteweg, Arthur & Sorensen, Morten, 2017. "Skill and luck in private equity performance," Journal of Financial Economics, Elsevier, vol. 124(3), pages 535-562.
    11. Blake, David & Sarno, Lucio & Zinna, Gabriele, 2017. "The market for lemmings: The herding behavior of pension funds," Journal of Financial Markets, Elsevier, vol. 36(C), pages 17-39.
    12. Fernández, Pablo & Aguirreamalloa, Javier & Corres, Luis, 2013. "Rentabilidad de los fondos de pensiones en España. 2001-2011," IESE Research Papers D/1060, IESE Business School.
    13. Kamel Laaradh, 2007. "« Investir Sur Le Marche Inernational Des Actions A-T-Il Plus D'Effet Sur La Persistance De La Performance Des Fonds ? Illustration Britannique »," Post-Print halshs-00544930, HAL.
    14. Moosa, Imad A. & Al-Deehani, Talla M., 2009. "The Myth of International Diversification," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 62(3), pages 383-406.
    15. Dreassi, Alberto & Miani, Stefano & Paltrinieri, Andrea, 2017. "Sovereign pension and social security reserve funds: A portfolio analysis," Global Finance Journal, Elsevier, vol. 34(C), pages 43-53.
    16. Ion Lapteacru, 2019. "Do bank activities and funding strategies of foreign and state‐owned banks have a differential effect on risk‐taking in Central and Eastern Europe?," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 27(2), pages 541-576, February.
    17. Gabriele Zinna, 2014. "Price pressures in the UK index-linked market: an empirical investigation," Temi di discussione (Economic working papers) 968, Bank of Italy, Economic Research and International Relations Area.
    18. Manuel Ammann & Andreas Zingg, 2008. "Investment Performance of Swiss Pension Funds and Investment Foundations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(II), pages 153-195, June.

  38. Allan Timmermann & M. Hashem Pesaran, 2002. "Market Timing and Return Prediction under Model Instability," FMG Discussion Papers dp412, Financial Markets Group.

    Cited by:

    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Elliott, Graham & Muller, Ulrich K., 2007. "Confidence sets for the date of a single break in linear time series regressions," Journal of Econometrics, Elsevier, vol. 141(2), pages 1196-1218, December.
    4. Massimo Guidolin & Alexei G. Orlov, 2022. "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 1-61, September.
    5. Fabian Baetje & Lukas Menkhoff, 2016. "Equity Premium Prediction: Are Economic and Technical Indicators Unstable?," Discussion Papers of DIW Berlin 1552, DIW Berlin, German Institute for Economic Research.
    6. Goodness C. Aye & Rangan Gupta & Mampho P. Modise, 2012. "Structural Breaks and Predictive Regressions Models of South African Equity Premium," Working Papers 201209, University of Pretoria, Department of Economics.
    7. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
    8. Robert A. Hill & Paulo M. M. Rodrigues, 2022. "Forgetting approaches to improve forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1356-1371, November.
    9. Emanuela Ciapanna & Marco Taboga, 2019. "Bayesian Analysis of Coefficient Instability in Dynamic Regressions," Econometrics, MDPI, vol. 7(3), pages 1-32, June.
    10. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    11. Tian, Jing & Anderson, Heather M., 2014. "Forecast combinations under structural break uncertainty," International Journal of Forecasting, Elsevier, vol. 30(1), pages 161-175.
    12. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
    13. Geweke, John & Jiang, Yu, 2011. "Inference and prediction in a multiple-structural-break model," Journal of Econometrics, Elsevier, vol. 163(2), pages 172-185, August.
    14. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    15. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    16. Yao, Juan & Gao, Jiti & Alles, Lakshman, 2005. "Dynamic investigation into the predictability of Australian industrial stock returns: Using financial and economic information," Pacific-Basin Finance Journal, Elsevier, vol. 13(2), pages 225-245, March.
    17. Jing Tian & Heather M. Anderson, 2011. "Forecasting Under Strucural Break Uncertainty," Monash Econometrics and Business Statistics Working Papers 8/11, Monash University, Department of Econometrics and Business Statistics.
    18. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Forecasting benchmarks of long-term stock returns via machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 221-240, February.
    19. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    20. Pesaran, M. Hashem & Timmermann, Allan, 2004. "How costly is it to ignore breaks when forecasting the direction of a time series?," International Journal of Forecasting, Elsevier, vol. 20(3), pages 411-425.
    21. Kumar, Nikeel Nishkar & Patel, Arvind, 2023. "Nonlinear effect of air travel tourism demand on economic growth in Fiji," Journal of Air Transport Management, Elsevier, vol. 109(C).
    22. Henriques, Irene & Sadorsky, Perry, 2023. "Forecasting rare earth stock prices with machine learning," Resources Policy, Elsevier, vol. 86(PA).
    23. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
    24. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.
    25. Caterina Forti Grazzini & Massimo Guidolin, 2013. "Forecasting yield spreads under crisis-induced multiple breakpoints," Applied Economics Letters, Taylor & Francis Journals, vol. 20(18), pages 1656-1664, December.
    26. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    27. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    28. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    29. Hui Hong & Fergal O'Brien & James Ryan, 2014. "Inflation And The Subsequent Timing Of The Chinese Stock Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 10(2), pages 13-35.
    30. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    31. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    32. Hanxiong Zhang & Robert Hudson & Hugh Metcalf & Viktor Manahov, 2017. "Investigation of institutional changes in the UK housing market using structural break tests and time-varying parameter models," Empirical Economics, Springer, vol. 53(2), pages 617-640, September.
    33. Pesaran, M. Hashem & Pettenuzzo, Davide & Timmermann, Allan, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," IZA Discussion Papers 1196, Institute of Labor Economics (IZA).
    34. Alptekin, Aynur & Broadstock, David C. & Chen, Xiaoqi & Wang, Dong, 2019. "Time-varying parameter energy demand functions: Benchmarking state-space methods against rolling-regressions," Energy Economics, Elsevier, vol. 82(C), pages 26-41.
    35. Yannick Hoga, 2024. "Persistence-Robust Break Detection in Predictive Quantile and CoVaR Regressions," Papers 2410.05861, arXiv.org.
    36. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    37. Chatzitzisi, Evanthia & Fountas, Stilianos & Panagiotidis, Theodore, 2021. "Another look at calendar anomalies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 823-840.
    38. Michael W. McCracken & Todd E. Clark, 2003. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Computing in Economics and Finance 2003 183, Society for Computational Economics.
    39. Kuang-Liang Chang, 2012. "Stock return predictability and stationarity of dividend yield," Economics Bulletin, AccessEcon, vol. 32(1), pages 715-729.
    40. Shamsi Zamenjani, Azam, 2021. "Do financial variables help predict the conditional distribution of the market portfolio?," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 327-345.
    41. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    42. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
    43. Evzen Kocenda, 1999. "Detecting Structural Breaks: Exchange Rates in Transition Economies," CERGE-EI Working Papers wp149, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    44. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.
    45. John M Maheu & Thomas H McCurdy, 2007. "How useful are historical data for forecasting the long-run equity return distribution?," Working Papers tecipa-293, University of Toronto, Department of Economics.
    46. Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
    47. Tae-Hwy Lee & Eric Hillebrand & Marcelo Medeiros, 2014. "Bagging Constrained Equity Premium Predictors," Working Papers 201421, University of California at Riverside, Department of Economics, revised Feb 2013.
    48. Russell Davidson & Niels S. Grønborg, 2018. "Time-varying parameters: New test tailored to applications in finance and macroeconomics," CREATES Research Papers 2018-22, Department of Economics and Business Economics, Aarhus University.
    49. Donadelli, Michael & Persha, Lauren, 2014. "Understanding emerging market equity risk premia: Industries, governance and macroeconomic policy uncertainty," Research in International Business and Finance, Elsevier, vol. 30(C), pages 284-309.
    50. Mark E. Wohar & David E. Rapach, 2007. "Forecasting the recent behavior of US business fixed investment spending: an analysis of competing models This is a significantly revised version of our previous paper, 'Forecasting US Business Fixed ," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 33-51.
    51. Lozinskaia, Agata & Saltykova, Anastasiia, 2019. "Fundamental Factors Affecting the MOEX Russia Index: Retrospective Analysis," MPRA Paper 97308, University Library of Munich, Germany, revised 23 Sep 2019.
    52. Davide De Gaetano, 2016. "Forecast Combinations For Realized Volatility In Presence Of Structural Breaks," Departmental Working Papers of Economics - University 'Roma Tre' 0208, Department of Economics - University Roma Tre.
    53. Barnhart, Scott W. & Giannetti, Antoine, 2009. "Negative earnings, positive earnings and stock return predictability: An empirical examination of market timing," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 70-86, January.
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    56. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    57. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.
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    74. McKenzie, Michael & Satchell, Stephen & Wongwachara, Warapong, 2012. "Nonlinearity and smoothing in venture capital performance data," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 782-795.
    75. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    76. Naser, Hanan & Alaali, Fatema, 2015. "Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach," MPRA Paper 65295, University Library of Munich, Germany, revised 25 Jun 2015.
    77. Campisi, Giovanni & Muzzioli, Silvia & De Baets, Bernard, 2024. "A comparison of machine learning methods for predicting the direction of the US stock market on the basis of volatility indices," International Journal of Forecasting, Elsevier, vol. 40(3), pages 869-880.
    78. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    79. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
    80. Pesaran, M.H. & Timmermann, A., 2004. "‘Real Time Econometrics’," Cambridge Working Papers in Economics 0432, Faculty of Economics, University of Cambridge.
    81. Hanan Naser & Fatema Alaali, 2018. "Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach," Empirical Economics, Springer, vol. 55(4), pages 1757-1777, December.
    82. Mai Dao & Davide Furceri & Prakash Loungani, 2017. "Regional Labor Market Adjustment in the United States: Trend and Cycle," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 243-257, May.
    83. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    84. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    85. Allan Timmermann & M. Hashem Pesaran, 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," CESifo Working Paper Series 990, CESifo.
    86. Patrick McGlenchy & Paul Kofman, 2004. "Structurally Sound Dynamic Index Futures Hedging," Econometric Society 2004 Australasian Meetings 80, Econometric Society.
    87. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    88. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    89. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    90. Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.
    91. Sjoerd van den Hauwe & Richard Paap & Dick J.C. van Dijk, 2011. "An Alternative Bayesian Approach to Structural Breaks in Time Series Models," Tinbergen Institute Discussion Papers 11-023/4, Tinbergen Institute.
    92. Roch, Oriol, 2013. "Histogram-based prediction of directional price relatives," Finance Research Letters, Elsevier, vol. 10(3), pages 110-115.
    93. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    94. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    95. Seema Narayan & Russell Smyth, 2015. "The Financial Econometrics of Price Discovery and Predictability," Monash Economics Working Papers 06-15, Monash University, Department of Economics.
    96. Sharma, Susan Sunila & Narayan, Paresh Kumar, 2022. "Technology shocks and stock returns: A long-term perspective," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 67-83.
    97. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
    98. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    99. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Optimal Forecast under Structural Breaks," Working Papers 202208, University of California at Riverside, Department of Economics.
    100. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    101. Adam Canopius, 2006. "Practitioners' Corner," Journal of Financial Econometrics, Oxford University Press, vol. 4(2), pages 346-351.
    102. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    103. Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
    104. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
    105. Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018. "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 132-142.
    106. El-Shazly, Alaa, 2016. "Structural breaks and monetary dynamics: A time series analysis," Economic Modelling, Elsevier, vol. 53(C), pages 133-143.
    107. Syed Abul, Basher & Perry, Sadorsky, 2022. "Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?," MPRA Paper 113293, University Library of Munich, Germany.
    108. Shahnaz Parsaeian, 2023. "Structural Breaks in Seemingly Unrelated Regression Models," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202308, University of Kansas, Department of Economics.
    109. Campbell, Alrick, 2018. "Price and income elasticities of electricity demand: Evidence from Jamaica," Energy Economics, Elsevier, vol. 69(C), pages 19-32.
    110. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    111. Francesco Battaglia & Mattheos Protopapas, 2012. "Multi–regime models for nonlinear nonstationary time series," Computational Statistics, Springer, vol. 27(2), pages 319-341, June.
    112. Yuqing Feng & Yaojie Zhang & Yudong Wang, 2024. "Out‐of‐sample volatility prediction: Rolling window, expanding window, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 567-582, April.
    113. Johnson, Lorne D. & Sakoulis, Georgios, 2008. "Maximizing equity market sector predictability in a Bayesian time-varying parameter model," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3083-3106, February.
    114. Anne Vila Wetherilt & Simon Wells, 2004. "Long-horizon equity return predictability: some new evidence for the United Kingdom," Bank of England working papers 244, Bank of England.
    115. Henriques, Irene & Sadorsky, Perry, 2023. "Forecasting NFT coin prices using machine learning: Insights into feature significance and portfolio strategies," Global Finance Journal, Elsevier, vol. 58(C).
    116. Ravazzolo, F. & van Dijk, D.J.C. & Paap, R. & Franses, Ph.H.B.F., 2006. "Bayesian Model Averaging in the Presence of Structural Breaks," Econometric Institute Research Papers EI 2006-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    117. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
    118. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    119. Ke Yang & Langnan Chen, 2014. "Realized Volatility Forecast: Structural Breaks, Long Memory, Asymmetry, and Day-of-the-Week Effect," International Review of Finance, International Review of Finance Ltd., vol. 14(3), pages 345-392, September.
    120. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    121. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    122. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    123. Hartmann, Daniel & Kempa, Bernd & Pierdzioch, Christian, 2006. "Economic and Financial Crises and the Predictability of U.S. Stock Returns," MPRA Paper 561, University Library of Munich, Germany.
    124. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    125. Mai Dao & Davide Furceri & Mr. Prakash Loungani, 2014. "Regional Labor Market Adjustments in the United States and Europe," IMF Working Papers 2014/026, International Monetary Fund.
    126. Jan Verbesselt & Achim Zeileis & Martin Herold, 2011. "Near Real-Time Disturbance Detection in Terrestrial Ecosystems Using Satellite Image Time Series: Drought Detection in Somalia," Working Papers 2011-18, Faculty of Economics and Statistics, Universität Innsbruck.
    127. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2019. "Machine Learning for Forecasting Excess Stock Returns The Five-Year-View," Graz Economics Papers 2019-06, University of Graz, Department of Economics.
    128. Ronald Ravinesh Kumar & Peter Josef Stauvermann & Nikeel Kumar & Syed Jawad Hussain Shahzad, 2019. "Exploring the effect of ICT and tourism on economic growth: a study of Israel," Economic Change and Restructuring, Springer, vol. 52(3), pages 221-254, August.
    129. Jiawen Xu & Pierre Perron, 2023. "Forecasting in the presence of in-sample and out-of-sample breaks," Empirical Economics, Springer, vol. 64(6), pages 3001-3035, June.
    130. Peter Klein & Daryl Purdy & Isaac Schweigert & Alexander Vedrashko, 2015. "The Canadian Hedge Fund Industry: Performance and Market Timing," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 283-320, September.
    131. Jing Tian & Qing Zhou, 2018. "Improving equity premium forecasts by incorporating structural break uncertainty," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 619-656, November.
    132. Muhammad Owais Qarni & Saiqb Gulzar, 2021. "Portfolio diversification benefits of alternative currency investment in Bitcoin and foreign exchange markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-37, December.
    133. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
    134. Giannetti, A., 2007. "The short term predictive ability of earnings-price ratios: The recent evidence (1994-2003)," The Quarterly Review of Economics and Finance, Elsevier, vol. 47(1), pages 26-39, March.
    135. Prakash Loungani & Davide Furceri & Mai Dao, 2015. "Regional labor market adjustment in the United States," 2015 Meeting Papers 733, Society for Economic Dynamics.
    136. Hong, Hui & Jiang, Lijun & Zhang, Cheng & Yue, Zhonggang, 2024. "Do conventional and new energy stock markets herd differently? Evidence from China," Research in International Business and Finance, Elsevier, vol. 67(PA).
    137. Yao, Juan & Alles, Lakshman, 2006. "Industry return predictability, timing and profitability," Journal of Multinational Financial Management, Elsevier, vol. 16(2), pages 122-141, April.
    138. Thobeka Ncanywa & Marius Mamokgaetji Masoga, 2018. "Can public debt stimulate public investment and economic growth in South Africa?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 6(1), pages 1516483-151, January.

  39. Bruce N. Lehmann & Allan Timmermann, 2002. "(UBS Pensions Series 3) Performance Clustering and Incentives in the UK Pension Fund Industry," FMG Discussion Papers dp425, Financial Markets Group.

    Cited by:

    1. Bijapur, Mohan & Croci, Manuela & Zaidi, Rida, 2012. "Do asset regulations impede portfolio diversification? evidence from European life insurance funds," LSE Research Online Documents on Economics 56618, London School of Economics and Political Science, LSE Library.
    2. Blake, David & Cairns, Andrew & Dowd, Kevin, 2008. "Turning pension plans into pension planes: What investment strategy designers of defined contribution pension plans can learn from commercial aircraft designers," MPRA Paper 33749, University Library of Munich, Germany.
    3. Martin Gold, 2010. "Fiduciary Finance," Books, Edward Elgar Publishing, number 13813.
    4. Lawrence Kryzanowski & Abdul Rahman, 2008. "Portfolio performance ambiguity and benchmark inefficiency revisited," Journal of Asset Management, Palgrave Macmillan, vol. 9(5), pages 321-332, December.
    5. Svitlana Voronkova & Martin T. Bohl, 2005. "Institutional Traders’ Behavior in an Emerging Stock Market: Empirical Evidence on Polish Pension Fund Investors," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(7‐8), pages 1537-1560, September.
    6. Agarwal, Vikas & Gómez, Juan-Pedro & Priestley, Richard, 2012. "Management compensation and market timing under portfolio constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1600-1625.
    7. Raddatz, Claudio & Schmukler, Sergio L., 2011. "Deconstructing herding : evidence from pension fund investment behavior," Policy Research Working Paper Series 5700, The World Bank.
    8. Paul Cox & Stephen Brammer & Andrew Millington, 2007. "Pension Fund Manager Tournaments and Attitudes Towards Corporate Characteristics," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(7‐8), pages 1307-1326, September.
    9. Christoph Gort & Mei Wang, 2010. "Overconfidence and Active Management," Chapters, in: Brian Bruce (ed.), Handbook of Behavioral Finance, chapter 12, Edward Elgar Publishing.
    10. John Watson & James Delaney & Michael Dempsey & J. Wickramanayake, 2016. "Australian superannuation (pension) fund product ratings and performance: A guide for fund managers," Australian Journal of Management, Australian School of Business, vol. 41(2), pages 189-211, May.
    11. Jem Tugwell, 2011. "Skill or luck? The role of strategies and scenario analysis as a competitive differentiator for fund management firms," Journal of Asset Management, Palgrave Macmillan, vol. 12(4), pages 281-291, September.

  40. Elliott, Graham & Timmermann, Allan, 2002. "Optimal Forecast Combination Under General Loss Functions and Forecast Error Distributions," University of California at San Diego, Economics Working Paper Series qt15r9t2q2, Department of Economics, UC San Diego.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    3. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
    4. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    5. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    6. Jiang Wu & Jianzhong Zhou & Lu Chen & Lei Ye, 2015. "Coupling Forecast Methods of Multiple Rainfall–Runoff Models for Improving the Precision of Hydrological Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5091-5108, November.
    7. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    8. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    9. Barrow, Devon K. & Kourentzes, Nikolaos, 2016. "Distributions of forecasting errors of forecast combinations: Implications for inventory management," International Journal of Production Economics, Elsevier, vol. 177(C), pages 24-33.
    10. Giacomini, Raffaella & Komunjer, Ivana, 2002. "Evaluation and Combination of Conditional Quantile Forecasts," University of California at San Diego, Economics Working Paper Series qt4n99t4wz, Department of Economics, UC San Diego.
    11. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
    12. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
    13. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    14. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Working Papers No 06/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    15. Heather M. Anderson & Farshid Vahid, 2005. "Nonlinear Correlograms and Partial Autocorrelograms," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 957-982, December.
    16. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    17. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.
    18. Jakub Nowotarski, 2013. "Short-term forecasting of electricity spot prices using model averaging (Krótkoterminowe prognozowanie spotowych cen energii elektrycznej z wykorzystaniem uśredniania modeli)," HSC Research Reports HSC/13/17, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    19. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    20. Coshall, John T. & Charlesworth, Richard, 2011. "A management orientated approach to combination forecasting of tourism demand," Tourism Management, Elsevier, vol. 32(4), pages 759-769.
    21. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    22. Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
    23. Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
    24. Barbara Będowska-Sójka, 2018. "Is intraday data useful for forecasting VaR? The evidence from EUR/PLN exchange rate," Risk Management, Palgrave Macmillan, vol. 20(4), pages 326-346, November.
    25. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
    26. Sainan Jin & Valentina Corradi & Norman Swanson, 2015. "Robust Forecast Comparison," Departmental Working Papers 201502, Rutgers University, Department of Economics.
    27. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    28. Viviano, Davide & Bradic, Jelena, 2023. "Synthetic Learner: Model-free inference on treatments over time," Journal of Econometrics, Elsevier, vol. 234(2), pages 691-713.
    29. Ekaterina V. Astafyeva & Maria Yu. Turuntseva, 2023. "Analysis of Opportunities to Improve the Quality of Natural Resource Price by Combining Forecasts Resulting from Methods Based on Regression Estimates of Weights [Анализ Возможностей Улучшения Каче," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 24-33, December.
    30. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.
    31. Heijmans, Roweno J.R.K. & Gerlagh, Reyer, 2019. "Regulating Global Externalities," Other publications TiSEM 9a0a6f7a-f8d0-4495-8aed-4, Tilburg University, School of Economics and Management.
    32. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
    33. Xu, Yexiao, 2004. "Small levels of predictability and large economic gains," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 247-275, March.
    34. Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
    35. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    36. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    37. Groen, Jan J.J. & Kapetanios, George, 2016. "Revisiting useful approaches to data-rich macroeconomic forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 221-239.
    38. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    39. Cheng, Gang & Yang, Yuhong, 2015. "Forecast combination with outlier protection," International Journal of Forecasting, Elsevier, vol. 31(2), pages 223-237.
    40. Sancetta, A., 2007. "Online Forecast Combination for Dependent Heterogeneous Data," Cambridge Working Papers in Economics 0718, Faculty of Economics, University of Cambridge.
    41. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Fotios Petropoulos, 2015. "Forecasting with Temporal Hierarchies," Monash Econometrics and Business Statistics Working Papers 16/15, Monash University, Department of Econometrics and Business Statistics.
    42. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
    43. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
    44. Sancetta, A. & Satchell, S.E., 2004. "Cost of Capital and Regulator’s Preferences: Investigation into a new method of estimating regulatory bias," Cambridge Working Papers in Economics 0441, Faculty of Economics, University of Cambridge.
    45. Martin Baumgärtner & Jens Klose, 2019. "Forecasting exchange rates with commodity prices—a global country analysis," The World Economy, Wiley Blackwell, vol. 42(9), pages 2546-2565, September.
    46. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
    47. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    48. Alessandro Riboni & Francisco Ruge-Murcia, 2020. "The Power of the Federal Reserve Chair," Cahiers de recherche 20-2020, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    49. Chanont Banternghansa & Michael W. McCracken, 2010. "Real-time forecast averaging with ALFRED," Working Papers 2010-033, Federal Reserve Bank of St. Louis.
    50. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    51. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    52. Gaglianone, Wagner Piazza & Issler, João Victor, 2019. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 813, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    53. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223, April.
    54. Xiaohong Chen & Yanqin Fan, 2004. "Estimation and Model Selection of Semiparametric Copula-Based Multivariate Dynamic Models under Copula Misspecification," Vanderbilt University Department of Economics Working Papers 0419, Vanderbilt University Department of Economics, revised Sep 2004.
    55. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Discussion Paper 2012-043, Tilburg University, Center for Economic Research.
    56. Heijmans, Roweno J.R.K. & Gerlagh, Reyer, 2019. "Regulating Global Externalities," Discussion Paper 2019-001, Tilburg University, Center for Economic Research.
    57. Qing Zhou & Robert Faff, 2017. "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 113-139, February.
    58. Taylor, James W., 2020. "Forecast combinations for value at risk and expected shortfall," International Journal of Forecasting, Elsevier, vol. 36(2), pages 428-441.
    59. Gomez, Miguel I. & Gonzalez, Eliana & Melo, Luis F. & Torres, Jose L., 2006. "Forecasting Food Price Inflation, Challenges for Central Banks in Developing Countries using an Inflation Targeting Framework: the Case of Colombia," 2006 Annual meeting, July 23-26, Long Beach, CA 21181, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    60. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    61. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    62. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
    63. Luke Hartigan, 2016. "Alternative HAC Covariance Matrix Estimators with Improved Finite Sample Properties," Discussion Papers 2016-06, School of Economics, The University of New South Wales.
    64. Elena Andreou & Constantinos Kourouyiannis & Andros Kourtellos, 2012. "Volatility Forecast Combinations using Asymmetric Loss Functions," University of Cyprus Working Papers in Economics 07-2012, University of Cyprus Department of Economics.
    65. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    66. Chotikapanich, D. & Griffiths, W.E. & Rao, D.S.P., 2001. "Averaging Income Distributions," Department of Economics - Working Papers Series 798, The University of Melbourne.
    67. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    68. Björn Fastrich & Peter Winker, 2014. "Combining Forecasts with Missing Data: Making Use of Portfolio Theory," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 127-152, August.
    69. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
    70. Egorov, Alexei V. & Hong, Yongmiao & Li, Haitao, 2006. "Validating forecasts of the joint probability density of bond yields: Can affine models beat random walk?," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 255-284.
    71. Gary Cornwall & Jeff Chen & Beau Sauley, 2021. "Standing on the Shoulders of Machine Learning: Can We Improve Hypothesis Testing?," Papers 2103.01368, arXiv.org.
    72. Matei Demetrescu, 2007. "Optimal forecast intervals under asymmetric loss," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 227-238.
    73. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.
    74. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    75. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
    76. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    77. Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
    78. Kevin Aretz & David Peel, 2007. "Some implications of a quartic loss function," Economics Bulletin, AccessEcon, vol. 7(13), pages 1-7.
    79. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.
    80. Sancetta, Alessio, 2007. "Online forecast combinations of distributions: Worst case bounds," Journal of Econometrics, Elsevier, vol. 141(2), pages 621-651, December.
    81. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Other publications TiSEM 7715e942-b446-4985-8216-f, Tilburg University, School of Economics and Management.

  41. Timmermann, Allan & Guidolin, Massimo, 2001. "Option Prices under Bayesian Learning: Implied Volatility Dynamics and Predictive Densities," CEPR Discussion Papers 3005, C.E.P.R. Discussion Papers.

    Cited by:

    1. Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019. "Implied volatility surface predictability: the case of commodity markets," Papers 1909.11009, arXiv.org.
    2. Chalamandaris, Georgios & Tsekrekos, Andrianos E., 2010. "Predictable dynamics in implied volatility surfaces from OTC currency options," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1175-1188, June.
    3. Laurent E. Calvet & Adlai J. Fisher, 2005. "Multifrequency News and Stock Returns," NBER Working Papers 11441, National Bureau of Economic Research, Inc.
    4. Hautsch, Nikolaus & Hess, Dieter E. & Veredas, David, 2010. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," CFS Working Paper Series 2010/01, Center for Financial Studies (CFS).
    5. A. A. Brown & L. C. G. Rogers, 2009. "Heterogeneous Beliefs with Finite-Lived Agents," Papers 0907.4953, arXiv.org.
    6. M. Duembgen & L. C. G. Rogers, 2014. "Estimate nothing," Papers 1401.5666, arXiv.org.
    7. Calvet, Laurent-Emmanuel & Czellar , Veronika, 2011. "state-observation sampling and the econometrics of learning models," HEC Research Papers Series 947, HEC Paris.
    8. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    9. Sílvia Gonçalves & Massimo Guidolin, 2006. "Predictable Dynamics in the S&P 500 Index Options Implied Volatility Surface," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1591-1636, May.
    10. Massimo Guidolin, 2006. "High equity premia and crash fears - Rational foundations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 693-708, August.
    11. Nikolaus Hautsch & Dieter Hess & Christoph Müller, 2008. "Price Adjustment to News with Uncertain Precision," FRU Working Papers 2008/01, University of Copenhagen. Department of Economics. Finance Research Unit.
    12. Carsten Krabbe Nielsen, 2004. "Rational overconfidence and excess volatility in General Equilibrium," Econometric Society 2004 Australasian Meetings 279, Econometric Society.
    13. Shu Ling Chiang & Ming Shann Tsai, 2019. "Valuation of an option using non-parametric methods," Review of Derivatives Research, Springer, vol. 22(3), pages 419-447, October.
    14. Bernales, Alejandro & Chen, Louisa & Valenzuela, Marcela, 2017. "Learning and forecasts about option returns through the volatility risk premium," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 312-330.
    15. Guidolin, Massimo & Timmermann, Allan, 2007. "Properties of equilibrium asset prices under alternative learning schemes," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 161-217, January.
    16. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay, 2014. "Crude oil moments and PNG stock returns," Energy Economics, Elsevier, vol. 44(C), pages 222-235.
    17. Sudarshan Kumar & Sobhesh Kumar Agarwalla & Jayanth R. Varma & Vineet Virmani, 2023. "Harvesting the volatility smile in a large emerging market: A Dynamic Nelson–Siegel approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1615-1644, November.
    18. Massimo Guidolin & Kai Wang, 2022. "The Empirical Performance of Option Implied Volatility Surface-Driven Optimal Portfolios," BAFFI CAREFIN Working Papers 22190, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    19. Calvet, Laurent E. & Czellar, Veronika, 2015. "Through the looking glass: Indirect inference via simple equilibria," Journal of Econometrics, Elsevier, vol. 185(2), pages 343-358.
    20. Massimo Guidolin, 2005. "Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle," Working Papers 2005-005, Federal Reserve Bank of St. Louis.
    21. Bedendo, Mascia & Hodges, Stewart D., 2009. "The dynamics of the volatility skew: A Kalman filter approach," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1156-1165, June.
    22. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    23. Élise PAYZAN LE NESTOUR, 2010. "Bayesian Learning in UnstableSettings: Experimental Evidence Based on the Bandit Problem," Swiss Finance Institute Research Paper Series 10-28, Swiss Finance Institute.
    24. Angus A Brown & L C G Rogers, 2010. "Diverse Beliefs," Papers 1001.1450, arXiv.org.
    25. Le, Van & Zurbruegg, Ralf, 2014. "Forecasting option smile dynamics," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 32-45.
    26. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    27. Sadayuki Ono, 2007. "Option Pricing under Stochastic Volatility and Trading Volume," Discussion Papers 07/05, Department of Economics, University of York.
    28. Chalamandaris, Georgios & Rompolis, Leonidas S., 2012. "Exploring the role of the realized return distribution in the formation of the implied volatility smile," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1028-1044.
    29. Lei Shi, 2010. "Portfolio Analysis and Equilibrium Asset Pricing with Heterogeneous Beliefs," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2010, January-A.
    30. Paruolo Paolo, 2004. "Automated Inference and the Future of Econometrics: A comment," Economics and Quantitative Methods qf04025, Department of Economics, University of Insubria.
    31. Rainer Baule & Bart Frijns & Milena E. Tieves, 2018. "Volatility discovery and volatility quoting on markets for options and warrants," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(7), pages 758-774, July.
    32. Tao Li, 2013. "Investors' Heterogeneity and Implied Volatility Smiles," Management Science, INFORMS, vol. 59(10), pages 2392-2412, October.
    33. Bernales, Alejandro & Verousis, Thanos & Voukelatos, Nikolaos, 2020. "Do investors follow the herd in option markets?," Journal of Banking & Finance, Elsevier, vol. 119(C).
    34. Quaye, Enoch & Tunaru, Radu, 2022. "The stock implied volatility and the implied dividend volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    35. Xue-Zhong He & Lei Shi, 2016. "A Binomial Model of Asset and Option Pricing with Heterogeneous Beliefs," Published Paper Series 2016-4, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    36. Shaliastovich, Ivan, 2015. "Learning, confidence, and option prices," Journal of Econometrics, Elsevier, vol. 187(1), pages 18-42.
    37. Liu, Yi-Fang & Zhang, Wei & Xu, Hai-Chuan, 2014. "Collective behavior and options volatility smile: An agent-based explanation," Economic Modelling, Elsevier, vol. 39(C), pages 232-239.
    38. Guidolin, Massimo, 2003. "International asset prices and portfolio choices under Bayesian learning," Research in Economics, Elsevier, vol. 57(4), pages 383-437, December.
    39. Konstantinidi, Eirini & Skiadopoulos, George & Tzagkaraki, Emilia, 2008. "Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2401-2411, November.
    40. Markopoulou, Chryssa & Skintzi, Vasiliki & Refenes, Apostolos, 2016. "On the predictability of model-free implied correlation," International Journal of Forecasting, Elsevier, vol. 32(2), pages 527-547.
    41. Nielsen, Carsten Krabbe, 2008. "On rationally confident beliefs and rational overconfidence," Mathematical Social Sciences, Elsevier, vol. 55(3), pages 381-404, May.
    42. Wang, Jinzhong & Chen, Shijiang & Tao, Qizhi & Zhang, Ting, 2017. "Modelling the implied volatility surface based on Shanghai 50ETF options," Economic Modelling, Elsevier, vol. 64(C), pages 295-301.
    43. Anais Maillet, 2015. "Food price volatility and farmers' production decisions under imperfect information," FOODSECURE Technical papers 8, LEI Wageningen UR.
    44. Shengli Chen & Zili Zhang, 2019. "Forecasting Implied Volatility Smile Surface via Deep Learning and Attention Mechanism," Papers 1912.11059, arXiv.org.

  42. Timmermann, Allan, 2001. "Structural Breaks, Incomplete Information and Stock Prices," University of California at San Diego, Economics Working Paper Series qt1sn269d7, Department of Economics, UC San Diego.

    Cited by:

    1. Martin Lettau & Stijn Van Nieuwerburgh, 2006. "Reconciling the Return Predictability Evidence," 2006 Meeting Papers 29, Society for Economic Dynamics.
    2. Elena Andreou, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 290-318.
    3. Massacci, Daniele & Kapetanios, George, 2024. "Forecasting in factor augmented regressions under structural change," International Journal of Forecasting, Elsevier, vol. 40(1), pages 62-76.
    4. Londoño Yarce, Juan Miguel & Regúlez Castillo, Marta & Vázquez Pérez, Jesús, 2014. "An Alternative View of the US Price-Dividend Ratio Dynamics," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    5. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
    6. Michail Karoglou & Bruce Morley & Dennis Thomas, 2013. "Risk and Structural Instability in US House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 424-436, April.
    7. Smith, Aaron, 2005. "Level Shifts and the Illusion of Long Memory in Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 321-335, July.
    8. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    9. Smith, Aaron & Naik, Prasad A. & Tsai, Chih-Ling, 2006. "Markov-switching model selection using Kullback-Leibler divergence," Journal of Econometrics, Elsevier, vol. 134(2), pages 553-577, October.
    10. Zhou, Yinggang, 2014. "Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 216-228.
    11. Pesaran, M. Hashem & Timmermann, Allan, 2004. "How costly is it to ignore breaks when forecasting the direction of a time series?," International Journal of Forecasting, Elsevier, vol. 20(3), pages 411-425.
    12. Granger, Clive W.J. & Machina, Mark J., 2006. "Structural attribution of observed volatility clustering," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 15-29.
    13. Abhimanyu Gupta & Myung Hwan Seo, 2019. "Robust Inference on Infinite and Growing Dimensional Time Series Regression," Papers 1911.08637, arXiv.org, revised Apr 2023.
    14. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    15. Londono, Juan M. & Regúlez, Marta & Vázquez, Jesús, 2015. "An alternative view of the US price–dividend ratio dynamics," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 291-307.
    16. Kanungo, Rama Prasad, 2021. "Uncertainty of M&As under asymmetric estimation," Journal of Business Research, Elsevier, vol. 122(C), pages 774-793.
    17. Massimo Guidolin, 2006. "High equity premia and crash fears - Rational foundations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 693-708, August.
    18. Pietro Veronesi, "undated". "Belief-dependent Utilities, Aversion to State-Uncertainty and Asset Prices,”," CRSP working papers 529, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    19. J. Doyne Farmer & John Geanakoplos, 2008. "The Virtues and Vices of Equilibrium and the Future of Financial Economics," Levine's Working Paper Archive 122247000000002067, David K. Levine.
    20. Giorgio Valente & Lucio Sarno, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376.
    21. Daniel Andrei & Bruce Carlin & Michael Hasler, 2019. "Asset Pricing with Disagreement and Uncertainty About the Length of Business Cycles," Management Science, INFORMS, vol. 67(6), pages 2900-2923, June.
    22. Bernales, Alejandro & Chen, Louisa & Valenzuela, Marcela, 2017. "Learning and forecasts about option returns through the volatility risk premium," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 312-330.
    23. Guidolin, Massimo & Timmermann, Allan, 2007. "Properties of equilibrium asset prices under alternative learning schemes," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 161-217, January.
    24. Christian Pierdzioch & Daniel Hartmann, 2013. "Forecasting Eurozone real-estate returns," Applied Financial Economics, Taylor & Francis Journals, vol. 23(14), pages 1185-1196, July.
    25. Hyein Shim & Hyeyoen Kim & Sunghyun Kim & Doojin Ryu, 2016. "Testing the relative purchasing power parity hypothesis: the case of Korea," Applied Economics, Taylor & Francis Journals, vol. 48(25), pages 2383-2395, May.
    26. Kelly David L. & Steigerwald Douglas G, 2004. "Private Information and High-Frequency Stochastic Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(1), pages 1-30, March.
    27. Yi Xue & Ramazan Gencay, 2009. "Trading Frequency and Volatility Clustering," Working Paper series 31_09, Rimini Centre for Economic Analysis.
    28. Jean-Marie Dufour & Richard Luger, 2017. "Identification-robust moment-based tests for Markov-switching in autoregressive models," Cahiers de recherche 1701, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    29. Massimo Guidolin & Kai Wang, 2022. "The Empirical Performance of Option Implied Volatility Surface-Driven Optimal Portfolios," BAFFI CAREFIN Working Papers 22190, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    30. Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, August.
    31. Massimo Guidolin, 2005. "Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle," Working Papers 2005-005, Federal Reserve Bank of St. Louis.
    32. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    33. Roman Frydman & Soren Johansen & Anders Rahbek & Morten Nyboe Tabor, 2021. "Asset Prices Under Knightian Uncertainty," Working Papers Series inetwp172, Institute for New Economic Thinking.
    34. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    35. Aaron Smith, 2005. "Forecasting in the presence of level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 557-574.
    36. Abbigail J. Chiodo & Massimo Guidolin & Michael T. Owyang & Makoto Shimoji, 2003. "Subjective probabilities: psychological evidence and economic applications," Working Papers 2003-009, Federal Reserve Bank of St. Louis.
    37. Smith Aaron, 2012. "Markov Breaks in Regression Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(1), pages 1-35, May.
    38. Hartmann, Daniel & Kempa, Bernd & Pierdzioch, Christian, 2006. "Economic and Financial Crises and the Predictability of U.S. Stock Returns," MPRA Paper 561, University Library of Munich, Germany.
    39. Massimiliano De Santis, 2005. "Movements in the Equity Premium: Evidence from a Bayesian Time-Varying VAR," Money Macro and Finance (MMF) Research Group Conference 2005 62, Money Macro and Finance Research Group.
    40. Guidolin, Massimo, 2003. "International asset prices and portfolio choices under Bayesian learning," Research in Economics, Elsevier, vol. 57(4), pages 383-437, December.
    41. Matei Demetrescu, 2007. "Volatility Clustering in High-Frequency Data: A self-fulfilling prophecy?," Economics Bulletin, AccessEcon, vol. 7(15), pages 1-8.
    42. Yang Lu & Michael Siemer, 2013. "Learning, Rare Disasters, and Asset Prices," Finance and Economics Discussion Series 2013-85, Board of Governors of the Federal Reserve System (U.S.).

  43. White, Halbert & Timmermann, Allan & Sullivan, Ryan, 2001. "Forecast Evaluation with Shared Data Sets," CEPR Discussion Papers 3060, C.E.P.R. Discussion Papers.

    Cited by:

    1. Saša ŽIKOVIÆ & Randall K. FILER, 2013. "Ranking of VaR and ES Models: Performance in Developed and Emerging Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(4), pages 327-359, August.
    2. Jasdeep S. Banga & B. Wade Brorsen, 2019. "Profitability of alternative methods of combining the signals from technical trading systems," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(1), pages 32-45, January.
    3. Andrei Shynkevich, 2021. "Impact of bitcoin futures on the informational efficiency of bitcoin spot market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 115-134, January.
    4. Lu, Tsung-Hsun, 2014. "The profitability of candlestick charting in the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 65-78.
    5. Park, Cheol-Ho & Irwin, Scott H., 2005. "The Profitability of Technical Trading Rules in US Futures Markets: A Data Snooping Free Test," AgMAS Project Research Reports 14771, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    6. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    7. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    8. Fang, Jiali & Jacobsen, Ben & Qin, Yafeng, 2014. "Predictability of the simple technical trading rules: An out-of-sample test," Review of Financial Economics, Elsevier, vol. 23(1), pages 30-45.
    9. A. Olasolo & M. A. Pérez & V. Ruiz, 2016. "Active investment strategies in the Spanish futures market: a solution to avoid data snooping bias," Applied Economics Letters, Taylor & Francis Journals, vol. 23(9), pages 609-613, June.
    10. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
    11. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    12. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    13. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    14. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    15. Cheol‐Ho Park & Scott H. Irwin, 2010. "A reality check on technical trading rule profits in the U.S. futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(7), pages 633-659, July.
    16. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
    17. Robert Ślepaczuk & Grzegorz Zakrzewski & Paweł Sakowski, 2012. "Investment strategies beating the market. What can we squeeze from the market?," Working Papers 2012-04, Faculty of Economic Sciences, University of Warsaw.
    18. Afiruddin Tapa* & Mohd Hasimi Yaacob & Ahmad Husni Hamzah & Yean Soh Chuen, 2018. "Trading Performance Analysis: A Comparisons Between the Original MA Crossover and Modified MA Crossover Strategy," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 933-941:6.
    19. Ślepaczuk Robert & Sakowski Paweł & Zakrzewski Grzegorz, 2018. "Investment Strategies that Beat the Market. What Can We Squeeze from the Market?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(4), pages 36-55, December.

  44. Allan Timmerman & Massimo Guidolin, 2001. "Option prices and implied volatility dynamics under Bayesian learning," CeNDEF Workshop Papers, January 2001 P3, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. A. A. Brown & L. C. G. Rogers, 2009. "Heterogeneous Beliefs with Finite-Lived Agents," Papers 0907.4953, arXiv.org.
    2. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    3. Alexander David & Pietro Veronesi, 1998. "Option Prices with Uncertain Fundamentals: Theory and Evidence on the Dynamics of Implied Volatilities," CRSP working papers 485, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    4. Angus A Brown & L C G Rogers, 2010. "Diverse Beliefs," Papers 1001.1450, arXiv.org.
    5. Sadayuki Ono, 2007. "Option Pricing under Stochastic Volatility and Trading Volume," Discussion Papers 07/05, Department of Economics, University of York.
    6. Paruolo Paolo, 2004. "Automated Inference and the Future of Econometrics: A comment," Economics and Quantitative Methods qf04025, Department of Economics, University of Insubria.
    7. René Garcia & Richard Luger & Eric Renault, 2001. "Empirical Assessment of an Intertemporal Option Pricing Model with Latent Variables (Note : Nouvelle version Février 2002)," CIRANO Working Papers 2001s-02, CIRANO.

  45. Allan Timmermann & Gabriel Perez-Quiros, 2000. "Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities," FMG Discussion Papers dp360, Financial Markets Group.

    Cited by:

    1. Zeng, Songlin & Bec, Frédérique, 2015. "Do stock returns rebound after bear markets? An empirical analysis from five OECD countries," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 50-61.
    2. David Nawrocki & Tonis Vaga, 2014. "A bifurcation model of market returns," Quantitative Finance, Taylor & Francis Journals, vol. 14(3), pages 509-528, March.
    3. Andrew Patton, 2002. "(IAM Series No 001) On the Out-Of-Sample Importance of Skewness and Asymetric Dependence for Asset Allocation," FMG Discussion Papers dp431, Financial Markets Group.
    4. Esfandiar Maasoumi & Jeffrey Racine, 2009. "A Robust Entropy-Based Test of Asymmetry for Discrete and Continuous Processes," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 246-261.
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    38. Zhang, Yue-Jun & Yao, Ting & He, Ling-Yun & Ripple, Ronald, 2019. "Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 302-317.
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    Cited by:

    1. Lu, Yang K. & Perron, Pierre, 2010. "Modeling and forecasting stock return volatility using a random level shift model," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 138-156, January.
    2. Kurmaş Akdoğan, 2017. "Unemployment hysteresis and structural change in Europe," Empirical Economics, Springer, vol. 53(4), pages 1415-1440, December.
    3. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2017. "International stock return predictability: Is the role of U.S. time-varying?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(1), pages 121-146, February.
    4. Altissimo, F. & Corradi, V., 2000. "Strong Rules for Detecting the Number of Breaks in a Time Series," Discussion Papers 0011, University of Exeter, Department of Economics.
    5. Liew, Freddy, 2012. "Forecasting inflation in Asian economies," MPRA Paper 36781, University Library of Munich, Germany.
    6. Kurmaş Akdoğan, 2015. "Asymmetric Behaviour of Inflation around the Target in Inflation-Targeting Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 62(5), pages 486-504, November.

  48. Allan Timmermann & Gabriel Perez-Quiros, 1999. "Firm Size and Cyclical Variations in Stock Returns," FMG Discussion Papers dp335, Financial Markets Group.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. David Nawrocki & Tonis Vaga, 2014. "A bifurcation model of market returns," Quantitative Finance, Taylor & Francis Journals, vol. 14(3), pages 509-528, March.
    3. Francisco Covas & Wouter Denhaan, 2006. "The role of debt and equity finance over the business cycle," 2006 Meeting Papers 407, Society for Economic Dynamics.
    4. Puneet Handa, 2006. "Does Stock Return Predictability Imply Improved Asset Allocation and Performance? Evidence from the U.S. Stock Market (1954–2002)," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2423-2468, September.
    5. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The memory of stock return volatility: Asset pricing implications," Journal of Financial Markets, Elsevier, vol. 47(C).
    6. Paulo Maio, 2014. "Another Look at the Stock Return Response to Monetary Policy Actions," Review of Finance, European Finance Association, vol. 18(1), pages 321-371.
    7. Abdul Karim, Zulkefly & Zaidi, Mohd Azlan Shah & Karim, Bakri, 2011. "Does Firm-Level Equity Return Respond to Domestic and International Monetary Policy Shocks? A Panel Data Study of Malaysia," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 45, pages 21-31.
    8. Pandey I M, 2005. "What Drives the Shareholer Value?," IIMA Working Papers WP2005-09-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    9. Bazgour, Tarik & Heuchenne, Cédric & Hübner, Georges & Sougné, Danielle, 2021. "How do volatility regimes affect the pricing of quality and liquidity in the stock market?," LIDAM Reprints ISBA 2021038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Cem Cakmakli & Richard Paap & Dick J.C. van Dijk, 2011. "Modeling and Estimation of Synchronization in Multistate Markov-Switching Models," Tinbergen Institute Discussion Papers 11-002/4, Tinbergen Institute.
    11. Hur, Jungshik & Pettengill, Glenn & Singh, Vivek, 2014. "Market states and the risk-based explanation of the size premium," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 139-150.
    12. Alessandra Guariglia & Marina-Eliza Spaliara & Serafeim Tsoukas, 2016. "To What Extent Does the Interest Burden Affect Firm Survival? Evidence from a Panel of UK Firms during the Recent Financial Crisis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 576-594, August.
    13. Peng Huang & C. James Hueng, 2009. "Interest-rate risk factor and stock returns: a time-varying factor-loadings model," Applied Financial Economics, Taylor & Francis Journals, vol. 19(22), pages 1813-1824.
    14. Alexandros Kontonikas & Alexandros Kostakis, 2013. "On Monetary Policy and Stock Market Anomalies," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 40(7-8), pages 1009-1042, September.
    15. Block, Joern & Fisch, Christian & Vismara, Silvio & Andres, René, 2019. "Private equity investment criteria: An experimental conjoint analysis of venture capital, business angels, and family offices," Journal of Corporate Finance, Elsevier, vol. 58(C), pages 329-352.
    16. Pesaran, M. Hashem & Timmermann, Allan, 2002. "Market timing and return prediction under model instability," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 495-510, December.
    17. Carol Alexander & Anca Dimitriu, 2003. "Equity Indexing: Conitegration and Stock Price Dispersion: A Regime Switiching Approach to market Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2003-02, Henley Business School, University of Reading.
    18. Don Bredin & Stuart Hyde, 2008. "Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies," European Financial Management, European Financial Management Association, vol. 14(2), pages 315-346, March.
    19. Eijffinger, S.C.W. & Mahieu, R.J. & Raes, L.B.D., 2012. "Can the Fed talk the Hind Legs off the Stock Market? (replaces CentER DP 2011-072)," Other publications TiSEM 347a970d-4a05-416f-a351-1, Tilburg University, School of Economics and Management.
    20. L. Baele & R. Vander Vennet & A. Van Landschoot, 2004. "Bank Risk Strategies and Cyclical Variation in Bank Stock Returns," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/217, Ghent University, Faculty of Economics and Business Administration.
    21. Renatas Kizys & Peter Spencer, 2007. "Assessing the Relation between Equity Risk Premium and Macroeconomic Volatilities in the UK," Discussion Papers 07/13, Department of Economics, University of York.
    22. Massimo Guidolin & Allan Timmerman, 2006. "Asset allocation under multivariate regime switching," Working Papers 2005-002, Federal Reserve Bank of St. Louis.
    23. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    24. David McMillan & Alan Speight, 2006. "Non-linear long horizon returns predictability: evidence from six south-east Asian markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(2), pages 95-111, June.
    25. Zolotoy, Leon & Frederickson, James R. & Lyon, John D., 2017. "Aggregate earnings and stock market returns: The good, the bad, and the state-dependent," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 157-175.
    26. David G. McMillan, 2009. "Non-linear interest rate dynamics and forecasting: evidence for US and Australian interest rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(2), pages 139-155.
    27. Tsai, Chun-Li, 2013. "The high-frequency asymmetric response of stock returns to monetary policy for high oil price events," Energy Economics, Elsevier, vol. 36(C), pages 166-176.
    28. Ehrmann, M., 2000. "Firm Size and Monetary Policy Transmission - Evidence from German Business Survey Data," Economics Working Papers eco2000/12, European University Institute.
    29. Andrew Phiri, 2018. "Has the South African Reserve Bank responded to equity returns since the sub-prime crisis? An asymmetric convergence approach," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 10(3), pages 205-225.
    30. Yeoh, Siew-Boey & Hooy, Chee-Wooi, 2024. "Is the military CEO aggressive or conservative? Differences in legal and cultural factors around the world," Research in International Business and Finance, Elsevier, vol. 70(PA).
    31. Ahn, Dong-Hyun & Min, Byoung-Kyu & Yoon, Bohyun, 2019. "Why has the size effect disappeared?," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 256-276.
    32. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    33. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    34. Lorenzo Cerboni Baiardi & Massimo Costabile & Domenico De Giovanni & Fabio Lamantia & Arturo Leccadito & Ivar Massabó & Massimiliano Menzietti & Marco Pirra & Emilio Russo & Alessandro Staino, 2020. "The Dynamics of the S&P 500 under a Crisis Context: Insights from a Three-Regime Switching Model," Risks, MDPI, vol. 8(3), pages 1-15, July.
    35. Pawel Bilinski & Danielle Lyssimachou, 2014. "Risk Interpretation of the CAPM's Beta: Evidence from a New Research Method," Abacus, Accounting Foundation, University of Sydney, vol. 50(2), pages 203-226, June.
    36. Turtle, H.J. & Zhang, Chengping, 2012. "Time-varying performance of international mutual funds," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 334-348.
    37. Qadan, Mahmoud & Aharon, David Y., 2019. "Can investor sentiment predict the size premium?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 10-26.
    38. Dennis Wesselbaum, 2022. "Cheap Talk in a New Keynesian Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 661-691, September.
    39. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    40. Atanasov, Victoria & Nitschka, Thomas, 2017. "Firm size, economic risks, and the cross-section of international stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 110-126.
    41. Bauer, Rob & Derwall, Jeroen & Molenaar, Roderick, 2004. "The real-time predictability of the size and value premium in Japan," Pacific-Basin Finance Journal, Elsevier, vol. 12(5), pages 503-523, November.
    42. Wu-Jen Chuang & Liang-Yuh Ou-Yang & Wen-Chen Lo, 2009. "Nonlinear Market Dynamics Between Stock Returns And Trading Volume: Empirical Evidences From Asian Stock Markets," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 621-634, November.
    43. Héctor M. Zárate Solano & Norberto Rodríguez Niño & Margarita Marín Jaramillo, 2012. "El tamaño de las empresas y la transmisión de la política monetaria en Colombia: una aplicación con la encuesta mensual de expectativas económicas," Borradores de Economia 721, Banco de la Republica de Colombia.
    44. Fedorova, E. & Afanasev, D., 2014. "Comprehensive Crisis Indicator for Russia," Journal of the New Economic Association, New Economic Association, vol. 23(3), pages 38-59.
    45. Ali Ozdagli & Mihail Velikov, 2016. "Show me the money: the monetary policy risk premium," Working Papers 16-27, Federal Reserve Bank of Boston.
    46. Pesaran, M. Hashem & Timmermann, Allan, 2004. "How costly is it to ignore breaks when forecasting the direction of a time series?," International Journal of Forecasting, Elsevier, vol. 20(3), pages 411-425.
    47. Lucia BALDI & Massimo PERI & Daniela VANDONE, 2010. "Is wine a financial parachute?," Departmental Working Papers 2010-01, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
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  50. Lunde, Asger & Timmermann, Allan & Blake, David, 1998. "The Hazards of Mutual Fund Underperformance: A Cox Regression Analysis," University of California at San Diego, Economics Working Paper Series qt1pd3z1hm, Department of Economics, UC San Diego.

    Cited by:

    1. Emmanuel Mamatzakis & Mike G. Tsionas, 2021. "Testing for persistence in US mutual funds’ performance: a Bayesian dynamic panel model," Annals of Operations Research, Springer, vol. 299(1), pages 1203-1233, April.
    2. A. Colin Cameron & Anthony D. Hall, 2003. "A Survival Analysis of Australian Equity Mutual Funds," Australian Journal of Management, Australian School of Business, vol. 28(2), pages 209-226, September.
    3. Ma, Tiejun & Tang, Leilei & McGroarty, Frank & Sung, Ming-Chien & Johnson, Johnnie E. V, 2016. "Time is money: Costing the impact of duration misperception in market prices," European Journal of Operational Research, Elsevier, vol. 255(2), pages 397-410.
    4. Kozo Kiyota & Miho Takizawa, 2007. "The Shadow of Death: Pre-exit Performance of Firms in Japan," Hi-Stat Discussion Paper Series d06-204, Institute of Economic Research, Hitotsubashi University.
    5. Blake, David & Cairns, Andrew & Dowd, Kevin, 2008. "Turning pension plans into pension planes: What investment strategy designers of defined contribution pension plans can learn from commercial aircraft designers," MPRA Paper 33749, University Library of Munich, Germany.
    6. Bank for International Settlements, 2003. "Incentive structures in institutional asset management and their implications for financial markets," CGFS Papers, Bank for International Settlements, number 21.
    7. Qiang Bu & Nelson Lacey, 2009. "On understanding mutual fund terminations," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(1), pages 80-99, January.
    8. Stephen Brown & William Goetzmann & James Park, 1998. "Conditions for Survival: Changing Risk and the Performance of Hedge Fund Managers and CTAs," Yale School of Management Working Papers ysm83, Yale School of Management, revised 01 Apr 2008.
    9. Darolles, Serge & Florens, Jean-Pierre & Simon, Guillaume, 2010. "Nonparametric Analysis of Hedge Funds Lifetimes," IDEI Working Papers 620, Institut d'Économie Industrielle (IDEI), Toulouse.
    10. Mohammad Mojtahedi & Sidney Newton & Jason Meding, 2017. "Predicting the resilience of transport infrastructure to a natural disaster using Cox’s proportional hazards regression model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(2), pages 1119-1133, January.
    11. Jung-Min KIM, 2015. "Failure Risk and the Cross-Section of Hedge Fund Returns," Working Papers 2015-13, Economic Research Institute, Bank of Korea.
    12. Emmanuel Mamatzakis & Mike Tsionas, 2018. "A Bayesian dynamic model to test persistence in funds' performance," Working Paper series 18-23, Rimini Centre for Economic Analysis.
    13. Fletcher, Jonathan & Forbes, David, 2002. "An exploration of the persistence of UK unit trust performance," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 475-493, December.
    14. Cogneau, Philippe & Hübner, Georges, 2015. "The prediction of fund failure through performance diagnostics," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 224-241.
    15. Juan Yao & Graham Partington & Max Stevenson, 2005. "Run length and the predictability of stock price reversals," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 45(4), pages 653-671, December.
    16. Yehong Liu & Guosheng Yin, 2018. "Average Holding Price," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-20, March.
    17. Bessler, Wolfgang & Blake, David & Lückoff, Peter & Tonks, Ian, 2010. "Why does mutual fund performance not persist? The impact and interaction of fund flows and manager changes," MPRA Paper 34185, University Library of Munich, Germany.
    18. Matallín-Sáez, Juan Carlos & Soler-Domínguez, Amparo & Tortosa-Ausina, Emili, 2016. "On the robustness of persistence in mutual fund performance," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 192-231.
    19. Carree, Martin A., 2003. "A hazard rate analysis of Russian commercial banks in the period 1994-1997," Economic Systems, Elsevier, vol. 27(3), pages 255-269, September.
    20. Hanke, Bernd & Keswani, Aneel & Quigley, Garrett & Zagonov, Maxim, 2018. "Survivorship bias and comparability of UK open-ended fund databases," Economics Letters, Elsevier, vol. 172(C), pages 110-114.
    21. Boldron, François & Fève, Frédérique & Florens, Jean-Pierre & Panet-Amaro, C. & Valognes, C., 2010. "Econometric Models and the Evolution of Post-Offices Network," IDEI Working Papers 626, Institut d'Économie Industrielle (IDEI), Toulouse.
    22. Peter A. F. Fraser‐Mackenzie & Tiejun Ma & Ming‐Chien Sung & Johnnie E. V. Johnson, 2019. "Let's Call it Quits: Break‐Even Effects in the Decision to Stop Taking Risks," Risk Analysis, John Wiley & Sons, vol. 39(7), pages 1560-1581, July.
    23. Alex Grecu & Burton G. Malkiel & Atanu Saha, 2006. "Why Do Hedge Funds Stop Reporting Their Performance?," Working Papers 78, Princeton University, Department of Economics, Center for Economic Policy Studies..
    24. Boyson, Nicole M., 2010. "Implicit incentives and reputational herding by hedge fund managers," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 283-299, June.
    25. Xisong Jin & Francisco Nadal De Simone, 2015. "Investment funds? vulnerabilities: A tail-risk dynamic CIMDO approach," BCL working papers 95, Central Bank of Luxembourg.
    26. Jin, Xisong & Nadal De Simone, Francisco, 2014. "A framework for tracking changes in the intensity of investment funds' systemic risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 343-368.
    27. Naohiko Baba & Hiromichi Goko, 2006. "Survival Analysis of Hedge Funds," Bank of Japan Working Paper Series 06-E-5, Bank of Japan.
    28. Cumming, Douglas & Dai, Na & Johan, Sofia, 2015. "Are hedge funds registered in Delaware different?," Journal of Corporate Finance, Elsevier, vol. 35(C), pages 232-246.
    29. Carree, M.A., 2000. "Interest and Hazard Rates of Russian Saving Banks," ERIM Report Series Research in Management ERS-2000-26-STR, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    30. Yamashita, Takashi, 2007. "House price appreciation, liquidity constraints, and second mortgages," Journal of Urban Economics, Elsevier, vol. 62(3), pages 424-440, November.
    31. Zhao, Xinge, 2004. "Why are some mutual funds closed to new investors?," Journal of Banking & Finance, Elsevier, vol. 28(8), pages 1867-1887, August.

  51. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 1998. "Dangers of Data-Driven Inference: The Case of Calendar Effects in Stock Returns," University of California at San Diego, Economics Working Paper Series qt2z02z6d9, Department of Economics, UC San Diego.

    Cited by:

    1. Ayman Abdalmajeed Ahmad Al-Smadi & Mahmoud Khalid Almsafir & Nur Hanis Hazwani Binti Husni, 2018. "Trends And Calendar Effects In Malaysia’S Stock Market," Romanian Economic Business Review, Romanian-American University, vol. 13(2), pages 15-22, June.
    2. Hendry, David F., 2001. "Achievements and challenges in econometric methodology," Journal of Econometrics, Elsevier, vol. 100(1), pages 7-10, January.
    3. Goran Karanovic & Bisera Karanovic, 2018. "The Day-of-the-Week Effect: Evidence from Selected Balkan Markets," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(1), pages 1-11, March.
    4. Kunkel, Robert A. & Compton, William S. & Beyer, Scott, 2003. "The turn-of-the-month effect still lives: the international evidence," International Review of Financial Analysis, Elsevier, vol. 12(2), pages 207-221.
    5. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    6. David McMillan & Alan Speight, 2004. "Intra-day periodicity, temporal aggregation and time-to-maturity in FTSE-100 index futures volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 253-263.
    7. Edwin D. Maberly & Daniel F. Waggoner, 2000. "Closing the question on the continuation of turn-of-the-month effects: evidence from the S&P 500 Index futures contract," FRB Atlanta Working Paper 2000-11, Federal Reserve Bank of Atlanta.
    8. Sasidharan, Anand, 2009. "Does seasonality persists in Indian stock markets?," MPRA Paper 24185, University Library of Munich, Germany, revised Aug 2010.
    9. Philip Kostov & Seamus McErlean, 2004. "Estimating the probability of large negative stock market," Finance 0409011, University Library of Munich, Germany.
    10. Lee, Tae-Hwy & Saltoglu, Burak, 2002. "Assessing the risk forecasts for Japanese stock market," Japan and the World Economy, Elsevier, vol. 14(1), pages 63-85, January.

  52. Blake, David & Lehmann, Bruce N & Timmermann, Allan G, 1997. "Performance Measurement using Multiple Asset Class Portfolio Data," CEPR Discussion Papers 1618, C.E.P.R. Discussion Papers.

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    1. Whitehouse, Edward, 2000. "Pension reform, financial literacy and public information : a case study of the United Kingdom," Social Protection Discussion Papers and Notes 21312, The World Bank.
    2. Whitehouse, Edward, 2000. "Administrative charges for funded pensions : an international comparison and assessment," Social Protection Discussion Papers and Notes 23140, The World Bank.
    3. Whitehouse, Edward, 2000. "Paying for pensions: An international comparison of administrative charges in funded retirement-income systems," MPRA Paper 14171, University Library of Munich, Germany.
    4. Srinivas, P.S. & Whitehouse, Edward & Yermo, Juan, 2000. "Regulating private pension funds'structure, performance, and investments : cross-country evidence," Social Protection Discussion Papers and Notes 23302, The World Bank.
    5. Claudio Borio & Craig Furfine & Philip Lowe, 2001. "Procyclicality of the financial system and financial stability: issues and policy options," BIS Papers chapters, in: Bank for International Settlements (ed.), Marrying the macro- and micro-prudential dimensions of financial stability, volume 1, pages 1-57, Bank for International Settlements.
    6. Manuel Ammann & Andreas Zingg, 2008. "Investment Performance of Swiss Pension Funds and Investment Foundations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(II), pages 153-195, June.

  53. Pesaran, M. H. & Timmermann, A., 1996. "A Recursive Modelling Approach to Predicting UK Stock Returns'," Cambridge Working Papers in Economics 9625, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Döpke, Jörg & Hartmann, Daniel & Pierdzioch, Christian, 2006. "Forecasting stock market volatility with macroeconomic variables in real time," Discussion Paper Series 2: Banking and Financial Studies 2006,01, Deutsche Bundesbank.
    2. M. Hashem Pesaran, 2000. "The Cost Efficiency of UK Debt Management: A Recursive Modelling Approach," CESifo Working Paper Series 346, CESifo.
    3. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    4. Alan Gregory, 2011. "The Expected Cost of Equity and the Expected Risk Premium in the UK," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 3(1), pages 1-26, April.
    5. Massimiliano Kaucic, 2009. "Predicting EU Energy Industry Excess Returns on EU Market Index via a Constrained Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 34(2), pages 173-193, September.
    6. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
    7. Pesaran, M. Hashem & Timmermann, Allan, 2002. "Market timing and return prediction under model instability," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 495-510, December.
    8. Favero, Carlo A. & Milani, Fabio, 2005. "Parameter Instability, Model Uncertainty and the Choice of Monetary Policy," CEPR Discussion Papers 4909, C.E.P.R. Discussion Papers.
    9. Poshakwale, Sunil S. & Chandorkar, Pankaj & Agarwal, Vineet, 2019. "Implied volatility and the cross section of stock returns in the UK," Research in International Business and Finance, Elsevier, vol. 48(C), pages 271-286.
    10. Groenewold, Nicolaas & Kan Tang, Sam Hak & Wu, Yanrui, 2008. "The profitability of regression-based trading rules for the Shanghai stock market," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 411-430.
    11. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    12. M. Hashem Pesaran, 2005. "Market Efficiency Today," IEPR Working Papers 05.41, Institute of Economic Policy Research (IEPR).
    13. Chau, Frankie & Deesomsak, Rataporn & Lau, Marco C.K., 2011. "Investor sentiment and feedback trading: Evidence from the exchange-traded fund markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 292-305.
    14. M. Hashem Pesaran, 2010. "Predictability of Asset Returns and the Efficient Market Hypothesis," CESifo Working Paper Series 3116, CESifo.
    15. Phillips, Peter C.B., 2005. "Automated Discovery In Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 3-20, February.
    16. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    17. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    18. Sen, Chitrakalpa & Chakrabarti, Gagari & Sarkar, Amitava, 1981. "Asymmetric Response in Foreign Exchange Volatility under Structural Break," MPRA Paper 26817, University Library of Munich, Germany.
    19. Dahmene, Meriam & Boughrara, Adel & Slim, Skander, 2021. "Nonlinearity in stock returns: Do risk aversion, investor sentiment and, monetary policy shocks matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 676-699.
    20. Jeffrey Jarrett & Eric Kyper, 2006. "Capital market efficiency and the predictability of daily returns," Applied Economics, Taylor & Francis Journals, vol. 38(6), pages 631-636.
    21. Wolfgang Gohout & Katja Specht, 2007. "Mean-variance portfolios using Bayesian vector-autoregressive forcasts," Statistical Papers, Springer, vol. 48(3), pages 403-418, September.
    22. Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian & Wohar, Mark E., 2017. "Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 276-284.
    23. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    24. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and state-level stock market realized volatility," Journal of Financial Markets, Elsevier, vol. 66(C).
    25. Villalba-Padilla, Fátima Irina & Flores-Ortega, Miguel, 2012. "Capacidad de predicción de los modelos GARCH simétricos aplicados a variables financieras de México 2001-2011," eseconomía, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 0(34), pages 81-124, segundo t.
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    29. Andrada-Félix Julián & Fernadez-Rodriguez Fernando & Garcia-Artiles Maria-Dolores & Sosvilla-Rivero Simon, 2003. "An Empirical Evaluation of Non-Linear Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-32, October.
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    33. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers 2010-039, Federal Reserve Bank of St. Louis.
    34. David McMillan, 2004. "Non-linear predictability of UK stock market returns," Money Macro and Finance (MMF) Research Group Conference 2003 63, Money Macro and Finance Research Group.
    35. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    36. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    37. Kadilli, Anjeza, 2015. "Predictability of stock returns of financial companies and the role of investor sentiment: A multi-country analysis," Journal of Financial Stability, Elsevier, vol. 21(C), pages 26-45.
    38. Rohloff, Sebastian & Pierdzioch, Christian & Risse, Marian, 2014. "Fluctuations of the Real Exchange Rate, Real Interest Rates, and the Dynamics of the Price of Gold in a Small Open Economy," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100429, Verein für Socialpolitik / German Economic Association.
    39. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    40. Smith, Ron, 2002. "Comments on 'The state of macroeconomic forecasting'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 491-493, December.
    41. Christian Pierdzioch & Daniel Hartmann, 2013. "Forecasting Eurozone real-estate returns," Applied Financial Economics, Taylor & Francis Journals, vol. 23(14), pages 1185-1196, July.
    42. Daniel Hartmann & Christian Pierdzioch, 2007. "International equity flows and the predictability of US stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 583-599.
    43. Carlo A. Favero, "undated". "Parameters´ Instability, Model Uncertainty and Optimal Monetary Policy," Working Papers 196, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    44. Guidolin, Massimo & Hyde, Stuart, 2012. "Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 695-716.
    45. George Kapetanios & Vincent Labhard & Simon Price, 2007. "Forecast combination and the Bank of England’s suite of statistical forecasting models," Bank of England working papers 323, Bank of England.
    46. Neil Kellard & John Nankervis & Fotis Papadimitriou, 2007. "Predicting the UK Equity Premium with Dividend Ratios: An Out-Of-Sample Recursive Residuals Graphical Approach," Money Macro and Finance (MMF) Research Group Conference 2006 129, Money Macro and Finance Research Group.
    47. Ioannidis, C. & Peel, D.A. & Matthews, K.P.G., 2006. "Expected stock returns, aggregate consumption and wealth: Some further empirical evidence," Journal of Macroeconomics, Elsevier, vol. 28(2), pages 439-445, June.
    48. Naser, Hanan & Alaali, Fatema, 2015. "Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach," MPRA Paper 65295, University Library of Munich, Germany, revised 25 Jun 2015.
    49. Angela J. Black & David G. McMillan, 2004. "Non‐linear Predictability of Value and Growth Stocks and Economic Activity," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(3‐4), pages 439-474, April.
    50. Aatola, Piia & Ollikka, Kimmo & Ollikainen, Markku, 2012. "Informational Efficiency of the EU ETS market – a study of price predictability and profitable trading," Working Papers 28, VATT Institute for Economic Research.
    51. Jakob B. Madsen & E. Philip Davis, 2004. "Equity Prices, Productivity Growth and 'The New Economy," FRU Working Papers 2004/11, University of Copenhagen. Department of Economics. Finance Research Unit.
    52. Pesaran, M.H. & Timmermann, A., 2004. "‘Real Time Econometrics’," Cambridge Working Papers in Economics 0432, Faculty of Economics, University of Cambridge.
    53. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    54. Hanan Naser & Fatema Alaali, 2018. "Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach," Empirical Economics, Springer, vol. 55(4), pages 1757-1777, December.
    55. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    56. McMillan, David G., 2007. "Non-linear forecasting of stock returns: Does volume help?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 115-126.
    57. Dell'Aquila, Rosario & Ronchetti, Elvezio, 2006. "Stock and bond return predictability: the discrimination power of model selection criteria," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1478-1495, March.
    58. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    59. Asteriou, Dimitrios & Bashmakova, Yuliya, 2013. "Assessing the impact of oil returns on emerging stock markets: A panel data approach for ten Central and Eastern European Countries," Energy Economics, Elsevier, vol. 38(C), pages 204-211.
    60. Döpke, Jörg & Hartmann, Daniel & Pierdzioch, Christian, 2008. "Real-time macroeconomic data and ex ante stock return predictability," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 274-290.
    61. T. Hendricks & B. Kempa & C. Pierdzioch, 2010. "Do local analysts have an informational advantage in forecasting stock returns? Evidence from the German DAX30," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(2), pages 137-158, June.
    62. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    63. Sarantis, Nicholas, 2006. "On the short-term predictability of exchange rates: A BVAR time-varying parameters approach," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2257-2279, August.
    64. Coe, P.J. & Pesaran, M.H. & Vahey, S.P., 2003. "Scope for Cost Minimization in Public Debt Management: the Case of the UK," Cambridge Working Papers in Economics 0338, Faculty of Economics, University of Cambridge.
    65. Mohammad Hasan, 2008. "Stock returns, inflation and interest rates in the United Kingdom," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 687-699.
    66. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2015. "A real-time quantile-regression approach to forecasting gold returns under asymmetric loss," Resources Policy, Elsevier, vol. 45(C), pages 299-306.
    67. Abhyankar, Abhay & Ho, Keng-Yu, 2006. "Long-run abnormal performance following convertible preference share and convertible bond issues: New evidence from the United Kingdom," International Review of Economics & Finance, Elsevier, vol. 15(1), pages 97-119.
    68. Sakar Hasan Hamza & Qingna Li, 2023. "The Dynamics of US Gasoline Demand and Its Prediction: An Extended Dynamic Model Averaging Approach," Energies, MDPI, vol. 16(12), pages 1-13, June.
    69. David McMillan & Mark Wohar, 2013. "UK stock market predictability: evidence of time variation," Applied Financial Economics, Taylor & Francis Journals, vol. 23(12), pages 1043-1055, June.
    70. Mollick, André Varella & Assefa, Tibebe Abebe, 2013. "U.S. stock returns and oil prices: The tale from daily data and the 2008–2009 financial crisis," Energy Economics, Elsevier, vol. 36(C), pages 1-18.
    71. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2007. "Investing for the Long-run in European Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 34(1), pages 35-80, January.
    72. Dirk Nitzsche & Keith Cuthbertson & Niall O'Sullivan, 2005. "Mutual Fund Performance: Skill Or Luck?," Money Macro and Finance (MMF) Research Group Conference 2005 4, Money Macro and Finance Research Group.
    73. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2018. "How good can heuristic-based forecasts be? A comparative performance of econometric and heuristic models for UK and US asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 139-169, January.
    74. Nektarios Aslanidis, 2002. "Smooth Transition Regression Models in UK Stock Returns," Working Papers 0201, University of Crete, Department of Economics.
    75. Jeffrey E. Jarrett, 2008. "Predicting Daily Stock Returns: A Lengthy Study of the Hong Kong and Tokyo Stock Exchanges," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(1), pages 37-51, April.
    76. Hartmann, Daniel & Pierdzioch, Christian, 2006. "Nonlinear Links between Stock Returns and Exchange Rate Movements," MPRA Paper 558, University Library of Munich, Germany.
    77. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    78. Aslanidis, Nektarios & Osborn, Denise R. & Sensier, Marianne, 2008. "Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations," Working Papers 2072/8950, Universitat Rovira i Virgili, Department of Economics.
    79. Chronopoulos, Dimitris K. & Papadimitriou, Fotios I. & Vlastakis, Nikolaos, 2018. "Information demand and stock return predictability," Journal of International Money and Finance, Elsevier, vol. 80(C), pages 59-74.
    80. Ali Habibnia & Esfandiar Maasoumi, 2021. "Forecasting in Big Data Environments: An Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 363-381, December.
    81. Kamel Laaradh, 2007. "« Investir Sur Le Marche Inernational Des Actions A-T-Il Plus D'Effet Sur La Persistance De La Performance Des Fonds ? Illustration Britannique »," Post-Print halshs-00544930, HAL.
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    84. Patrick J. Coe & M. Hashem Pesaran & Shaun P. Vahey, 2005. "The Cost Effectiveness of the UK's Sovereign Debt Portfolio," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(4), pages 467-495, August.
    85. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
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    87. Chau, Frankie & Deesomsak, Rataporn, 2015. "Business cycle variation in positive feedback trading: Evidence from the G-7 economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 35(C), pages 147-159.
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    92. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Bonsu, Christiana Osei & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "The effects of public sentiments and feelings on stock market behavior: Evidence from Australia," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 443-472.
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    Cited by:

    1. M. Hashem Pesaran, 2000. "The Cost Efficiency of UK Debt Management: A Recursive Modelling Approach," CESifo Working Paper Series 346, CESifo.
    2. Dorfmann, Jeffrey & Karali, Berna, 2015. "A Nonparametric Search for Information Effects from USDA Reports," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 40(1), pages 1-20.
    3. Chance, Don M. & Hemler, Michael L., 2001. "The performance of professional market timers: daily evidence from executed strategies," Journal of Financial Economics, Elsevier, vol. 62(2), pages 377-411, November.
    4. Meade, Nigel, 2002. "A comparison of the accuracy of short term foreign exchange forecasting methods," International Journal of Forecasting, Elsevier, vol. 18(1), pages 67-83.
    5. Krishna, Kala & Ozyildirim, Ataman & Swanson, Norman R., 2003. "Trade, investment and growth: nexus, analysis and prognosis," Journal of Development Economics, Elsevier, vol. 70(2), pages 479-499, April.
    6. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
    7. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.
    8. Lucian Liviu ALBU & Carlos MatéJIMÉNEZ & Mihaela SIMIONESCU, 2015. "The Assessment of Some Macroeconomic Forecasts for Spain using Aggregated Accuracy Indicators," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 30-47, June.
    9. Utpal Bhattacharya & Benjamin Loos & Steffen Meyer & Andreas Hackethal, 2017. "Abusing ETFs," Review of Finance, European Finance Association, vol. 21(3), pages 1217-1250.
    10. Christian Pierdzioch, 2012. "Macroeconomic Factors and the German Real Estate Market: A Stock-Market-Based Forecasting Experiment," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 87-96, May.
    11. Kladívko, Kamil & Österholm, Pär, 2021. "Do market participants’ forecasts of financial variables outperform the random-walk benchmark?," Finance Research Letters, Elsevier, vol. 40(C).
    12. Swanson, N.R. & White, H., 1995. "A Models Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Papers 04-95-12, Pennsylvania State - Department of Economics.
    13. Sentana, Juan, 2022. "Tests for independence between categorical variables," Economics Letters, Elsevier, vol. 220(C).
    14. Jia, Jian & Kang, Sang Baum, 2022. "Do the basis and other predictors of futures return also predict spot return with the same signs and magnitudes? Evidence from the LME," Journal of Commodity Markets, Elsevier, vol. 25(C).
    15. Bakshi, Gurdip & Panayotov, George, 2013. "Predictability of currency carry trades and asset pricing implications," Journal of Financial Economics, Elsevier, vol. 110(1), pages 139-163.
    16. Jordi Pons, 2001. "The rationality of price forecasts: a directional analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 11(3), pages 287-290.
    17. McCracken,M.W. & West,K.D., 2001. "Inference about predictive ability," Working papers 14, Wisconsin Madison - Social Systems.
    18. Serafeim Tsoukas & Marina-Eliza Spaliara, 2014. "Market Implied Ratings and Financing Constraints: Evidence from US Firms," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 41(1-2), pages 242-269, January.
    19. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    20. Mizen, Paul & Tsoukas, Serafeim, 2012. "Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model," International Journal of Forecasting, Elsevier, vol. 28(1), pages 273-287.
    21. Anatolyev, Stanislav & Kosenok, Grigory, 2009. "Tests in contingency tables as regression tests," Economics Letters, Elsevier, vol. 105(2), pages 189-192, November.
    22. Coe, P.J. & Pesaran, M.H. & Vahey, S.P., 2003. "Scope for Cost Minimization in Public Debt Management: the Case of the UK," Cambridge Working Papers in Economics 0338, Faculty of Economics, University of Cambridge.
    23. Sanders, Dwight R. & Manfredo, Mark R. & Boris, Keith, 2008. "Accuracy and efficiency in the U.S. Department of Energy's short-term supply forecasts," Energy Economics, Elsevier, vol. 30(3), pages 1192-1207, May.
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    1. Carl Chiarella & Xue-Zhong He & Cars Hommes, 2004. "A Dynamic Analysis of Moving Average Rules," Research Paper Series 133, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. Granger, C.W.J. & Pesaran, M. H., 1999. "Economic and Statistical Measures of Forecast Accuracy," Cambridge Working Papers in Economics 9910, Faculty of Economics, University of Cambridge.
    3. M. Hashem Pesaran & Simon M. Potter, 1993. "Equilibrium Asset Pricing Models and Predictability of Excess Returns," UCLA Economics Working Papers 694, UCLA Department of Economics.
    4. Stephen E. Satchell & Shaun A. Bond, 2004. "Asymmetry, Loss Aversion and Forecasting," Econometric Society 2004 Australasian Meetings 160, Econometric Society.

  56. Pesaran, M.H. & Timmermann, A., 1990. "A Simple, Non-Parametric Test Of Predictive Performance," Cambridge Working Papers in Economics 9021, Faculty of Economics, University of Cambridge.

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    391. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
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    400. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
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    403. Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023. "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, vol. 64(C).
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    Cited by:

    1. Chen, Shiyi & Jeong, Kiho & Härdle, Wolfgang Karl, 2008. "Recurrent support vector regression for a nonlinear ARMA model with applications to forecasting financial returns," SFB 649 Discussion Papers 2008-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

Articles

  1. Pettenuzzo, Davide & Timmermann, Allan, 2011. "Predictability of stock returns and asset allocation under structural breaks," Journal of Econometrics, Elsevier, vol. 164(1), pages 60-78, September.

    Cited by:

    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Liming Chen & Zhi Zhang & Ziqing Du & Lingling Deng, 2021. "Heterogeneous determinants of the exchange rate market in China with structural breaks," Applied Economics, Taylor & Francis Journals, vol. 53(59), pages 6839-6854, December.
    3. Fabian Baetje & Lukas Menkhoff, 2016. "Equity Premium Prediction: Are Economic and Technical Indicators Unstable?," Discussion Papers of DIW Berlin 1552, DIW Berlin, German Institute for Economic Research.
    4. Senyuz, Zeynep, 2009. "Factor Analysis of Permanent and Transitory Dynamics of the U.S. Economy and the Stock Market," MPRA Paper 26855, University Library of Munich, Germany, revised Mar 2010.
    5. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    6. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    7. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    8. Nuno Silva, 2015. "Time-Varying Stock Return Predictability: The Eurozone Case," Notas Económicas, Faculty of Economics, University of Coimbra, issue 41, pages 28-38, June.
    9. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    10. Frydman, Roman & Goldberg, Michael D. & Mangee, Nicholas, 2015. "Knightian uncertainty and stock-price movements: Why the REH present-value model failed empirically," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-50.
    11. Avdis, Efstathios & Wachter, Jessica A., 2017. "Maximum likelihood estimation of the equity premium," Journal of Financial Economics, Elsevier, vol. 125(3), pages 589-609.
    12. Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
    13. Chen, Xiaoyu & Chiang, Thomas C., 2020. "Empirical investigation of changes in policy uncertainty on stock returns—Evidence from China’s market," Research in International Business and Finance, Elsevier, vol. 53(C).
    14. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    15. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    16. Harry J. Turtle & Chengping Zhang, 2015. "Structural breaks and portfolio performance in global equity markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 909-922, June.
    17. Dendramis, Yiannis & Kapetanios, George & Tzavalis, Elias, 2014. "Level shifts in stock returns driven by large shocks," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 41-51.
    18. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    19. Carlos Carvalho & Jared D. Fisher & Davide Pettenuzzo, 2018. "Optimal Asset Allocation with Multivariate Bayesian Dynamic Linear Models," Working Papers 123, Brandeis University, Department of Economics and International Business School.
    20. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    21. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
    22. Katrin Wölfel & Christoph S. Weber, 2017. "Searching for the Fed’s reaction function," Empirical Economics, Springer, vol. 52(1), pages 191-227, February.
    23. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    24. Yannick Hoga, 2024. "Persistence-Robust Break Detection in Predictive Quantile and CoVaR Regressions," Papers 2410.05861, arXiv.org.
    25. Chatzitzisi, Evanthia & Fountas, Stilianos & Panagiotidis, Theodore, 2021. "Another look at calendar anomalies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 823-840.
    26. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    27. Casas Villalba, Maria Isabel, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    28. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    29. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    30. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    31. Michael D. Goldberg & Olesia Kozlova & Deniz Ozabaci, 2020. "Forward Rate Bias in Developed and Developing Countries: More Risky Not Less Rational," Econometrics, MDPI, vol. 8(4), pages 1-26, December.
    32. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    33. Erik Hjalmarsson, 2008. "Predicting global stock returns," International Finance Discussion Papers 933, Board of Governors of the Federal Reserve System (U.S.).
    34. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    35. Goodarzi, Milad & Meinerding, Christoph, 2023. "Asset allocation with recursive parameter updating and macroeconomic regime identifiers," Discussion Papers 06/2023, Deutsche Bundesbank.
    36. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    37. Bart Diris & Franz Palm & Peter Schotman, 2015. "Long-Term Strategic Asset Allocation: An Out-of-Sample Evaluation," Management Science, INFORMS, vol. 61(9), pages 2185-2202, September.
    38. Roy P. P. M. Hoevenaars & Roderick D. J. Molenaar & Peter C. Schotman & Tom B. M. Steenkamp, 2014. "Strategic Asset Allocation For Long‐Term Investors: Parameter Uncertainty And Prior Information," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 353-376, April.
    39. Caroline Michere Ndei & Stephen Muchina & Kennedy Waweru, 2019. "Modeling stock market return volatility in the presence of structural breaks: Evidence from Nairobi Securities Exchange, Kenya," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 8(5), pages 156-171, September.
    40. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    41. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    42. Chen, Xiaoyu & Chiang, Thomas C., 2016. "Stock returns and economic forces—An empirical investigation of Chinese markets," Global Finance Journal, Elsevier, vol. 30(C), pages 45-65.
    43. Luo, Shikong & Yan, Xinyan & Yang, Haoyi, 2021. "Let’s take a smooth break: Stock return predictability revisited," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 300-314.
    44. Hollstein, Fabian & Prokopczuk, Marcel & Tharann, Björn & Wese Simen, Chardin, 2021. "Predictability in commodity markets: Evidence from more than a century," Journal of Commodity Markets, Elsevier, vol. 24(C).
    45. Seema Narayan & Russell Smyth, 2015. "The Financial Econometrics of Price Discovery and Predictability," Monash Economics Working Papers 06-15, Monash University, Department of Economics.
    46. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
    47. Roman Frydman & Soren Johansen & Anders Rahbek & Morten Nyboe Tabor, 2021. "Asset Prices Under Knightian Uncertainty," Working Papers Series inetwp172, Institute for New Economic Thinking.
    48. Markwat, T.D. & Kole, H.J.W.G. & van Dijk, D.J.C., 2009. "Time Variation in Asset Return Dependence: Strength or Structure?," ERIM Report Series Research in Management ERS-2009-052-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    49. Zhu, Xiaoneng & Zhu, Jie, 2013. "Predicting stock returns: A regime-switching combination approach and economic links," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4120-4133.
    50. Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018. "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 132-142.
    51. Xu, Ke-Li, 2013. "Powerful tests for structural changes in volatility," Journal of Econometrics, Elsevier, vol. 173(1), pages 126-142.
    52. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    53. Simon C. Smith, 2020. "Equity premium prediction and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 412-429, July.
    54. Bali, Turan G. & Demirtas, K. Ozgur & Levy, Haim, 2008. "Nonlinear mean reversion in stock prices," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 767-782, May.
    55. Zhang, Yugui & Zhu, Jie & Zhu, Xiaoneng, 2020. "Investing for the long run when expected equity premium is nonnegative," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    56. Zhu, Xiaoneng, 2013. "Perpetual learning and stock return predictability," Economics Letters, Elsevier, vol. 121(1), pages 19-22.
    57. Chen, Cathy Yi-Hsuan & Chiang, Thomas C. & Härdle, Wolfgang Karl, 2016. "Downside risk and stock returns: An empirical analysis of the long-run and short-run dynamics from the G-7 Countries," SFB 649 Discussion Papers 2016-001, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    58. Ravazzolo, F. & van Dijk, D.J.C. & Paap, R. & Franses, Ph.H.B.F., 2006. "Bayesian Model Averaging in the Presence of Structural Breaks," Econometric Institute Research Papers EI 2006-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    59. Focardi, Sergio M. & Fabozzi, Frank J. & Mazza, Davide, 2019. "Modeling local trends with regime shifting models with time-varying probabilities," International Review of Financial Analysis, Elsevier, vol. 66(C).
    60. Li, Chenxing, 2022. "A multivariate GARCH model with an infinite hidden Markov mixture," MPRA Paper 112792, University Library of Munich, Germany.
    61. Sensoy, Ahmet, 2013. "Dynamic relationship between precious metals," Resources Policy, Elsevier, vol. 38(4), pages 504-511.
    62. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," Journal of Econometrics, Elsevier, vol. 177(2), pages 357-373.
    63. Masahiko Egami & Yuki Shigeta & Katsutoshi Wakai, 2014. "The change of correlation structure across industries:an analysis in the regime-switching framework," Discussion papers e-14-002, Graduate School of Economics Project Center, Kyoto University.
    64. Chiang, Thomas C., 2019. "Economic policy uncertainty, risk and stock returns: Evidence from G7 stock markets," Finance Research Letters, Elsevier, vol. 29(C), pages 41-49.
    65. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    66. Cathy Yi†Hsuan Chen & Thomas C. Chiang, 2016. "Empirical Analysis of the Intertemporal Relationship between Downside Risk and Expected Returns: Evidence from Time†varying Transition Probability Models," European Financial Management, European Financial Management Association, vol. 22(5), pages 749-796, November.
    67. Luis A. Gil-Alana & Goodness C. Aye & Rangan Gupta, 2012. "Testing for Persistence with Breaks and Outliers in South African House Prices," Faculty Working Papers 20/12, School of Economics and Business Administration, University of Navarra.
    68. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    69. Bachmeier, Lance J. & Nadimi, Soheil R., 2018. "Oil shocks and stock return volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 1-9.
    70. Barras, Laurent, 2007. "International conditional asset allocation under specification uncertainty," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 443-464, September.
    71. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    72. Jiawen Xu & Pierre Perron, 2023. "Forecasting in the presence of in-sample and out-of-sample breaks," Empirical Economics, Springer, vol. 64(6), pages 3001-3035, June.
    73. Nuno Silva, 2015. "Industry based equity premium forecasts," GEMF Working Papers 2015-19, GEMF, Faculty of Economics, University of Coimbra.
    74. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
    75. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Equity Premia using Bayesian Dynamic Model Averaging," CQE Working Papers 2914, Center for Quantitative Economics (CQE), University of Muenster.

  2. Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2011. "Variable selection, estimation and inference for multi-period forecasting problems," Journal of Econometrics, Elsevier, vol. 164(1), pages 173-187, September.

    Cited by:

    1. Mario Porqueddu & Fabrizio Venditti, 2012. "Do food commodity prices have asymmetric effects on Euro-Area inflation?," Temi di discussione (Economic working papers) 878, Bank of Italy, Economic Research and International Relations Area.
    2. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    3. Kourentzes, Nikolaos & Trapero, Juan R. & Barrow, Devon K., 2020. "Optimising forecasting models for inventory planning," International Journal of Production Economics, Elsevier, vol. 225(C).
    4. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
    5. Y. Dendramis & G. Kapetanios & M. Marcellino, 2020. "A similarity‐based approach for macroeconomic forecasting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 801-827, June.
    6. Buncic, Daniel & Piras, Gion Donat, 2014. "Heterogeneous Agents, the Financial Crisis and Exchange Rate Predictability," Economics Working Paper Series 1436, University of St. Gallen, School of Economics and Political Science, revised Oct 2015.
    7. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2017. "The transmission of monetary policy shocks," Bank of England working papers 657, Bank of England.
    8. Tanya Araujo & João Dias & Samuel Eleutério & Francisco Louçã, 2012. "How Fama Went Wrong: Measures of Multivariate Kurtosis for the Identification of the Dynamics of a N-Dimensional Market," Working Papers Department of Economics 2012/21, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    9. International Monetary Fund, 2012. "Short-Term Wholesale Funding and Systemic Risk: A Global Covar Approach," IMF Working Papers 2012/046, International Monetary Fund.
    10. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High Dimensional Vector Autoregressive Models," CEIS Research Paper 534, Tor Vergata University, CEIS, revised 24 Mar 2022.
    11. Fabricio Tourrucôo & João F. Caldeira & Guilherme V. Moura & André A. P. Santos, 2016. "Forecasting The Yield Curve With The Arbitrage-Free Dynamic Nelson-Siegel Model: Brazilian Evidence," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 028, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    12. Boriss Siliverstovs & Daniel Wochner, 2019. "Recessions as Breadwinner for Forecasters State-Dependent Evaluation of Predictive Ability: Evidence from Big Macroeconomic US Data," KOF Working papers 19-463, KOF Swiss Economic Institute, ETH Zurich.
    13. Cheng, Xu & Hansen, Bruce E., 2015. "Forecasting with factor-augmented regression: A frequentist model averaging approach," Journal of Econometrics, Elsevier, vol. 186(2), pages 280-293.
    14. Mikkel Plagborg-Møller & Christian K. Wolf, 2020. "Local Projections and VARs Estimate the Same Impulse Responses," Working Papers 2020-16, Princeton University. Economics Department..
    15. Sultan Mehmood, 2014. "Terrorism and the macroeconomy: Evidence from Pakistan," Defence and Peace Economics, Taylor & Francis Journals, vol. 25(5), pages 509-534, October.
    16. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
    17. Kohei Maehashi & Mototsugu Shintani, 2020. "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series CIRJE-F-1146, CIRJE, Faculty of Economics, University of Tokyo.
    18. Tanya Ara'ujo & Jo~ao Dias & Samuel Eleut'erio & Francisco Louc{c}~a, 2012. "How Fama Went Wrong: Measures of Multivariate Kurtosis for the Identification of the Dynamics of a N-Dimensional Market," Papers 1207.1202, arXiv.org.
    19. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    20. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    21. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
    22. Buncic, Daniel & Gisler, Katja I. M., 2015. "Global Equity Market Volatility Spillovers: A Broader Role for the United States," Economics Working Paper Series 1508, University of St. Gallen, School of Economics and Political Science.
    23. Hou, Linke & Lv, Yuxia & Geng, Hao & Li, Feiyue, 2019. "To tell the truth or the perceived truth: Structural estimation of peer effects in China’s macroeconomic forecast," Economic Systems, Elsevier, vol. 43(2), pages 1-1.
    24. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    25. Kim, Hyun Hak & Swanson, Norman R., 2014. "Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence," Journal of Econometrics, Elsevier, vol. 178(P2), pages 352-367.
    26. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric Model Averaging of Ultra-High Dimensional Time Series," Discussion Papers 15/18, Department of Economics, University of York.
    27. Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
    28. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    29. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
    30. Germán López-Espinosa & Antonio Moreno & Antonio Rubia & Laura Valderrama, 2012. "Short-term Wholesale Funding and Systemic Risk: A Global CoVaR Approach," Faculty Working Papers 02/12, School of Economics and Business Administration, University of Navarra.
    31. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.
    32. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    33. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, Department of Economics and Business Economics, Aarhus University.
    34. Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version," PIER Working Paper Archive 13-061, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Sep 2013.
    35. Boudoukh, Jacob & Israel, Ronen & Richardson, Matthew, 2022. "Biases in long-horizon predictive regressions," Journal of Financial Economics, Elsevier, vol. 145(3), pages 937-969.
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  3. Issler, João Victor & Linton, Oliver & Timmermann, Allan, 2011. "Annals issue on forecasting--Guest editors' introduction," Journal of Econometrics, Elsevier, vol. 164(1), pages 1-3, September.

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    1. Mikkel Plagborg-Møller & Christian K. Wolf, 2020. "Local Projections and VARs Estimate the Same Impulse Responses," Working Papers 2020-16, Princeton University. Economics Department..

  4. Patton, Andrew J. & Timmermann, Allan, 2011. "Predictability of Output Growth and Inflation: A Multi-Horizon Survey Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 397-410.

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    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Camba-Méndez, Gonzalo & Werner, Thomas, 2017. "The inflation risk premium in the post-Lehman period," Working Paper Series 2033, European Central Bank.
    3. Hecq, Alain & Jacobs, Jan P.A.M. & Stamatogiannis, Michalis P., 2019. "Testing for news and noise in non-stationary time series subject to multiple historical revisions," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 396-407.
    4. Atalla, Tarek & Joutz, Fred & Pierru, Axel, 2016. "Does disagreement among oil price forecasters reflect volatility? Evidence from the ECB surveys," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1178-1192.
    5. Burban, Valentin & De Backer, Bruno & Vladu, Andreea Liliana, 2024. "Inflation (de-)anchoring in the euro area," Working Paper Series 2964, European Central Bank.
    6. Beckmann, Joscha & Czudaj, Robert L., 2020. "Fundamental determinants of exchange rate expectations," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224617, Verein für Socialpolitik / German Economic Association.
    7. Marcela De Castro-Valderrama & Santiago Forero-Alvarado & Nicolás Moreno-Arias & Sara Naranjo-Saldarriaga, 2021. "Unraveling the Exogenous Forces Behind Analysts’ Macroeconomic Forecasts," Borradores de Economia 1184, Banco de la Republica de Colombia.
    8. Beckmann, Joscha & Czudaj, Robert L. & Murach, Michael, 2024. "Macroeconomic Effects from Media Coverage of the China-U.S. Trade War on selected EU Countries," MPRA Paper 121751, University Library of Munich, Germany.
    9. Qu, Ritong & Timmermann, Allan & Zhu, Yinchu, 2024. "Comparing forecasting performance with panel data," International Journal of Forecasting, Elsevier, vol. 40(3), pages 918-941.
    10. Czudaj, Robert & Beckmann, Joscha, 2018. "Monetary policy shocks, expectations and information rigidities," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181573, Verein für Socialpolitik / German Economic Association.
    11. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024. "Constructing fan charts from the ragged edge of SPF forecasts," Working Papers 2429, Banco de España.
    12. Meade, Nigel & Driver, Ciaran, 2023. "Differing behaviours of forecasters of UK GDP growth," International Journal of Forecasting, Elsevier, vol. 39(2), pages 772-790.
    13. Bruno Deschamps & Christos Ioannidis, 2014. "The Efficiency of Multivariate Macroeconomic Forecasts," Manchester School, University of Manchester, vol. 82(5), pages 509-523, September.
    14. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Inflation fan charts, monetary policy and skew normal distribution," Discussion Papers in Economics 13/06, Division of Economics, School of Business, University of Leicester.
    15. William A. Branch, 2014. "Nowcasting and the Taylor Rule," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(5), pages 1035-1055, August.
    16. Robert L. Czudaj, 2019. "Is the negative interest rate policy effective?," Chemnitz Economic Papers 034, Department of Economics, Chemnitz University of Technology, revised Dec 2019.
    17. Andrew J. Patton & Allan Timmermann, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-17, June.
    18. Bennett Schmanski & Chiara Scotti & Clara Vega, 2023. "Fed Communication, News, Twitter, and Echo Chambers," Finance and Economics Discussion Series 2023-036, Board of Governors of the Federal Reserve System (U.S.).
    19. Valentin Burban & Bruno De Backer & Andreea Liliana Vladu, 2024. "Inflation (De-)Anchoring in the Euro Area," Working papers 965, Banque de France.
    20. Clements, Michael P. & Galvão, Ana Beatriz, 2017. "Model and survey estimates of the term structure of US macroeconomic uncertainty," International Journal of Forecasting, Elsevier, vol. 33(3), pages 591-604.
    21. Feunou Bruno & Fontaine Jean-Sébastien & Jin Jianjian, 2021. "What model for the target rate," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(1), pages 1-23, February.
    22. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    23. Clements, Michael P., 2012. "Subjective and Ex Post Forecast Uncertainty: US Inflation and Output Growth," Economic Research Papers 270629, University of Warwick - Department of Economics.
    24. Joscha Beckmann & Robert L. Czudaj, 2023. "The role of expectations for currency crisis dynamics—The case of the Turkish lira," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 625-642, April.
    25. Michele Bernardi & Jaqueson K. Galimberti, 2014. "A Note on the Representative Adaptive Learning Algorithm," KOF Working papers 14-356, KOF Swiss Economic Institute, ETH Zurich.
    26. Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, University of Reading.
    27. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
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    30. Dybowski, T. Philipp & Kempa, Bernd, 2020. "The European Central Bank’s monetary pillar after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 121(C).
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    32. Busetto, Filippo, 2024. "Asymmetric expectations of monetary policy," Bank of England working papers 1058, Bank of England.
    33. Joscha Beckmann & Robert L. Czudaj, 2020. "Professional forecasters' expectations, consistency, and international spillovers," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1001-1024, November.
    34. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The University of Manchester.
    35. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.

  5. Aiolfi, Marco & Catão, Luis A.V. & Timmermann, Allan, 2011. "Common factors in Latin America's business cycles," Journal of Development Economics, Elsevier, vol. 95(2), pages 212-228, July.
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  6. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.

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    1. Park, Sunjin, 2022. "Heterogeneous beliefs in macroeconomic growth prospects and the carry risk premium," Journal of Banking & Finance, Elsevier, vol. 136(C).
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    3. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    4. Atalla, Tarek & Joutz, Fred & Pierru, Axel, 2016. "Does disagreement among oil price forecasters reflect volatility? Evidence from the ECB surveys," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1178-1192.
    5. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    6. Michael D. Bauer & Carolin Pflueger & Adi Sunderam, 2023. "Perceptions about Monetary Policy," Working Paper Series 2023-31, Federal Reserve Bank of San Francisco.
    7. Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," Bank of Israel Working Papers 2020.11, Bank of Israel.
    8. Maiko Koga & Haruko Kato, 2017. "Behavioral Biases in Firms' Growth Expectations," Bank of Japan Working Paper Series 17-E-9, Bank of Japan.
    9. Richard K. Crump & Stefano Eusepi & Emanuel Moench, 2016. "The term structure of expectations and bond yields," Staff Reports 775, Federal Reserve Bank of New York.
    10. Osnat Zohar, 2021. "Cyclicality of Uncertainty and Disagreement," Bank of Israel Working Papers 2021.09, Bank of Israel.
    11. Cordeiro, Yara de Almeida Campos & Gaglianone, Wagner Piazza & Issler, João Victor, 2016. "Inattention in individual expectations," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 776, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    12. Andrew C. Chang & Trace J. Levinson, 2023. "Raiders of the lost high‐frequency forecasts: New data and evidence on the efficiency of the Fed's forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 88-104, January.
    13. Coibion, Olivier & Gorodnichenko, Yuriy & Kumar, Saten & Ryngaert, Jane, 2021. "Do You Know that I Know that You Know…? Higher-Order Beliefs in Survey Data," Department of Economics, Working Paper Series qt5cd1r3bd, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    14. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
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    17. Marcela De Castro-Valderrama & Santiago Forero-Alvarado & Nicolás Moreno-Arias & Sara Naranjo-Saldarriaga, 2021. "Unraveling the Exogenous Forces Behind Analysts’ Macroeconomic Forecasts," Borradores de Economia 1184, Banco de la Republica de Colombia.
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    56. Xiang, Ju & Zhu, Xiaoneng, 2014. "Intraday asymmetric liquidity and asymmetric volatility in FTSE-100 futures market," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 134-148.
    57. Hoechle, Daniel & Schmid, Markus & Zimmermann, Heinz, 2017. "Does Unobservable Heterogeneity Matter for Portfolio-Based Asset Pricing Tests?," Working Papers on Finance 1717, University of St. Gallen, School of Finance, revised Mar 2020.
    58. Kazuhiro Hiraki & George Skiadopoulos, 2023. "The Contribution of Transaction Costs to Expected Stock Returns: A Novel Measure," Working Papers 946, Queen Mary University of London, School of Economics and Finance.
    59. Zaremba, Adam & Bianchi, Robert J. & Mikutowski, Mateusz, 2021. "Long-run reversal in commodity returns: Insights from seven centuries of evidence," Journal of Banking & Finance, Elsevier, vol. 133(C).
    60. Adam Zaremba, 2016. "Has the Long-Term Reversal Reversed? Evidence from Country Equity Indices," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 88-103, March.
    61. Zaremba, Adam & Szyszka, Adam & Karathanasopoulos, Andreas & Mikutowski, Mateusz, 2021. "Herding for profits: Market breadth and the cross-section of global equity returns," Economic Modelling, Elsevier, vol. 97(C), pages 348-364.
    62. Malamud, Semyon & Vilkov, Grigory, 2018. "Non-myopic betas," Journal of Financial Economics, Elsevier, vol. 129(2), pages 357-381.
    63. Timmermann, Allan & Lunde, Asger & Groenborg, Niels & Wermers, Russ, 2017. "Picking Funds with Confidence," CEPR Discussion Papers 11896, C.E.P.R. Discussion Papers.
    64. Klinkowska, Olga & Zhao, Yuan, 2023. "Fund flows and performance: New evidence from retail and institutional SRI mutual funds," International Review of Financial Analysis, Elsevier, vol. 87(C).
    65. Nuno Clara, 2018. "Demand Elasticities, Nominal Rigidities and Asset Prices," 2018 Meeting Papers 790, Society for Economic Dynamics.
    66. Klein, Tobias J. & Salm, Martin & Upadhyay, Suraj, 2022. "The response to dynamic incentives in insurance contracts with a deductible: Evidence from a differences-in-regression-discontinuities design," Journal of Public Economics, Elsevier, vol. 210(C).
    67. Terence Tai-Leung Chong & Sunny Chun Tsui & Wing Hong Chan, 2017. "Factor pricing in commodity futures and the role of liquidity," Quantitative Finance, Taylor & Francis Journals, vol. 17(11), pages 1745-1757, November.
    68. Zaremba, Adam & Kizys, Renatas & Raza, Muhammad Wajid, 2020. "The long-run reversal in the long run: Insights from two centuries of international equity returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 177-199.
    69. Patton, Andrew J. & Weller, Brian M., 2020. "What you see is not what you get: The costs of trading market anomalies," Journal of Financial Economics, Elsevier, vol. 137(2), pages 515-549.
    70. Richard D. F. Harris & Xuguang Li & Fang Qiao, 2019. "Option‐implied betas and the cross section of stock returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 94-108, January.
    71. Huang, Huichou & MacDonald, Ronald & Zhao, Yang, 2012. "Global Currency Misalignments, Crash Sensitivity, and Downside Insurance Costs," MPRA Paper 53745, University Library of Munich, Germany, revised 18 Nov 2013.
    72. Vintilă Georgeta & Păunescu Radu Alin, 2015. "Econometric Tests of the CAPM Model for a Portfolio Composed of Companies Listed on Nasdaq and Dow Jones Components," Scientific Annals of Economics and Business, Sciendo, vol. 62(3), pages 453-480, November.
    73. Zaremba, Adam & Czapkiewicz, Anna, 2017. "The cross section of international government bond returns," Economic Modelling, Elsevier, vol. 66(C), pages 171-183.
    74. Smith, Simon C. & Timmermann, Allan, 2022. "Have risk premia vanished?," Journal of Financial Economics, Elsevier, vol. 145(2), pages 553-576.
    75. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    76. Adam Zaremba, 2017. "Combining Equity Country Selection Strategies," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 11(1), March.
    77. Waszczuk, Antonina, 2013. "A risk-based explanation of return patterns—Evidence from the Polish stock market," Emerging Markets Review, Elsevier, vol. 15(C), pages 186-210.
    78. Eriksen, Jonas N., 2019. "Cross-sectional return dispersion and currency momentum," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 91-108.
    79. Zaremba, Adam & Mikutowski, Mateusz & Szczygielski, Jan Jakub & Karathanasopoulos, Andreas, 2021. "The alpha momentum effect in commodity markets," Energy Economics, Elsevier, vol. 93(C).
    80. Lukas Mankhoff & Lucio Sarno & Maik Schmeling & Andreas Schrimpf, 2013. "Information flows in foreign exchange markets: dissecting customer currency trades," BIS Working Papers 405, Bank for International Settlements.
    81. Anarkulova, Aizhan & Cederburg, Scott & O’Doherty, Michael S., 2022. "Stocks for the long run? Evidence from a broad sample of developed markets," Journal of Financial Economics, Elsevier, vol. 143(1), pages 409-433.
    82. Ahmad, Fawad & Oriani, Raffaele, 2022. "Investor attention, information acquisition, and value premium: A mispricing perspective," International Review of Financial Analysis, Elsevier, vol. 79(C).
    83. Victor Sellemi, 2022. "Risk in Network Economies," Papers 2208.01467, arXiv.org.
    84. Ornelas, José Renato Haas, 2016. "The Forecast Ability of Option-implied Densities from Emerging Markets Currencies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(1), March.
    85. Koerniadi, Hardjo & Krishnamurti, Chandrasekhar & Lau, Sie Ting & Tourani-Rad, Alireza & Yang, Ting, 2015. "The role of internal and external certification mechanisms in seasoned equity offerings," Journal of Multinational Financial Management, Elsevier, vol. 30(C), pages 110-127.
    86. Zaremba, Adam, 2019. "Price range and the cross-section of expected country and industry returns," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 174-189.
    87. Kharrat, Sabrine & Hammami, Yacine & Fatnassi, Ibrahim, 2020. "On the cross-sectional relation between exchange rates and future fundamentals," Economic Modelling, Elsevier, vol. 89(C), pages 484-501.
    88. Kim, Junyong, 2024. "Zoom in on momentum," International Review of Financial Analysis, Elsevier, vol. 94(C).
    89. Romano, Joseph P. & Wolf, Michael, 2013. "Testing for monotonicity in expected asset returns," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 93-116.
    90. Zaremba, Adam & Cakici, Nusret & Bianchi, Robert J. & Long, Huaigang, 2023. "Interest rate changes and the cross-section of global equity returns," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    91. Zaremba, Adam & Maydybura, Alina, 2019. "The cross-section of returns in frontier equity markets: Integrated or segmented pricing?," Emerging Markets Review, Elsevier, vol. 38(C), pages 219-238.

  8. Marco Aiolfi & Marius Rodriguez & Allan Timmermann, 2010. "Understanding Analysts' Earnings Expectations: Biases, Nonlinearities, and Predictability," Journal of Financial Econometrics, Oxford University Press, vol. 8(3), pages 305-334, Summer.
    See citations under working paper version above.
  9. Carlos Capistr¡N & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 365-396, March.
    See citations under working paper version above.
  10. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    See citations under working paper version above.
  11. Pesaran, M. Hashem & Timmermann, Allan, 2009. "Testing Dependence Among Serially Correlated Multicategory Variables," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 325-337.
    See citations under working paper version above.
  12. Guidolin, Massimo & Timmermann, Allan, 2009. "Forecasts of US short-term interest rates: A flexible forecast combination approach," Journal of Econometrics, Elsevier, vol. 150(2), pages 297-311, June.
    See citations under working paper version above.
  13. Timmermann, Allan, 2008. "Reply to the discussion of Elusive Return Predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 29-30.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Fabian Baetje & Lukas Menkhoff, 2016. "Equity Premium Prediction: Are Economic and Technical Indicators Unstable?," Discussion Papers of DIW Berlin 1552, DIW Berlin, German Institute for Economic Research.
    3. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    4. Alexandru Todea & Andrei Rusu, 2014. "Liquidity, information and market efficiency: an intraday approach on a frontier stock market," Economics Bulletin, AccessEcon, vol. 34(4), pages 2303-2307.
    5. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    6. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    7. Yi-Chieh Wen & Bin Li, 2020. "Lagged country returns and international stock return predictability during business cycle recession periods," Applied Economics, Taylor & Francis Journals, vol. 52(46), pages 5005-5019, October.
    8. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    9. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    10. Nicolas S. Magner & Nicolás Hardy & Tiago Ferreira & Jaime F. Lavin, 2023. "“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    11. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    12. Andrew Detzel & Jack Strauss, 2018. "Combination Return Forecasts and Portfolio Allocation with the Cross-Section of Book-to-Market Ratios [Illiquidity and stock returns: cross-section and time-series effects]," Review of Finance, European Finance Association, vol. 22(5), pages 1949-1973.
    13. Georgiev, I & Harvey, DI & Leybourne, SJ & Taylor, AM, 2018. "Testing for Parameter Instability in Predictive Regression Models," Essex Finance Centre Working Papers 21162, University of Essex, Essex Business School.
    14. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    15. Larry W. Taylor, 2009. "Penalized‐R2 Criteria For Model Selection," Manchester School, University of Manchester, vol. 77(6), pages 699-717, December.
    16. Pönkä, Harri, 2014. "Predicting the direction of US stock markets using industry returns," MPRA Paper 62942, University Library of Munich, Germany.
    17. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    18. Roberto Gómez‐Cram, 2022. "Late to Recessions: Stocks and the Business Cycle," Journal of Finance, American Finance Association, vol. 77(2), pages 923-966, April.
    19. Taylor, Mark & Hsu, Po-Hsuan & Wang, Zigan, 2020. "The Out-of-Sample Performance of Carry Trades," CEPR Discussion Papers 15052, C.E.P.R. Discussion Papers.
    20. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    21. Leopoldo Catania & Anna Gloria Billé, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," CEIS Research Paper 375, Tor Vergata University, CEIS, revised 31 Mar 2016.
    22. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    23. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.
    24. Daniel Mantilla-García & Vijay Vaidyanathan, 2017. "Predicting stock returns in the presence of uncertain structural changes and sample noise," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 357-391, August.
    25. David G. McMillan, 2017. "Stock return predictability: the role of inflation and threshold dynamics," International Review of Applied Economics, Taylor & Francis Journals, vol. 31(3), pages 357-375, May.
    26. Massimo Guidolin & Manuela Pedio & Milena Petrova, 2019. "The Predictability of Real Estate Excess Returns: An Out-of-Sample Economic Value Analysis," BAFFI CAREFIN Working Papers 19122, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    27. Massacci, Daniele, 2017. "Least squares estimation of large dimensional threshold factor models," Journal of Econometrics, Elsevier, vol. 197(1), pages 101-129.
    28. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    29. Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
    30. Jean-Yves Pitarakis, 2017. "A Simple Approach for Diagnosing Instabilities in Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 851-874, October.
    31. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    32. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    33. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    34. Tang, Chor Foon & Lai, Yew Wah & Ozturk, Ilhan, 2015. "How stable is the export-led growth hypothesis? Evidence from Asia's Four Little Dragons," Economic Modelling, Elsevier, vol. 44(C), pages 229-235.
    35. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
    36. Giulia Dal Pra & Massimo Guidolin & Manuela Pedio & Fabiola Vasile, 2016. "Do Regimes in Excess Stock Return Predictability Create Economic Value? An Out-of-Sample Portfolio Analysis," BAFFI CAREFIN Working Papers 1637, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    37. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    38. Guillaume Belly & Lukas Boeckelmann & Carlos Mateo Caicedo Graciano & Alberto Di Iorio & Klodiana Istrefi & Vasileios Siakoulis & Arthur Stalla-Bourdillon, 2023. "Forecasting sovereign risk in the Euro area via machine learning," Post-Print hal-04459577, HAL.
    39. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    40. Jonathan Iworiso & Spyridon Vrontos, 2020. "On the directional predictability of equity premium using machine learning techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 449-469, April.
    41. Nicolás Magner & Jaime F. Lavín & Mauricio A. Valle, 2022. "Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach," Mathematics, MDPI, vol. 10(19), pages 1-30, October.
    42. Shailesh Rana & William H. Bommer & G. Michael Phillips, 2020. "Predicting Returns for Growth and Value Stocks: A Forecast Assessment Approach Using Global Asset Pricing Models," International Journal of Economics and Financial Issues, Econjournals, vol. 10(4), pages 88-106.
    43. Marta Matyjaszek & Gregorio Fidalgo Valverde & Alicja Krzemień & Krzysztof Wodarski & Pedro Riesgo Fernández, 2020. "Optimizing Predictor Variables in Artificial Neural Networks When Forecasting Raw Material Prices for Energy Production," Energies, MDPI, vol. 13(8), pages 1-15, April.
    44. Salah Abosedra & Chor Foon Tang, 2019. "Are exports a reliable source of economic growth in MENA countries? New evidence from the rolling Granger causality method," Empirical Economics, Springer, vol. 56(3), pages 831-841, March.
    45. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
    46. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    47. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    48. I. Marta Miranda García & María‐Jesús Segovia‐Vargas & Usue Mori & José A. Lozano, 2023. "Early prediction of Ibex 35 movements," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1150-1166, August.
    49. Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
    50. Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
    51. Pincheira, Pablo & Hardy, Nicolas, 2020. "The Mean Squared Prediction Error Paradox: A summary," MPRA Paper 105020, University Library of Munich, Germany.
    52. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
    53. Chor Foon Tang & Eu Chye Tan, 2017. "Re-visiting the Savings-Led Growth Hypothesis and Its Stability in East Asian Economies," International Economic Journal, Taylor & Francis Journals, vol. 31(3), pages 436-447, July.
    54. Jurdi, Doureige J., 2022. "Predicting the Australian equity risk premium," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    55. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    56. McMillan, David G., 2019. "Stock return predictability: Using the cyclical component of the price ratio," Research in International Business and Finance, Elsevier, vol. 48(C), pages 228-242.
    57. David I. Harvey & Stephen J. Leybourne & Robert Sollis & A.M. Robert Taylor, 2021. "Real‐time detection of regimes of predictability in the US equity premium," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 45-70, January.
    58. Chor Foon Tang & Salah Abosedra, 2016. "Tourism and growth in Lebanon: new evidence from bootstrap simulation and rolling causality approaches," Empirical Economics, Springer, vol. 50(2), pages 679-696, March.
    59. Afsaneh Bahrami & Abul Shamsuddin & Katherine Uylangco, 2018. "Out‐of‐sample stock return predictability in emerging markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(3), pages 727-750, September.
    60. McMillan, David G., 2019. "Predicting firm level stock returns: Implications for asset pricing and economic links," The British Accounting Review, Elsevier, vol. 51(4), pages 333-351.
    61. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    62. Ellie Birbeck & Dave Cliff, 2018. "Using Stock Prices as Ground Truth in Sentiment Analysis to Generate Profitable Trading Signals," Papers 1811.02886, arXiv.org.
    63. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
    64. Jian Zhou & Jin Man Lee, 2013. "Adaptive market hypothesis: evidence from the REIT market," Applied Financial Economics, Taylor & Francis Journals, vol. 23(21), pages 1649-1662, November.

  14. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    See citations under working paper version above.
  15. Massimo Guidolin & Allan Timmermann, 2008. "Size and Value Anomalies under Regime Shifts," Journal of Financial Econometrics, Oxford University Press, vol. 6(1), pages 1-48, Winter.

    Cited by:

    1. Alexandros Kontonikas & Alexandros Kostakis, 2013. "On Monetary Policy and Stock Market Anomalies," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 40(7-8), pages 1009-1042, September.
    2. Argyropoulos, Christos & Candelon, Bertrand & Hasse, Jean-Baptiste & Panopoulou, Ekaterini, 2020. "Toward a macroprudential regulatory framework for mutual funds," LIDAM Discussion Papers LFIN 2020008, Université catholique de Louvain, Louvain Finance (LFIN).
    3. Massimo Guidolin & Allan Timmerman, 2006. "Asset allocation under multivariate regime switching," Working Papers 2005-002, Federal Reserve Bank of St. Louis.
    4. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    5. Turtle, H.J. & Zhang, Chengping, 2012. "Time-varying performance of international mutual funds," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 334-348.
    6. Jinjarak, Yothin, 2014. "Equity prices and financial globalization," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 49-57.
    7. Massimo Guidolin & Giovanna Nicodano, 2007. "Managing international portfolios with small capitalization stocks," Working Papers 2007-030, Federal Reserve Bank of St. Louis.
    8. Mendes, Fernando Henrique de Paula e Silva & Caldeira, João Frois & Moura, Guilherme Valle, 2018. "Evidence of Bull and Bear Markets in the Bovespa index: An application of Markovian regime-switching Models with Duration Dependence," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(1), May.
    9. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    10. Massimo Guidolin & Federica Ria, 2010. "Regime shifts in mean-variance efficient frontiers: some international evidence," Working Papers 2010-040, Federal Reserve Bank of St. Louis.
    11. Carol Alexander & Anca Dimitriu, 2005. "Detecting Switching Strategies in Equity Hedge Funds," ICMA Centre Discussion Papers in Finance icma-dp2005-07, Henley Business School, University of Reading.
    12. Massimo Guidolin & Giovanna Nicodano, 2009. "Small caps in international equity portfolios: the effects of variance risk," Annals of Finance, Springer, vol. 5(1), pages 15-48, January.
    13. Chih-Nan Chen & Chien-Hsiu Lin, 2022. "Optimal carry trade portfolio choice under regime shifts," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 483-506, August.
    14. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2010. "1/N and long run optimal portfolios: results for mixed asset menus," Working Papers 2010-003, Federal Reserve Bank of St. Louis.
    15. Guidolin, Massimo & Hyde, Stuart, 2012. "Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 695-716.
    16. Yizhan Shu & John M. Mulvey, 2024. "Dynamic Factor Allocation Leveraging Regime-Switching Signals," Papers 2410.14841, arXiv.org.
    17. Francesco Chincoli & Massimo Guidolin, 2017. "Linear and nonlinear predictability in investment style factors: multivariate evidence," Journal of Asset Management, Palgrave Macmillan, vol. 18(6), pages 476-509, October.
    18. Lioui, Abraham & Tarelli, Andrea, 2020. "Factor Investing for the Long Run," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    19. Raeid Saqur, 2024. "What Teaches Robots to Walk, Teaches Them to Trade too -- Regime Adaptive Execution using Informed Data and LLMs," Papers 2406.15508, arXiv.org.
    20. Pettenuzzo, Davide & Timmermann, Allan, 2011. "Predictability of stock returns and asset allocation under structural breaks," Journal of Econometrics, Elsevier, vol. 164(1), pages 60-78, September.
    21. Azamat Abdymomunov, 2013. "Regime-switching measure of systemic financial stress," Annals of Finance, Springer, vol. 9(3), pages 455-470, August.
    22. Yoldas Emre, 2012. "Threshold Asymmetries in Equity Return Distributions: Statistical Tests and Investment Implications," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(5), pages 1-37, December.
    23. Campani, Carlos Heitor & Garcia, René & Lewin, Marcelo, 2021. "Optimal portfolio strategies in the presence of regimes in asset returns," Journal of Banking & Finance, Elsevier, vol. 123(C).
    24. Erdemlioglu, Deniz & Joliet, Robert, 2019. "Long-term asset allocation, risk tolerance and market sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 1-19.
    25. Carmine Trecroci, 2010. "Multifactors risk loadings and abnormal returns under uncertainty and learning," Working Papers 1011, University of Brescia, Department of Economics.
    26. Elizabeth Fons & Paula Dawson & Jeffrey Yau & Xiao-jun Zeng & John Keane, 2019. "A novel dynamic asset allocation system using Feature Saliency Hidden Markov models for smart beta investing," Papers 1902.10849, arXiv.org.
    27. Urga, Giovanni & Wang, Fa, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," MPRA Paper 117012, University Library of Munich, Germany, revised 10 Apr 2023.
    28. Huseyin Gulen & Yuhang Xing & Lu Zhang, 2011. "Value versus Growth: Time‐Varying Expected Stock Returns," Financial Management, Financial Management Association International, vol. 40(2), pages 381-407, June.
    29. Massimo Guidolin, 2013. "Markov switching models in asset pricing research," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 1, pages 3-44, Edward Elgar Publishing.
    30. Hwang, Soosung & Rubesam, Alexandre, 2013. "A behavioral explanation of the value anomaly based on time-varying return reversals," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2367-2377.
    31. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2015. "Equally Weighted vs. Long†Run Optimal Portfolios," European Financial Management, European Financial Management Association, vol. 21(4), pages 742-789, September.
    32. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
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    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
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    5. Schrimpf, Andreas, 2008. "International Stock Return Predictability Under Model Uncertainty," ZEW Discussion Papers 08-048, ZEW - Leibniz Centre for European Economic Research.
    6. Alexandru Todea & Andrei Rusu, 2014. "Liquidity, information and market efficiency: an intraday approach on a frontier stock market," Economics Bulletin, AccessEcon, vol. 34(4), pages 2303-2307.
    7. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
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    51. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
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    60. Marta Matyjaszek & Gregorio Fidalgo Valverde & Alicja Krzemień & Krzysztof Wodarski & Pedro Riesgo Fernández, 2020. "Optimizing Predictor Variables in Artificial Neural Networks When Forecasting Raw Material Prices for Energy Production," Energies, MDPI, vol. 13(8), pages 1-15, April.
    61. Salah Abosedra & Chor Foon Tang, 2019. "Are exports a reliable source of economic growth in MENA countries? New evidence from the rolling Granger causality method," Empirical Economics, Springer, vol. 56(3), pages 831-841, March.
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    63. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
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    66. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
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    72. Ravi Kashyap, 2024. "The Blockchain Risk Parity Line: Moving From The Efficient Frontier To The Final Frontier Of Investments," Papers 2407.09536, arXiv.org.
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    Cited by:

    1. Noori, Mohammad, 2024. "Stock-oil comovements through fear, uncertainty, and expectations: Evidence from conditional comoments," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 529-551.
    2. Fischer, Andreas M. & Greminger, Rafael P. & Grisse, Christian & Kaufmann, Sylvia, 2021. "Portfolio rebalancing in times of stress," Journal of International Money and Finance, Elsevier, vol. 113(C).
    3. Thomas Conlon & John Cotter & Chenglu Jin, 2019. "Co-skewness across Return Horizons," Working Papers 201910, Geary Institute, University College Dublin.
    4. Escobar-Anel, Marcos & Spies, Ben & Zagst, Rudi, 2024. "Mean–variance optimization under affine GARCH: A utility-based solution," Finance Research Letters, Elsevier, vol. 59(C).
    5. Wu, Bo & Li, Lingfei, 2024. "Reinforcement learning for continuous-time mean-variance portfolio selection in a regime-switching market," Journal of Economic Dynamics and Control, Elsevier, vol. 158(C).
    6. Fabio C. Bagliano & Carolina Fugazza & Giovanna Nicodano, 2017. "A Life-Cycle Model with Unemployment Traps," Carlo Alberto Notebooks 514, Collegio Carlo Alberto, revised 2019.
      • Fabio C. Bagliano & Carolina Fugazza & Giovanna Nicodano, 2017. "A Life-Cycle Model with Unemployment Traps," Working papers 041, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    7. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2024.
    8. Guidolin, Massimo & Liu, Hening, 2016. "Ambiguity Aversion and Underdiversification," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1297-1323, August.
    9. Donatien Hainaut & Griselda Deelstra, 2019. "A Bivariate Mutually-Excited Switching Jump Diffusion (BMESJD) for Asset Prices," Methodology and Computing in Applied Probability, Springer, vol. 21(4), pages 1337-1375, December.
    10. Konermann, Patrick & Meinerding, Christoph & Sedova, Olga, 2013. "Asset allocation in markets with contagion: The interplay between volatilities, jump intensities, and correlations," Review of Financial Economics, Elsevier, vol. 22(1), pages 36-46.
    11. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    12. Ai, Hengjie & Han, Leyla Jianyu & Pan, Xuhui Nick & Xu, Lai, 2022. "The cross section of the monetary policy announcement premium," Journal of Financial Economics, Elsevier, vol. 143(1), pages 247-276.
    13. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    14. John M Maheu & Thomas H McCurdy & Yong Song, 2009. "Extracting bull and bear markets from stock returns," Working Papers tecipa-369, University of Toronto, Department of Economics.
    15. Massimo Guidolin & Stuart Hyde, 2009. "What tames the Celtic Tiger? Portfolio implications from a Multivariate Markov Switching model," Applied Financial Economics, Taylor & Francis Journals, vol. 19(6), pages 463-488.
    16. Turtle, H.J. & Zhang, Chengping, 2012. "Time-varying performance of international mutual funds," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 334-348.
    17. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    18. Nicole Branger & Holger Kraft & Christoph Meinerding, 2009. "What is the Impact of Stock Market Contagion on an Investor's Portfolio Choice?," Working Paper Series: Finance and Accounting 198, Department of Finance, Goethe University Frankfurt am Main.
    19. Chen, Ke & Vitiello, Luiz & Hyde, Stuart & Poon, Ser-Huang, 2018. "The reality of stock market jumps diversification," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 171-188.
    20. Lambert, Philippe & Laurent, Sébastien & Veredas, David, 2012. "Testing conditional asymmetry: A residual-based approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1229-1247.
    21. Zhou, Yinggang, 2014. "Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 216-228.
    22. Hematizadeh, Roksana & Tajaddini, Reza & Hallahan, Terrence, 2022. "Dynamic asset allocation strategy using a state-dependent Markov model: Applications to international equity markets," Journal of International Money and Finance, Elsevier, vol. 128(C).
    23. Stanislav Anatolyev & Vladimir Pyrlik, 2021. "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers wp699, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    24. Loriana Pelizzon & Monica Billio & Mila Getmansky, 2008. "Crisis and Hedge Fund Risk," Working Papers 2008_10, Department of Economics, University of Venice "Ca' Foscari".
    25. Matthijs Lof, 2015. "Rational Speculators, Contrarians, and Excess Volatility," Management Science, INFORMS, vol. 61(8), pages 1889-1901, August.
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    162. Cathy Yi†Hsuan Chen & Thomas C. Chiang, 2016. "Empirical Analysis of the Intertemporal Relationship between Downside Risk and Expected Returns: Evidence from Time†varying Transition Probability Models," European Financial Management, European Financial Management Association, vol. 22(5), pages 749-796, November.
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    164. Gębka, Bartosz & Serwa, Dobromił, 2015. "The elusive nature of motives to trade: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 147-157.
    165. Laura Arenas & Ana Maria Gil-Lafuente, 2021. "Regime Switching in High-Tech ETFs: Idiosyncratic Volatility and Return," Mathematics, MDPI, vol. 9(7), pages 1-25, March.
    166. Högholm, Kenneth & Knif, Johan & Koutmos, Gregory & Pynnönen, Seppo, 2011. "Distributional asymmetry of loadings on market co-moments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(5), pages 851-866.
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    168. Elyasiani, Elyas & Mansur, Iqbal, 2017. "Hedge fund return, volatility asymmetry, and systemic effects: A higher-moment factor-EGARCH model," Journal of Financial Stability, Elsevier, vol. 28(C), pages 49-65.
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    171. Bi, Hongwei & Huang, Rachel J. & Tzeng, Larry Y. & Zhu, Wei, 2019. "Higher-order Omega: A performance index with a decision-theoretic foundation," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 43-57.
    172. Brad Case & Massimo Guidolin & Yildiray Yildirim, 2014. "Markov Switching Dynamics in REIT Returns: Univariate and Multivariate Evidence on Forecasting Performance," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(2), pages 279-342, June.
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    174. Huang, Weihong & Zheng, Huanhuan, 2012. "Financial crises and regime-dependent dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 82(2), pages 445-461.
    175. Taamouti, Abderrahim, 2012. "Moments of multivariate regime switching with application to risk-return trade-off," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 292-308.
    176. Vladimir Zdorovenin & Jacques Pézier, 2011. "Does Information Content of Option Prices Add Value for Asset Allocation?," ICMA Centre Discussion Papers in Finance icma-dp2011-03, Henley Business School, University of Reading.
    177. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    178. Chung, San-Lin & Hung, Mao-Wei & Wei, Tzu-Wen & Yeh, Chung-Ying, 2024. "Strategic asset allocation with distorted beliefs," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 804-831.
    179. Massimo Guidolin & Stuart Hyde, 2012. "Optimal Portfolios for Occupational Funds under Time-Varying Correlations in Bull and Bear Markets? Assessing the Ex-Post Economic Value," Working Papers 455, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    180. Fry, Renée & Martin, Vance L. & Tang, Chrismin, 2010. "A New Class of Tests of Contagion With Applications," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(3), pages 423-437.
    181. Marcelo Lewin & Carlos Heitor Campani, 2023. "Constrained portfolio strategies in a regime-switching economy," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(1), pages 27-59, March.
    182. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 015-031, June.
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    184. Lai, Jing-yi, 2012. "Shock-dependent conditional skewness in international aggregate stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 72-83.
    185. Tihana Škrinjarić & Boško Šego, 2018. "Using Grey Incidence Analysis Approach in Portfolio Selection," IJFS, MDPI, vol. 7(1), pages 1-16, December.
    186. Jianmin Shi, 2023. "Dynamic asset allocation with multiple regime‐switching markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1741-1755, April.
    187. Byron J. Idrovo-Aguirre & Francisco J. Lozano & Javier E. Contreras-Reyes, 2021. "Prosperity or Real Estate Bubble? Exuberance Probability Index of Real Housing Prices in Chile," IJFS, MDPI, vol. 9(3), pages 1-24, September.

  19. Allan Timmermann, 2007. "An Evaluation of the World Economic Outlook Forecasts," IMF Staff Papers, Palgrave Macmillan, vol. 54(1), pages 1-33, May.

    Cited by:

    1. Michael K Andersson & Ted Aranki & André Reslow, 2017. "Adjusting for information content when comparing forecast performance," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 784-794, November.
    2. Winkelried, Diego, 2014. "Inferring inflation expectations from fixed-event forecasts," Working Papers 2014-016, Banco Central de Reserva del Perú.
    3. Capistrán Carlos & López Moctezuma Gabriel, 2008. "Experts' Macroeconomics Expectations: An Evaluation of Mexican Short-Run Forecasts," Working Papers 2008-11, Banco de México.
    4. Mikael C. Bergbrant & Patrick J. Kelly, 2015. "Macroeconomic Expectations and the Size, Value and Momentum Factors," Working Papers w0214, New Economic School (NES).
    5. Foltas, Alexander & Pierdzioch, Christian, 2020. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Working Papers 22, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    6. Carabotta, Laura & Paluzie, Elisenda & Ramos, Raul, 2017. "Does fiscal responsibility matter? Evidence from public and private forecasters in Italy," International Journal of Forecasting, Elsevier, vol. 33(3), pages 694-706.
    7. Masahito Ambashi & Fusanori Iwasaki & Keita Oikawa, 2021. "Prediction Errors of Macroeconomic Indicators and Economic Shocks for ASEAN Member States," Working Papers DP-2022-02, Economic Research Institute for ASEAN and East Asia (ERIA).
    8. Qu, Ritong & Timmermann, Allan & Zhu, Yinchu, 2024. "Comparing forecasting performance with panel data," International Journal of Forecasting, Elsevier, vol. 40(3), pages 918-941.
    9. Winkelried, Diego, 2023. "Simple interpolations of inflation expectations," Economics Letters, Elsevier, vol. 229(C).
    10. Merola, Rossana & Pérez, Javier J., 2014. "Fiscal Forecast Errors: Governments Versus Independent Agencies?," Papers RB2014/1/1, Economic and Social Research Institute (ESRI).
    11. Aromí, J. Daniel, 2019. "Medium term growth forecasts: Experts vs. simple models," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1085-1099.
    12. MORIKAWA Masayuki, 2019. "Uncertainty in Long-Term Macroeconomic Forecasts: Ex post Evaluation of Forecasts by Economics Researchers," Discussion papers 19084, Research Institute of Economy, Trade and Industry (RIETI).
    13. Julien Champagne & Guillaume Poulin-Bellisle & Rodrigo Sekkel, 2018. "Evaluating the Bank of Canada Staff Economic Projections Using a New Database of Real-Time Data and Forecasts," Staff Working Papers 18-52, Bank of Canada.
    14. Jaramillo, Laura & Mulas-Granados, Carlos & Kimani, Elijah, 2017. "Debt spikes and stock flow adjustments: Emerging economies in perspective," Journal of Economics and Business, Elsevier, vol. 94(C), pages 1-14.
    15. Mr. Yan Carriere-Swallow & José Marzluf, 2021. "Macrofinancial Causes of Optimism in Growth Forecasts," IMF Working Papers 2021/275, International Monetary Fund.
    16. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    17. Mihaela SIMIONESCU, 2015. "The Evaluation of Global Accuracy of Romanian Inflation Rate Predictions Using Mahalanobis Distance," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 3(1), pages 133-149, March.
    18. Behrens, Christoph & Pierdzioch, Christian & Risse, Marian, 2018. "Testing the optimality of inflation forecasts under flexible loss with random forests," Economic Modelling, Elsevier, vol. 72(C), pages 270-277.
    19. Jin-Kyu Jung & Manasa Patnam & Anna Ter-Martirosyan, 2018. "An Algorithmic Crystal Ball: Forecasts-based on Machine Learning," IMF Working Papers 2018/230, International Monetary Fund.
    20. Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    21. Burgess, Matthew G. & Langendorf, Ryan E. & Ippolito, Tara & Pielke, Roger Jr, 2020. "Optimistically biased economic growth forecasts and negatively skewed annual variation," SocArXiv vndqr, Center for Open Science.
    22. Paulo Júlio & Pedro M. Esperança, 2012. "Evaluating the forecast quality of GDP components: An application to G7," GEE Papers 0047, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Apr 2012.
    23. Katja Heinisch & Axel Lindner, 2019. "For how long do IMF forecasts of world economic growth stay up-to-date?," Applied Economics Letters, Taylor & Francis Journals, vol. 26(3), pages 255-260, February.
    24. Yoichi Tsuchiya, 2021. "Thirty‐year assessment of Asian Development Bank's forecasts," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 35(2), pages 18-40, November.
    25. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
    26. Paulo Júlio & Pedro M. Esperança & João C. Fonseca, 2011. "Evaluating the forecast quality of GDP components," GEE Papers 0041 Classification-C52, , Gabinete de Estratégia e Estudos, Ministério da Economia, revised Oct 2011.
    27. Carlos Fonseca Marinheiro, 2010. "Fiscal sustainability and the accuracy of macroeconomic forecasts: do supranational forecasts rather than government forecasts make a difference?," GEMF Working Papers 2010-07, GEMF, Faculty of Economics, University of Coimbra.
    28. Mr. Francesco Grigoli & Alexander Herman & Mr. Andrew J Swiston & Gabriel Di Bella, 2015. "Output Gap Uncertainty and Real-Time Monetary Policy," IMF Working Papers 2015/014, International Monetary Fund.
    29. Paloviita, Maritta & Ikonen, Pasi, 2016. "How to explain errors in budget balance forecasts in euro area countries? Empirical evidence based on real-time data," Bank of Finland Research Discussion Papers 17/2016, Bank of Finland.
    30. Frank, Luis, 2021. "¿Son sesgadas las proyecciones de WEO? El caso de la proyección de crecimiento de Argentina [Are the WEO forecasts biased? The case of Argentina's growth forecast]," MPRA Paper 114333, University Library of Munich, Germany.
    31. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    32. María Paula Bonel & Daniel J. Aromí, 2021. "Assessing GDP forecasts from autoregressive models: the impact of model complexity and training dataset," Asociación Argentina de Economía Política: Working Papers 4440, Asociación Argentina de Economía Política.
    33. Hassan Naqvi, 2014. "IMF Conditionality and the Intertemporal Allocation of Resources," International Review of Finance, International Review of Finance Ltd., vol. 14(2), pages 203-235, June.
    34. Ley, Eduardo & Misch, Florian, 2013. "Real-time macro monitoring and fiscal policy," Policy Research Working Paper Series 6303, The World Bank.
    35. A. Melander & G. Sismanidis & D. Grenouilleau, 2007. "The track record of the Commission's forecasts - an update," European Economy - Economic Papers 2008 - 2015 291, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    36. Masahito Ambashi & Fusanori Iwasaki & Keita Oikawa, 2022. "Prediction Errors of Macroeconomic Indicators and Economic Shocks for ASEAN Member States, 1990-2021," KIER Working Papers 1088, Kyoto University, Institute of Economic Research.
    37. Capistrán, Carlos & López-Moctezuma, Gabriel, 2010. "Las expectativas macroeconómicas de los especialistas. Una evaluación de pronósticos de corto plazo en México," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(306), pages 275-312, abril-jun.
    38. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
    39. Eicher, Theo S. & Rollinson, Yuan Gao, 2023. "The accuracy of IMF crises nowcasts," International Journal of Forecasting, Elsevier, vol. 39(1), pages 431-449.
    40. Kanngiesser, Derrick & Willems, Tim, 2024. "Forecast accuracy and efficiency at the Bank of England – and how errors can be leveraged to do better," Bank of England working papers 1078, Bank of England.
    41. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
    42. Fernando M. Martin & Juan M. Sanchez & Olivia Wilkinson, 2022. "The Economic Impact of COVID-19 around the World," Working Papers 2022-030, Federal Reserve Bank of St. Louis.
    43. Emilian Dobrescu, 2014. "Attempting to Quantify the Accuracy of Complex Macroeconomic Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-21, December.
    44. Bourmpoula, Evangelia. & Wieser, Christina., 2014. "An accuracy assessment of the global employment trends' unemployment rate forecasts," ILO Working Papers 994888903402676, International Labour Organization.
    45. Behrens, Christoph, 2020. "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers 26, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    46. Paulina Ziembińska, 2021. "Quality of Tests of Expectation Formation for Revised Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 405-453, December.
    47. Drechsel, Katja & Giesen, Sebastian & Lindner, Axel, 2014. "Outperforming IMF Forecasts by the Use of Leading Indicators," IWH Discussion Papers 4/2014, Halle Institute for Economic Research (IWH).
    48. Javier J. Perez & Rossana Merola, 2012. "Fiscal forecast errors: governments vs independent agencies?," EcoMod2012 4694, EcoMod.
    49. Michel, David, 2009. "Foxes, hedgehogs, and greenhouse governance: Knowledge, uncertainty, and international policy-making in a warming World," Applied Energy, Elsevier, vol. 86(2), pages 258-264, February.
    50. Bourmpoula, Evangelia. & Wieser, Christina., 2014. "An accuracy assessment of the global employment trends' unemployment rate forecasts," Global Employment Trends Reports 994888903402676, International Labour Office, Economic and Labour Market Analysis Department.
    51. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.
    52. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    53. Klaus-Peter Hellwig, 2018. "Overfitting in Judgment-based Economic Forecasts: The Case of IMF Growth Projections," IMF Working Papers 2018/260, International Monetary Fund.
    54. Laura Jaramillo & Mr. Carlos Mulas-Granados & Elijah Kimani, 2016. "The Blind Side of Public Debt Spikes," IMF Working Papers 2016/202, International Monetary Fund.
    55. Jonas Dovern & Johannes Weisser, 2009. "Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7," Jena Economics Research Papers 2009-091, Friedrich-Schiller-University Jena.
    56. Nordvik, Frode Martin, 2022. "Inflation news and the poor: The role of ethnic heterogeneity," World Development, Elsevier, vol. 151(C).
    57. Axel Dreher & Silvia Marchesi & James Raymond Vreeland, 2007. "The Politics of IMF Forecasts," CESifo Working Paper Series 2129, CESifo.
    58. Hadzi-Vaskov, Metodij & Ricci, Luca Antonio & Werner, Alejandro & Zamarripa, Rene, 2021. "Patterns in IMF Growth Forecast Revisions: A Panel Study at Multiple Horizons," CEPR Discussion Papers 16153, C.E.P.R. Discussion Papers.
    59. H.O. Stekler & Huixia Zhang, 2013. "An evaluation of Chinese economic forecasts," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 11(4), pages 251-259, November.
    60. Maritta Paloviita & Pasi Ikonen, 2018. "Real-time uncertainty in budget planning: evidence from euro area countries," Journal of Economic Policy Reform, Taylor and Francis Journals, vol. 21(4), pages 281-300, October.
    61. Giang Ho & Paolo Mauro, 2016. "Growth—Now and Forever?," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(3), pages 526-547, August.
    62. Eicher, Theo S. & Kawai, Reina, 2023. "IMF trade forecasts for crisis countries: Bias, inefficiency, and their origins," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1615-1639.
    63. Timmermann, Allan & Qu, Ritong & Zhu, Yinchu, 2019. "Do Any Economists Have Superior Forecasting Skills?," CEPR Discussion Papers 14112, C.E.P.R. Discussion Papers.
    64. Jungjin Lee & Mr. Abdul d Abiad & Mr. Prakash Kannan, 2009. "Evaluating Historical CGER Assessments: How Well Have They Predicted Subsequent Exchange Rate Movements?," IMF Working Papers 2009/032, International Monetary Fund.

  20. Guidolin, Massimo & Timmermann, Allan, 2007. "Asset allocation under multivariate regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3503-3544, November.

    Cited by:

    1. Zeng, Songlin & Bec, Frédérique, 2015. "Do stock returns rebound after bear markets? An empirical analysis from five OECD countries," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 50-61.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Zhu, Dong-Mei & Lu, Jiejun & Ching, Wai-Ki & Siu, Tak-Kuen, 2017. "Discrete-time optimal asset allocation under Higher-Order Hidden Markov Model," Economic Modelling, Elsevier, vol. 66(C), pages 223-232.
    4. Bazgour, Tarik & Heuchenne, Cédric & Hübner, Georges & Sougné, Danielle, 2021. "How do volatility regimes affect the pricing of quality and liquidity in the stock market?," LIDAM Reprints ISBA 2021038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    6. Jang, Bong-Gyu & Kim, Kyeong Tae, 2015. "Optimal reinsurance and asset allocation under regime switching," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 37-47.
    7. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    8. GIOT, Pierre & PETITJEAN, Mikael, 2005. "Dynamic asset allocation between stocks and bonds using the Bond-Equity Yield Ratio," LIDAM Discussion Papers CORE 2005010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Anna Battauz & Marzia Donno & Alessandro Sbuelz, 2017. "Reaching nirvana with a defaultable asset?," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 31-52, November.
    10. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
    11. Jia Liu & John M. Maheu & Yong Song, 2024. "Identification and forecasting of bull and bear markets using multivariate returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 723-745, August.
    12. Wu, Bo & Li, Lingfei, 2024. "Reinforcement learning for continuous-time mean-variance portfolio selection in a regime-switching market," Journal of Economic Dynamics and Control, Elsevier, vol. 158(C).
    13. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    14. Guidolin, Massimo & Liu, Hening, 2016. "Ambiguity Aversion and Underdiversification," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1297-1323, August.
    15. Zolotoy, Leon & Frederickson, James R. & Lyon, John D., 2017. "Aggregate earnings and stock market returns: The good, the bad, and the state-dependent," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 157-175.
    16. Kim Hiang Liow & Qing Ye, 2018. "Regime dependent volatilities and correlation in international securitized real estate markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(3), pages 457-487, August.
    17. Konermann, Patrick & Meinerding, Christoph & Sedova, Olga, 2013. "Asset allocation in markets with contagion: The interplay between volatilities, jump intensities, and correlations," Review of Financial Economics, Elsevier, vol. 22(1), pages 36-46.
    18. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    19. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    20. Massimo Guidolin & Manuela Pedio, 2021. "Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?," Annals of Operations Research, Springer, vol. 299(1), pages 1317-1356, April.
    21. Bouaddi, Mohammed & Taamouti, Abderrahim, 2013. "Portfolio selection in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2943-2962.
    22. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    23. Fernando Alexandre & Vasco J. Gabriel & Pedro Bação, 2007. "The Consumption-Wealth Ratio Under Asymmetric Adjustment," NIPE Working Papers 15/2007, NIPE - Universidade do Minho.
    24. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    25. Nicole Branger & Holger Kraft & Christoph Meinerding, 2009. "What is the Impact of Stock Market Contagion on an Investor's Portfolio Choice?," Working Paper Series: Finance and Accounting 198, Department of Finance, Goethe University Frankfurt am Main.
    26. Yoontae Hwang & Stefan Zohren & Yongjae Lee, 2024. "Temporal Representation Learning for Stock Similarities and Its Applications in Investment Management," Papers 2407.13751, arXiv.org.
    27. Pim van Vliet & David Blitz, 2011. "Dynamic strategic asset allocation: Risk and return across the business cycle," Journal of Asset Management, Palgrave Macmillan, vol. 12(5), pages 360-375, November.
    28. Zhou, Yinggang, 2014. "Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 216-228.
    29. Gupta, Rangan & Hammoudeh, Shawkat & Modise, Mampho P. & Nguyen, Duc Khuong, 2014. "Can economic uncertainty, financial stress and consumer sentiments predict U.S. equity premium?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 367-378.
    30. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla & Masih, A. Mansur M., 2014. "Combining Momentum, Value, and Quality for the Islamic Equity Portfolio: Multi-style Rotation Strategies using Augmented Black Litterman Factor Model," MPRA Paper 56965, University Library of Munich, Germany.
    31. Reza Bradrania & Davood Pirayesh Neghab, 2022. "State-dependent Asset Allocation Using Neural Networks," Papers 2211.00871, arXiv.org.
    32. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    33. Javier Mencía & Enrique Sentana, 2008. "Multivariate Location-Scale Mixtures of Normals and Mean-Variance-skewness Portfolio Allocation," Working Papers wp2008_0805, CEMFI.
    34. Peter Nystrup & Henrik Madsen & Erik Lindström, 2018. "Dynamic portfolio optimization across hidden market regimes," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 83-95, January.
    35. Hematizadeh, Roksana & Tajaddini, Reza & Hallahan, Terrence, 2022. "Dynamic asset allocation strategy using a state-dependent Markov model: Applications to international equity markets," Journal of International Money and Finance, Elsevier, vol. 128(C).
    36. Pami Dua & Divya Tuteja, 2021. "Regime Shifts in the Behaviour of International Currency and Equity Markets: A Markov-Switching Analysis," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 309-336, December.
    37. Marco Tronzano, 2020. "Safe-Haven Assets, Financial Crises, and Macroeconomic Variables: Evidence from the Last Two Decades (2000–2018)," JRFM, MDPI, vol. 13(3), pages 1-21, February.
    38. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    39. Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
    40. Kang-Soek Lee, 2017. "Safe-haven currency: An empirical identification," Review of International Economics, Wiley Blackwell, vol. 25(4), pages 924-947, September.
    41. Anandadeep Mandal & Sunil S. Poshakwale & Gabriel J. Power, 2021. "Do investors gain from forecasting the asymmetric return co‐movements of financial and real assets?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3246-3268, July.
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    175. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 015-031, June.
    176. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
    177. Tihana Škrinjarić & Boško Šego, 2018. "Using Grey Incidence Analysis Approach in Portfolio Selection," IJFS, MDPI, vol. 7(1), pages 1-16, December.
    178. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
    179. Díaz, Antonio & Escribano, Ana & Esparcia, Carlos, 2024. "Sustainable risk preferences on asset allocation: a higher order optimal portfolio study," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).

  21. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Stan Hurn & Jing Tian & Lina Xu, 2021. "Assessing the Informational Content of Official Australian Bureau of Meteorology Forecasts of Wind Speed," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 525-547, December.
    3. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    4. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    5. Shea, Paul, 2015. "Red herrings and revelations: does learning about a new variable worsen forecasts?," Economic Modelling, Elsevier, vol. 49(C), pages 395-406.
    6. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    7. Christian Pierdzioch & Jan-Christoph Rülke & Peter Tillmann, 2013. "Using forecasts to uncover the loss function of FOMC members," MAGKS Papers on Economics 201302, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    8. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    9. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2009. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," National Institute of Economic and Social Research (NIESR) Discussion Papers 343, National Institute of Economic and Social Research.
    10. Pierdzioch, Christian & Rülke, Jan-Christoph, 2013. "Do inflation targets anchor inflation expectations?," Economic Modelling, Elsevier, vol. 35(C), pages 214-223.
    11. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    12. Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.
    13. Bauer, Christian & Neuenkirch, Matthias, 2017. "Forecast uncertainty and the Taylor rule," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 99-116.
    14. Timmermann Allan & Capistrán Carlos, 2006. "Disagreement and Biases in Inflation Expectations," Working Papers 2006-07, Banco de México.
    15. Pablo Pincheira B. & Nicolás Fernández, 2011. "Jaque Mate a las Proyecciones de Consenso," Working Papers Central Bank of Chile 630, Central Bank of Chile.
    16. Nazaria Solferino & Robert Waldmann, 2010. "Predicting the signs of forecast errors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 476-485.
    17. Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
    18. Jens J. Krüger, 2014. "A multivariate evaluation of German output growth and inflation forecasts," Economics Bulletin, AccessEcon, vol. 34(3), pages 1410-1418.
    19. Anatolyev, Stanislav, 2009. "Dynamic modeling under linear-exponential loss," Economic Modelling, Elsevier, vol. 26(1), pages 82-89, January.
    20. Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
    21. Cui, Qiurong & Xu, Yuqing & Zhang, Zhengjun & Chan, Vincent, 2021. "Max-linear regression models with regularization," Journal of Econometrics, Elsevier, vol. 222(1), pages 579-600.
    22. William A. Branch, 2014. "Nowcasting and the Taylor Rule," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(5), pages 1035-1055, August.
    23. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
    24. Goodwin, Thomas & Tian, Jing, 2017. "A state space approach to evaluate multi-horizon forecasts," Working Papers 2017-15, University of Tasmania, Tasmanian School of Business and Economics.
    25. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    26. Andrew J. Patton & Allan Timmermann, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-17, June.
    27. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    28. Jalles, João Tovar, 2017. "On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 175-189.
    29. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    30. Joanna Bruzda, 2020. "Multistep quantile forecasts for supply chain and logistics operations: bootstrapping, the GARCH model and quantile regression based approaches," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 309-336, March.
    31. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
    32. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    33. Kostas Mouratidis & Dimitris Kenourgios & Aris Samitas, 2010. "Evaluating currency crisis:A multivariate Markov switching approach," Working Papers 2010018, The University of Sheffield, Department of Economics, revised Oct 2010.
    34. Carlos Capistrán & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2‐3), pages 365-396, March.
    35. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    36. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    37. Conrad, Christian, 2017. "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168200, Verein für Socialpolitik / German Economic Association.
    38. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    39. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2009. "Expert opinion versus expertise in forecasting," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 334-346, August.
    40. Florian Peters & Simas Kucinskas, 2018. "Measuring Biases in Expectation Formation," Tinbergen Institute Discussion Papers 18-058/IV, Tinbergen Institute.
    41. Andrea Betancor & Pablo Pincheira, 2008. "Forecasting Inflation Forecast Errors," Working Papers Central Bank of Chile 477, Central Bank of Chile.
    42. Xinglin Yang & Peng Wang, 2018. "VIX futures pricing with conditional skewness," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1126-1151, September.
    43. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    44. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    45. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    46. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    47. Barbara Rossi, 2011. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 25-29, August.
    48. Bovi, Maurizio, 2019. "A Time-Varying Expectations Formation Mechanism," MPRA Paper 97624, University Library of Munich, Germany.
    49. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    50. Tian, Jing & Goodwin, Thomas, 2018. "An unobserved component modeling approach to evaluate multi-horizon forecasts," Working Papers 2018-04, University of Tasmania, Tasmanian School of Business and Economics.
    51. Lillestøl, Jostein & Sinding-Larsen, Richard, 2015. "Best estimate reporting with asymmetric loss," Discussion Papers 2015/7, Norwegian School of Economics, Department of Business and Management Science.
    52. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    53. Bourmpoula, Evangelia. & Wieser, Christina., 2014. "An accuracy assessment of the global employment trends' unemployment rate forecasts," ILO Working Papers 994888903402676, International Labour Organization.
    54. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    55. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2009. "How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan," CIRJE F-Series CIRJE-F-637, CIRJE, Faculty of Economics, University of Tokyo.
    56. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
    57. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    58. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    59. Federico Bassetti & Roberto Casarin & Marco Del Negro, 2022. "A Bayesian Approach to Inference on Probabilistic Surveys," Staff Reports 1025, Federal Reserve Bank of New York.
    60. Bourmpoula, Evangelia. & Wieser, Christina., 2014. "An accuracy assessment of the global employment trends' unemployment rate forecasts," Global Employment Trends Reports 994888903402676, International Labour Office, Economic and Labour Market Analysis Department.
    61. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.
    62. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    63. Sizova, Natalia, 2011. "Integrated variance forecasting: Model based vs. reduced form," Journal of Econometrics, Elsevier, vol. 162(2), pages 294-311, June.
    64. Qiu, Yajie & Deschamps, Bruno & Liu, Xiaoquan, 2024. "Uncertainty and macroeconomic forecasts: Evidence from survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 463-480.
    65. Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    66. Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
    67. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    68. Luetkepohl Helmut & Xu Fang, 2011. "Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-23, February.
    69. Michael W. McCracken & Giorgio Valente, 2012. "Asymptotic Inference for Performance Fees and the Predictability of Asset Returns," Working Papers 2012-049, Federal Reserve Bank of St. Louis.
    70. Pablo Pincheira, 2010. "A Real Time Evaluation of the Central Bank of Chile GDP Growth Forecasts," Working Papers Central Bank of Chile 556, Central Bank of Chile.
    71. Thiago De Oliveira Souza, 2011. "Forecasting Investment-Grade Credit-Spreads. A Regularized Approach," Working Papers ECARES ECARES 2011-037, ULB -- Universite Libre de Bruxelles.
    72. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    73. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    74. Kexin Ding & Ani L. Katchova, 2024. "Testing the optimality of USDA's WASDE forecasts under unknown loss," Agribusiness, John Wiley & Sons, Ltd., vol. 40(4), pages 846-865, October.
    75. Olga Isengildina‐Massa & Berna Karali & Todd H. Kuethe & Ani L. Katchova, 2021. "Joint Evaluation of the System of USDA's Farm Income Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(3), pages 1140-1160, September.
    76. Donayre, Luiggi & Panovska, Irina, 2016. "Nonlinearities in the U.S. wage Phillips curve," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 19-43.
    77. Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
    78. Henri Karttunen, 2020. "An autoregressive model based on the generalized hyperbolic distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 787-816, September.

  22. Guidolin, Massimo & Timmermann, Allan, 2007. "Properties of equilibrium asset prices under alternative learning schemes," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 161-217, January.

    Cited by:

    1. Volker Wieland & Christos Koulovatianos, 2011. "Asset Pricing under Rational Learning about Rare Disasters," 2011 Meeting Papers 1417, Society for Economic Dynamics.
    2. Christos Koulovatianos, 2010. "A Paradox of Environmental Awareness Campaigns," Discussion Papers 10/17, University of Nottingham, School of Economics.
    3. Milani, Fabio, 2017. "Learning about the interdependence between the macroeconomy and the stock market," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 223-242.
    4. Massimo Guidolin, 2006. "High equity premia and crash fears - Rational foundations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 693-708, August.
    5. Bernales, Alejandro & Chen, Louisa & Valenzuela, Marcela, 2017. "Learning and forecasts about option returns through the volatility risk premium," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 312-330.
    6. Subrahmanyam, Avanidhar, 2008. "Learning from experience and trading volume," Review of Financial Economics, Elsevier, vol. 17(4), pages 245-260, December.
    7. Hommes, C.H. & Zhu, M., 2012. "Behavioral Learning Equilibria," CeNDEF Working Papers 12-09, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    8. Massimo Guidolin, 2005. "Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle," Working Papers 2005-005, Federal Reserve Bank of St. Louis.
    9. Boudoukh, Jacob & Israel, Ronen & Richardson, Matthew, 2022. "Biases in long-horizon predictive regressions," Journal of Financial Economics, Elsevier, vol. 145(3), pages 937-969.
    10. Geoffrey J. Warren, 2008. "Implications for Asset Pricing Puzzles of a Roll‐over Assumption for the Risk‐Free Asset," International Review of Finance, International Review of Finance Ltd., vol. 8(3‐4), pages 125-157, September.
    11. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    12. Du, Kai, 2019. "Investor expectations, earnings management, and asset prices," Journal of Economic Dynamics and Control, Elsevier, vol. 105(C), pages 134-157.
    13. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    14. Lei Shi, 2010. "Portfolio Analysis and Equilibrium Asset Pricing with Heterogeneous Beliefs," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2010, January-A.
    15. Avanidhar Subrahmanyam, 2008. "Learning from experience and trading volume," Review of Financial Economics, John Wiley & Sons, vol. 17(4), pages 245-260, December.
    16. James B. Bullard & Jacek Suda, 2008. "The stability of macroeconomic systems with Bayesian learners," Working Papers 2008-043, Federal Reserve Bank of St. Louis.
    17. Quaye, Enoch & Tunaru, Radu, 2022. "The stock implied volatility and the implied dividend volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    18. Xue-Zhong He & Lei Shi, 2016. "A Binomial Model of Asset and Option Pricing with Heterogeneous Beliefs," Published Paper Series 2016-4, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    19. Consiglio, Andrea & Russino, Annalisa, 2007. "How does learning affect market liquidity? A simulation analysis of a double-auction financial market with portfolio traders," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1910-1937, June.
    20. Christos Koulovatianos, 2015. "Strategic Exploitation of a Common-Property Resource Under Rational Learning About its Reproduction," Dynamic Games and Applications, Springer, vol. 5(1), pages 94-119, March.
    21. Avanidhar Subrahmanyam, 2009. "Optimal financial education," Review of Financial Economics, John Wiley & Sons, vol. 18(1), pages 1-9, January.
    22. Brianzoni, Serena & Campisi, Giovanni, 2020. "Dynamical analysis of a financial market with fundamentalists, chartists, and imitators," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    23. Subrahmanyam, Avanidhar, 2009. "Optimal financial education," Review of Financial Economics, Elsevier, vol. 18(1), pages 1-9, January.
    24. Gandré, Pauline, 2020. "US stock prices and recency-biased learning in the run-up to the Global Financial Crisis and its aftermath," Journal of International Money and Finance, Elsevier, vol. 104(C).

  23. Patton, Andrew J. & Timmermann, Allan, 2007. "Testing Forecast Optimality Under Unknown Loss," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1172-1184, December.

    Cited by:

    1. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    2. D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.
    3. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    4. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    5. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    6. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    7. Christian Pierdzioch & Jan-Christoph Rülke & Peter Tillmann, 2013. "Using forecasts to uncover the loss function of FOMC members," MAGKS Papers on Economics 201302, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    8. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
    9. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2009. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," National Institute of Economic and Social Research (NIESR) Discussion Papers 343, National Institute of Economic and Social Research.
    10. Francis X. Diebold & Minchul Shin, 2017. "Assessing point forecast accuracy by stochastic error distance," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 588-598, October.
    11. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Combining Non-Replicable Forecasts," Working Papers in Economics 10/35, University of Canterbury, Department of Economics and Finance.
    12. Foltas, Alexander & Pierdzioch, Christian, 2020. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Working Papers 22, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    13. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    14. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Working Papers No 06/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    15. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    16. Andrew J. Patton & Allan Timmermann, 2008. "The Resolution of Macroeconomic Uncertainty: Evidence from Survey Forecast," CREATES Research Papers 2008-54, Department of Economics and Business Economics, Aarhus University.
    17. Michael Clements, 2017. "Do forecasters target first or later releases of national accounts data?," ICMA Centre Discussion Papers in Finance icma-dp2017-03, Henley Business School, University of Reading.
    18. Michael P. Clements, 2018. "Do Macroforecasters Herd?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 265-292, March.
    19. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    20. Timmermann Allan & Capistrán Carlos, 2006. "Disagreement and Biases in Inflation Expectations," Working Papers 2006-07, Banco de México.
    21. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    22. Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
    23. Chini, Emilio Zanetti, 2023. "Can we estimate macroforecasters’ mis-behavior?," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    24. Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2014. "Forecasting the South African Inflation Rate: On Asymmetric Loss and Forecast Rationality," Working Papers 201475, University of Pretoria, Department of Economics.
    25. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Aug 2024.
    26. Michael P. Clements, 2014. "US Inflation Expectations and Heterogeneous Loss Functions, 1968–2010," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 1-14, January.
    27. Andrew J. Patton & Allan Timmermann, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-17, June.
    28. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    29. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    30. Behrens, Christoph & Pierdzioch, Christian & Risse, Marian, 2018. "Testing the optimality of inflation forecasts under flexible loss with random forests," Economic Modelling, Elsevier, vol. 72(C), pages 270-277.
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    49. Efthymios G. Pavlidis & Ivan Paya & David A. Peel, 2018. "Using Market Expectations to Test for Speculative Bubbles in the Crude Oil Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(5), pages 833-856, August.
    50. Issler, João Victor & Rodrigues, Claudia & Burjack, Rafael, 2014. "Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 310-335.
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    54. Philip Hans Franses & Max Welz, 2022. "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 829-839, July.
    55. Angelo Mont’Alverne Duarte & Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & João Victor Issler, 2020. "Commodity Prices and Global Economic Activity: a derived-demand approach," Working Papers Series 539, Central Bank of Brazil, Research Department.
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    58. Manzanares, Andrés & Garcí­a, Juan Angel, 2007. "Reporting biases and survey results: evidence from European professional forecasters," Working Paper Series 836, European Central Bank.
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    121. Adekunle, Salami Saheed & Masih, Mansur, 2017. "Assessing the viability of Sukuk for portfolio diversification using MS-DCC-GARCH," MPRA Paper 79443, University Library of Munich, Germany.
    122. Liu, Chunbo & Zhang, Xuan & Zhou, Zhiping, 2023. "Are commodity futures a hedge against inflation? A Markov-switching approach," International Review of Financial Analysis, Elsevier, vol. 86(C).
    123. Raza, Hamid & Wu, Weiou, 2018. "Quantile dependence between the stock, bond and foreign exchange markets – Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 286-296.
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    125. Akay, Ozgur (Ozzy) & Senyuz, Zeynep & Yoldas, Emre, 2013. "Hedge fund contagion and risk-adjusted returns: A Markov-switching dynamic factor approach," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 16-29.
    126. MacLean, Leonard C. & Zhao, Yonggan & Ziemba, William T., 2014. "Optimal capital growth with convex shortfall penalties," LSE Research Online Documents on Economics 59292, London School of Economics and Political Science, LSE Library.
    127. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Post-Print halshs-01821815, HAL.
    128. Dominique Guégan & Matteo Iacopini, 2018. "Nonparameteric forecasting of multivariate probability density functions," Documents de travail du Centre d'Economie de la Sorbonne 18012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    129. Constantin Anghelache & Marius Popovici & Alina – Georgiana Solomon & Emilia Stanciu, 2017. "Aggregates in Real Expression and Price Indices by Deflation," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 7(6), pages 1053-1060, June.
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    134. Mehmet Balcilar & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2019. "The Risk Exposures of Safe Havens to Global and Regional Stock Market Shocks: A Novel Approach," Working Papers 201915, University of Pretoria, Department of Economics.
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    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    3. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    4. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
    5. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    6. Zhenni Ding & Huayou Chen & Ligang Zhou, 2023. "Using shapely values to define subgroups of forecasts for combining," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 905-923, July.
    7. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    8. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
    9. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    10. Cristiana Belu Manescu & Ine Van Robays, 2016. "Forecasting the Brent Oil Price: Addressing Time-Variation in Forecast Performance," CESifo Working Paper Series 6242, CESifo.
    11. Masayoshi Hayashi, 2012. "Forecasting Welfare Caseloads: The Case of the Japanese Public Assistance Program," CIRJE F-Series CIRJE-F-846, CIRJE, Faculty of Economics, University of Tokyo.
    12. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
    13. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
    14. Bravo, Jorge M. & Ayuso, Mercedes & Holzmann, Robert & Palmer, Edward, 2021. "Addressing the life expectancy gap in pension policy," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 200-221.
    15. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    16. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
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    21. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
    22. Turgut Kisinbay & Chikako Baba, 2011. "Predicting Recessions: A New Approach for Identifying Leading Indicators and Forecast Combinations," IMF Working Papers 2011/235, International Monetary Fund.
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    25. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
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    37. Qian Chen & Xiang Gao & Shan Xie & Li Sun & Shuairu Tian & Shigeyuki Hamori, 2021. "On the Predictability of China Macro Indicator with Carbon Emissions Trading," Energies, MDPI, vol. 14(5), pages 1-24, February.
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    45. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
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    47. Foroni, Claudia & Marcellino, Massimiliano, 2014. "A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates," International Journal of Forecasting, Elsevier, vol. 30(3), pages 554-568.
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    51. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
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    66. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
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    132. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
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    134. Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018. "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 132-142.
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    136. Boriss Siliverstovs, 2015. "Dissecting Models' Forecasting Performance," KOF Working papers 15-397, KOF Swiss Economic Institute, ETH Zurich.
    137. Cenesizoglu, Tolga & Timmermann, Allan, 2012. "Do return prediction models add economic value?," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2974-2987.
    138. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    139. Massacci, Daniele, 2013. "A switching model with flexible threshold variable: With an application to nonlinear dynamics in stock returns," Economics Letters, Elsevier, vol. 119(2), pages 199-203.
    140. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    141. Chi‐Hsiou Hung, 2008. "Return Predictability of Higher‐Moment CAPM Market Models," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(7‐8), pages 998-1022, September.
    142. David Alan Peel & Pantelis Promponas, 2016. "Forecasting the nominal exchange rate movements in a changing world. The case of the U.S. and the U.K," Working Papers 144439514, Lancaster University Management School, Economics Department.
    143. Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
    144. Cai, Zongwu & Wang, Yunfei, 2014. "Testing predictive regression models with nonstationary regressors," Journal of Econometrics, Elsevier, vol. 178(P1), pages 4-14.
    145. Stefano Cassella & Huseyin Gulen, 2018. "Extrapolation Bias and the Predictability of Stock Returns by Price-Scaled Variables," The Review of Financial Studies, Society for Financial Studies, vol. 31(11), pages 4345-4397.
    146. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    147. Gantungalag Altansukh & Denise R. Osborn, 2022. "Using structural break inference for forecasting time series," Empirical Economics, Springer, vol. 63(1), pages 1-41, July.
    148. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    149. McMillan, David G., 2019. "Stock return predictability: Using the cyclical component of the price ratio," Research in International Business and Finance, Elsevier, vol. 48(C), pages 228-242.
    150. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    151. Atanasov, Victoria, 2018. "World output gap and global stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 181-197.
    152. Smith, Simon C. & Timmermann, Allan, 2022. "Have risk premia vanished?," Journal of Financial Economics, Elsevier, vol. 145(2), pages 553-576.
    153. Tae-Hwy Lee & Aman Ullah & He Wang, 2023. "The Second-order Bias and Mean Squared Error of Quantile Regression Estimators," Working Papers 202313, University of California at Riverside, Department of Economics.
    154. David I. Harvey & Stephen J. Leybourne & Robert Sollis & A.M. Robert Taylor, 2021. "Real‐time detection of regimes of predictability in the US equity premium," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 45-70, January.
    155. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    156. Cathy Yi†Hsuan Chen & Thomas C. Chiang, 2016. "Empirical Analysis of the Intertemporal Relationship between Downside Risk and Expected Returns: Evidence from Time†varying Transition Probability Models," European Financial Management, European Financial Management Association, vol. 22(5), pages 749-796, November.
    157. Jennie Bai, 2010. "Equity premium predictions with adaptive macro indexes," Staff Reports 475, Federal Reserve Bank of New York.
    158. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    159. Hartmann, Daniel & Kempa, Bernd & Pierdzioch, Christian, 2006. "Economic and Financial Crises and the Predictability of U.S. Stock Returns," MPRA Paper 561, University Library of Munich, Germany.
    160. Kirt Butler & Katsushi Okada, 2009. "The relative contribution of conditional mean and volatility in bivariate returns to international stock market indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(1), pages 1-15.
    161. Barras, Laurent, 2007. "International conditional asset allocation under specification uncertainty," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 443-464, September.
    162. McMillan, David G., 2019. "Predicting firm level stock returns: Implications for asset pricing and economic links," The British Accounting Review, Elsevier, vol. 51(4), pages 333-351.
    163. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
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  31. Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, August.

    Cited by:

    1. Bastianin, Andrea & Conti, Francesca & Manera, Matteo, 2016. "The Impacts of Oil Price Shocks on Stock Market Volatility: Evidence from the G7 Countries," Energy: Resources and Markets 230682, Fondazione Eni Enrico Mattei (FEEM).
    2. Hayette Gatfaoui, 2010. "Investigating the dependence structure between credit default swap spreads and the U.S. financial market," Annals of Finance, Springer, vol. 6(4), pages 511-535, October.
    3. Andrea BASTIANIN & Matteo MANERA, 2015. "How Does Stock Market Volatility React to Oil Shocks?," Departmental Working Papers 2015-09, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    4. Nolte, Ingmar & Voev, Valeri, 2007. "Panel intensity models with latent factors: An application to the trading dynamics on the foreign exchange market," CoFE Discussion Papers 07/02, University of Konstanz, Center of Finance and Econometrics (CoFE).
    5. Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.

  32. Allan Timmermann & David Blake, 2005. "International Asset Allocation with Time-Varying Investment Opportunities," The Journal of Business, University of Chicago Press, vol. 78(1), pages 71-98, January.
    See citations under working paper version above.
  33. Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
    See citations under working paper version above.
  34. Pesaran, Hashem & Timmermann, Allan, 2005. "Real-Time Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 212-231, February.
    See citations under working paper version above.
  35. Graham Elliott & Allan Timmermann, 2005. "Optimal Forecast Combination Under Regime Switching ," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(4), pages 1081-1102, November.
    See citations under working paper version above.
  36. Massimo Guidolin & Allan Timmermann, 2005. "Economic Implications of Bull and Bear Regimes in UK Stock and Bond Returns," Economic Journal, Royal Economic Society, vol. 115(500), pages 111-143, January.

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    1. Zeng, Songlin & Bec, Frédérique, 2015. "Do stock returns rebound after bear markets? An empirical analysis from five OECD countries," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 50-61.
    2. Michael T. Owyang & Jeremy Piger & Daniel Soques, 2022. "Contagious switching," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 415-432, March.
    3. J. Cuñado & L. Gil-Alana & F. Gracia, 2009. "US stock market volatility persistence: evidence before and after the burst of the IT bubble," Review of Quantitative Finance and Accounting, Springer, vol. 33(3), pages 233-252, October.
    4. Bulla, Jan & Mergner, Sascha & Bulla, Ingo & Sesboüé, André & Chesneau, Christophe, 2010. "Markov-switching Asset Allocation: Do Profitable Strategies Exist?," MPRA Paper 21154, University Library of Munich, Germany.
    5. Mamadou Cisse & Mamadou Konte & Mohamed Toure & Smael Afolabi Assani, 2019. "Contribution to the Valuation of BRVM’s Assets: A Conditional CAPM Approach," JRFM, MDPI, vol. 12(1), pages 1-15, February.
    6. Thomas J. Flavin and Ekaterini Panopoulou, 2007. "Detecting Shift and Pure Contagion in East Asian Equity Markets: A Unified Approach," The Institute for International Integration Studies Discussion Paper Series iiisdp236, IIIS.
    7. Fletcher, Jonathan, 2011. "Do optimal diversification strategies outperform the 1/N strategy in U.K. stock returns?," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 375-385.
    8. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova & Michael Obersteiner, 2024. "Regime‐dependent commodity price dynamics: A predictive analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2822-2847, November.
    9. Heidari , Hassan & Refah-Kahriz, Arash & Hashemi Berenjabadi, Nayyer, 2018. "Dynamic Relationship between Macroeconomic Variables and Stock Return Volatility in Tehran Stock Exchange: Multivariate MS ARMA GARCH Approach," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 5(2), pages 223-250, August.
    10. Don Bredin & Stuart Hyde, 2008. "Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies," European Financial Management, European Financial Management Association, vol. 14(2), pages 315-346, March.
    11. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    12. Thomas J. Flavin & Ekaterini Panopoulou & Deren Unalmis, 2008. "On the Stability of Domestic Financial Market Linkages in the Presence of time-varying Volatility," Working Papers 0810, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    13. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2009. "Time and Risk Diversification in Real Estate Investments: Assessing the Ex Post Economic Value," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 37(3), pages 341-381, September.
    14. Chang, Kuang-Liang, 2016. "Does the return-state-varying relationship between risk and return matter in modeling the time series process of stock return?," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 72-87.
    15. Jilber Urbina & Miguel Santolino & Montserrat Guillen, 2021. "Covariance Principle for Capital Allocation: A Time-Varying Approach," Mathematics, MDPI, vol. 9(16), pages 1-13, August.
    16. John M Maheu & Thomas H McCurdy & Yong Song, 2009. "Extracting bull and bear markets from stock returns," Working Papers tecipa-369, University of Toronto, Department of Economics.
    17. Frédérique Bec & Annabelle de Gaye, 2019. "Le modèle autorégressif autorégressif à seuil avec effet rebond : Une application aux rendements boursiers français et américains ," Working Papers hal-02014663, HAL.
    18. Massimo Guidolin & Stuart Hyde, 2009. "What tames the Celtic Tiger? Portfolio implications from a Multivariate Markov Switching model," Applied Financial Economics, Taylor & Francis Journals, vol. 19(6), pages 463-488.
    19. Turtle, H.J. & Zhang, Chengping, 2012. "Time-varying performance of international mutual funds," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 334-348.
    20. Gil-Alana, Luis A. & Shittu, Olanrewaju I. & Yaya, OlaOluwa S., 2014. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 149-162.
    21. Syed Jawad Hussain Shahzad & Saba Ameer & Muhammad Shahbaz, 2016. "Disaggregating the correlation under bearish and bullish markets: A Quantile-quantile approach," Post-Print hal-02013740, HAL.
    22. Hadhri, Sinda, 2021. "The nexus, downside risk and asset allocation between oil and Islamic stock markets: A cross-country analysis," Energy Economics, Elsevier, vol. 101(C).
    23. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
    24. Thomas Flavin & Dolores Lagoa-Varela, 2016. "Do long-term bonds hedge equity risk? Evidence from Spain," Economics Department Working Paper Series n275-16.pdf, Department of Economics, National University of Ireland - Maynooth.
    25. Zhou, Yinggang, 2014. "Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 216-228.
    26. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2008. "Diversifying in public real estate: The ex-post performance," Journal of Asset Management, Palgrave Macmillan, vol. 8(6), pages 361-373, February.
    27. Massimo Guidolin & Giovanna Nicodano, 2007. "Managing international portfolios with small capitalization stocks," Working Papers 2007-030, Federal Reserve Bank of St. Louis.
    28. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    29. Chatziantoniou, Ioannis & Filis, George & Floros, Christos, 2017. "Asset prices regime-switching and the role of inflation targeting monetary policy," Global Finance Journal, Elsevier, vol. 32(C), pages 97-112.
    30. Chan, Kalok & Yang, Jian & Zhou, Yinggang, 2018. "Conditional co-skewness and safe-haven currencies: A regime switching approach," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 58-80.
    31. John Fender, 2020. "Beyond the efficient markets hypothesis: Towards a new paradigm," Bulletin of Economic Research, Wiley Blackwell, vol. 72(3), pages 333-351, July.
    32. Anandadeep Mandal & Sunil S. Poshakwale & Gabriel J. Power, 2021. "Do investors gain from forecasting the asymmetric return co‐movements of financial and real assets?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3246-3268, July.
    33. Apostolos Thomadakis, 2012. "Contagion or Flight-to-Quality Phenomena in Stock and Bond Returns," School of Economics Discussion Papers 0612, School of Economics, University of Surrey.
    34. Meenagh, David & Minford, Patrick & Peel, David, 2007. "Simulating stock returns under switching regimes - A new test of market efficiency," Economics Letters, Elsevier, vol. 94(2), pages 235-239, February.
    35. Donatien Hainaut & Yang Shen & Yan Zeng, 2018. "How do capital structure and economic regime affect fair prices of bank’s equity and liabilities?," Annals of Operations Research, Springer, vol. 262(2), pages 519-545, March.
    36. Angelidis, Timotheos & Degiannakis, Stavros & Filis, George, 2015. "US stock market regimes and oil price shocks," MPRA Paper 80436, University Library of Munich, Germany.
    37. Jonathan Fletcher, 2011. "An Examination of Dynamic Trading Stategies in UK and US Stock Returns," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(9-10), pages 1290-1310, November.
    38. Flavin, Thomas J. & Lagoa-Varela, Dolores, 2021. "On the stability of stock-bond comovements across market conditions in the Eurozone periphery," Global Finance Journal, Elsevier, vol. 49(C).
    39. Alfonso Dufour & Andrei Stancu & Simone Varotto, 2014. "The Equity-like Behaviour of Sovereign Bonds," ICMA Centre Discussion Papers in Finance icma-dp2014-16, Henley Business School, University of Reading.
    40. Bulla, Jan, 2009. "Hidden Markov models with t components. Increased persistence and other aspects," MPRA Paper 21830, University Library of Munich, Germany.
    41. Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
    42. Sim, Nicholas, 2016. "Modeling the dependence structures of financial assets through the Copula Quantile-on-Quantile approach," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 31-45.
    43. Roy H. Kwon & Jonathan Y. Li, 2016. "A stochastic semidefinite programming approach for bounds on option pricing under regime switching," Annals of Operations Research, Springer, vol. 237(1), pages 41-75, February.
    44. Guidolin, Massimo & Hyde, Stuart, 2008. "Equity portfolio diversification under time-varying predictability: Evidence from Ireland, the US, and the UK," Journal of Multinational Financial Management, Elsevier, vol. 18(4), pages 293-312, October.
    45. Misheck Mutize & Sean J. Gossel, 2019. "Sovereign Credit Rating Announcement Effects on Foreign Currency Denominated Bond and Equity Markets in Africa," Journal of African Business, Taylor & Francis Journals, vol. 20(1), pages 135-152, January.
    46. Chang, Kuang-Liang, 2012. "The impacts of regime-switching structures and fat-tailed characteristics on the relationship between inflation and inflation uncertainty," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 523-536.
    47. Emrah İ. Çevik & Turhan Korkmaz & Erdal Atukeren, 2012. "Business confidence and stock returns in the USA: a time-varying Markov regime-switching model," Applied Financial Economics, Taylor & Francis Journals, vol. 22(4), pages 299-312, February.
    48. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
    49. Hainaut, Donatien, 2014. "Impulse control of pension fund contributions, in a regime switching economy," European Journal of Operational Research, Elsevier, vol. 239(3), pages 810-819.
    50. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers 2010-039, Federal Reserve Bank of St. Louis.
    51. Chang, Kuang-Liang, 2021. "Do U.S. and Japanese uncertainty shocks play important roles in affecting transition mechanisms of Japanese stock market?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    52. Muhl, Stefan & Talpsepp, Tõnn, 2018. "Faster learning in troubled times: How market conditions affect the disposition effect," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 226-236.
    53. Massimo Guidolin & Giovanna Nicodano, 2009. "Small caps in international equity portfolios: the effects of variance risk," Annals of Finance, Springer, vol. 5(1), pages 15-48, January.
    54. Refk Selmi & Christos Kollias & Stephanos Papadamou & Rangan Gupta, 2017. "A Copula-Based Quantile-on-Quantile Regression Approach to Modeling Dependence Structure between Stock and Bond Returns: Evidence from Historical Data of India, South Africa, UK and US," Working Papers 201747, University of Pretoria, Department of Economics.
    55. Flavin, Thomas J. & Panopoulou, Ekaterini, 2009. "On the robustness of international portfolio diversification benefits to regime-switching volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 140-156, February.
    56. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    57. Yao Zheng & Peihwang Wei & Eric Osmer, 2022. "The relation between earnings and price momentum: Does it vary across regimes?," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1145-1213, April.
    58. Thomas Flavin & Ekaterini Panopoulou, 2007. "International Portfolio Diversification and Market Linkages in the presence of regime-switching volatility," Money Macro and Finance (MMF) Research Group Conference 2006 150, Money Macro and Finance Research Group.
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    61. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.
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    76. Donatien Hainaut & Franck Moraux, 2019. "A switching self-exciting jump diffusion process for stock prices," Annals of Finance, Springer, vol. 15(2), pages 267-306, June.
    77. Olivier Courtois & Xiaoshan Su, 2020. "Structural Pricing of CoCos and Deposit Insurance with Regime Switching and Jumps," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(4), pages 477-520, December.
    78. Apostolos Thomadakis, 2012. "Measuring Financial Contagion with Extreme Coexceedances," School of Economics Discussion Papers 1112, School of Economics, University of Surrey.
    79. Coakley, Jerry & Fuertes, Ana-Maria, 2006. "Valuation ratios and price deviations from fundamentals," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2325-2346, August.
    80. Roy Kwon & Jonathan Li, 2016. "A stochastic semidefinite programming approach for bounds on option pricing under regime switching," Annals of Operations Research, Springer, vol. 237(1), pages 41-75, February.
    81. Wang, Ling, 2022. "The dynamics of money supply determination under asset purchase programs: A market-based versus a bank-based financial system," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    82. Joe Brocato & Kenneth Smith, 2012. "Sudden equity price declines and the flight-to-safety phenomenon: additional evidence using daily data," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(3), pages 712-727, July.
    83. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2007. "Investing for the Long-run in European Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 34(1), pages 35-80, January.
    84. Angelos Kanas, 2009. "The relation between the equity risk premium and the bond maturity premium in the UK: 1900–2006," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(2), pages 111-127, April.
    85. Wai-Mun Chia & Mengling Li & Huanhuan Zheng, 2017. "Behavioral heterogeneity in the Australian housing market," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 872-885, February.
    86. Hainaut, Donatien & Goutte, Stephane, 2019. "A switching microstructure model for stock prices," LIDAM Reprints ISBA 2019024, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    87. Simmons-Süer, Banu, 2018. "“How relevant is capital structure for aggregate investment? a regime-switching approach”," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 109-117.
    88. Chourdakis, Kyriakos & Dendramis, Yiannis & Tzavalis, Elias, 2014. "Are regime-shift sources of risk priced in the market?," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 151-170.
    89. Thomas Flavin & Ekaterini Panopoulou, 2006. "Shift versus traditional contagion in Asian markets," The Institute for International Integration Studies Discussion Paper Series iiisdp176, IIIS.
    90. Yaojie Zhang & Mengxi He & Yuqi Zhao & Xianfeng Hao, 2023. "Predicting stock realized variance based on an asymmetric robust regression approach," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1022-1047, October.
    91. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
    92. Luis Alberiko & OlaOluwa S. Yaya & Olarenwaju I. Shittu, 2015. "Fractional integration and asymmetric volatility in european, asian and american bull and bear markets. Applications to high frequency stock data," NCID Working Papers 07/2015, Navarra Center for International Development, University of Navarra.
    93. Jun Tu, 2010. "Is Regime Switching in Stock Returns Important in Portfolio Decisions?," Management Science, INFORMS, vol. 56(7), pages 1198-1215, July.
    94. Massimo Guidolin & Stuart Hyde, 2008. "Equity portfolio diversification under time-varying predictability and comovements: evidence from Ireland, the US, and the UK," Working Papers 2008-005, Federal Reserve Bank of St. Louis.
    95. Marika Křepelová & Josef Jablonský, 2013. "Analýza státních dluhopisů jako indikátoru pro akciový trh [Analysis of Government Bonds as an Indicator for Stock Market]," Politická ekonomie, Prague University of Economics and Business, vol. 2013(5), pages 605-622.
    96. Jian Yang & Yinggang Zhou & Zijun Wang, 2010. "Conditional Coskewness in Stock and Bond Markets: Time-Series Evidence," Management Science, INFORMS, vol. 56(11), pages 2031-2049, November.
    97. Bejaoui, Azza & Karaa, Adel, 2016. "Revisiting the bull and bear markets notions in the Tunisian stock market: New evidence from multi-state duration-dependence Markov-switching models," Economic Modelling, Elsevier, vol. 59(C), pages 529-545.
    98. Ayadi, Mohamed A. & Lazrak, Skander & Liao, Yusui & Welch, Robert, 2018. "Performance of fixed-income mutual funds with regime-switching models," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 217-231.
    99. Chang, Kuang-Liang & Yu, Shih-Ti, 2013. "Does crude oil price play an important role in explaining stock return behavior?," Energy Economics, Elsevier, vol. 39(C), pages 159-168.
    100. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    101. Afsaneh Bahrami & Abul Shamsuddin & Katherine Uylangco, 2018. "Out‐of‐sample stock return predictability in emerging markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(3), pages 727-750, September.
    102. Jan Bulla & Sascha Mergner & Ingo Bulla & André Sesboüé & Christophe Chesneau, 2011. "Markov-switching asset allocation: Do profitable strategies exist?," Journal of Asset Management, Palgrave Macmillan, vol. 12(5), pages 310-321, November.
    103. Li, Dakai, 2024. "Forecasting stock market realized volatility: The role of investor attention to the price of petroleum products," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 115-122.
    104. Taamouti, Abderrahim, 2012. "Moments of multivariate regime switching with application to risk-return trade-off," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 292-308.
    105. Christos Kollias & Stephanos Papadamou & Vangelis Arvanitis, 2013. "Does Terrorism Affect the Stock‐Bond Covariance? Evidence from European Countries," Southern Economic Journal, John Wiley & Sons, vol. 79(4), pages 832-848, April.
    106. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    107. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
    108. Hanna, Alan J., 2018. "A top-down approach to identifying bull and bear market states," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 93-110.
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    111. Zegadło, Piotr, 2022. "Identifying bull and bear market regimes with a robust rule-based method," Research in International Business and Finance, Elsevier, vol. 60(C).
    112. Cunado, J. & Gil-Alana, L.A. & Gracia, Fernando Perez de, 2010. "Mean reversion in stock market prices: New evidence based on bull and bear markets," Research in International Business and Finance, Elsevier, vol. 24(2), pages 113-122, June.

  37. Sandeep Kapur & Allan Timmermann, 2005. "Relative Performance Evaluation Contracts and Asset Market Equilibrium," Economic Journal, Royal Economic Society, vol. 115(506), pages 1077-1102, October.
    See citations under working paper version above.
  38. Elliott, Graham & Timmermann, Allan, 2004. "Optimal forecast combinations under general loss functions and forecast error distributions," Journal of Econometrics, Elsevier, vol. 122(1), pages 47-79, September.
    See citations under working paper version above.
  39. Pesaran, M. Hashem & Timmermann, Allan, 2004. "How costly is it to ignore breaks when forecasting the direction of a time series?," International Journal of Forecasting, Elsevier, vol. 20(3), pages 411-425.
    See citations under working paper version above.
  40. Lunde A. & Timmermann A., 2004. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 253-273, July.
    See citations under working paper version above.
  41. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    See citations under working paper version above.
  42. Massimo Guidolin & Allan Timmermann, 2003. "Recursive Modeling of Nonlinear Dynamics in UK Stock Returns," Manchester School, University of Manchester, vol. 71(4), pages 381-395, July.

    Cited by:

    1. Don Bredin & Stuart Hyde, 2008. "Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies," European Financial Management, European Financial Management Association, vol. 14(2), pages 315-346, March.
    2. Massimo Guidolin & Stuart Hyde, 2009. "What tames the Celtic Tiger? Portfolio implications from a Multivariate Markov Switching model," Applied Financial Economics, Taylor & Francis Journals, vol. 19(6), pages 463-488.
    3. Apostolos Thomadakis, 2012. "Contagion or Flight-to-Quality Phenomena in Stock and Bond Returns," School of Economics Discussion Papers 0612, School of Economics, University of Surrey.
    4. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
    5. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers 2010-039, Federal Reserve Bank of St. Louis.
    6. Aslanidis, Nektarios & Osborn, Denise R. & Sensier, Marianne, 2008. "Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations," Working Papers 2072/8950, Universitat Rovira i Virgili, Department of Economics.
    7. N Aslanidis & D R Osborn & M Sensier, 2003. "Explaining Movements in UK Stock Prices: How Important is the US Market?," Economics Discussion Paper Series 0305, Economics, The University of Manchester.
    8. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2008. "Comovements between US and UK stock prices: the roles of macroeconomic information and timevarying conditional correlations," Economics Discussion Paper Series 0805, Economics, The University of Manchester.
    9. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2010. "Co-movements between US and UK stock prices: the role of time-varying conditional correlations," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 366-380.
    10. Nektarios Aslanidis & Denise Osborn & Marianne Sensier, 2003. "Explaining movements in UK stock prices:," Working Papers 0302, University of Crete, Department of Economics.

  43. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2003. "Forecast evaluation with shared data sets," International Journal of Forecasting, Elsevier, vol. 19(2), pages 217-227.
    See citations under working paper version above.
  44. Guidolin, Massimo & Timmermann, Allan, 2003. "Option prices under Bayesian learning: implied volatility dynamics and predictive densities," Journal of Economic Dynamics and Control, Elsevier, vol. 27(5), pages 717-769, March.
    See citations under working paper version above.
  45. Pesaran, M. Hashem & Timmermann, Allan, 2002. "Market timing and return prediction under model instability," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 495-510, December.
    See citations under working paper version above.
  46. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2001. "Dangers of data mining: The case of calendar effects in stock returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 249-286, November.

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    1. Diego Winkelried & Luis A. Iberico, 2018. "Calendar effects in Latin American stock markets," Empirical Economics, Springer, vol. 54(3), pages 1215-1235, May.
    2. Kam Fong Chan & John G. Powell & Jing Shi & Tom Smith, 2018. "Dividend persistence and dividend behaviour," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(1), pages 127-147, March.
    3. Mateus, Irina B. & Mateus, Cesario & Todorovic, Natasa, 2019. "Review of new trends in the literature on factor models and mutual fund performance," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 344-354.
    4. Egbers, Tom & Swinkels, Laurens, 2015. "Can implied volatility predict returns on the currency carry trade?," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 14-26.
    5. Ryans Bartens & Shakill Hassan, 2009. "Value, Size and Momentum Portfolios in Real Time: The Cross-Section of South African Stocks," Working Papers 154, Economic Research Southern Africa.
    6. Dichtl, Hubert & Drobetz, Wolfgang, 2015. "Sell in May and Go Away: Still good advice for investors?," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 29-43.
    7. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
    8. Andrew Y. Chen & Tom Zimmermann, 2018. "Publication Bias and the Cross-Section of Stock Returns," Finance and Economics Discussion Series 2018-033, Board of Governors of the Federal Reserve System (U.S.).
    9. Kilian, Lutz & Inoue, Atsushi, 2002. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," CEPR Discussion Papers 3671, C.E.P.R. Discussion Papers.
    10. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    11. Doyle, John R. & Chen, Catherine Huirong, 2009. "The wandering weekday effect in major stock markets," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1388-1399, August.
    12. Pedro Antonio Martín-Cervantes & María del Carmen Valls Martínez, 2023. "Unraveling the relationship between betas and ESG scores through the Random Forests methodology," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-29, September.
    13. William Ziemba, 2011. "Investing in the turn-of-the-year effect," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(4), pages 455-472, December.
    14. Meenagh, David & Minford, Patrick & Peel, David, 2007. "Simulating stock returns under switching regimes - A new test of market efficiency," Economics Letters, Elsevier, vol. 94(2), pages 235-239, February.
    15. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
    16. Chatzitzisi, Evanthia & Fountas, Stilianos & Panagiotidis, Theodore, 2021. "Another look at calendar anomalies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 823-840.
    17. Gencay, Ramazan & Selcuk, Faruk & Ulugulyagci, Abdurrahman, 2003. "High volatility, thick tails and extreme value theory in value-at-risk estimation," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 337-356, October.
    18. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    19. Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy (IfW Kiel).
    20. Söhnke M. Bartram & Harald Lohre & Peter F. Pope & Ananthalakshmi Ranganathan, 2021. "Navigating the factor zoo around the world: an institutional investor perspective," Journal of Business Economics, Springer, vol. 91(5), pages 655-703, July.
    21. Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
    22. Qadan, Mahmoud & Idilbi-Bayaa, Yasmeen, 2021. "The day-of-the-week-effect on the volatility of commodities," Resources Policy, Elsevier, vol. 71(C).
    23. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    24. Yoon-Jae Whang & Young-Hyun Cho & Oliver Linton, 2006. "Are there Monday effects in Stock Returns: A Stochastic Dominance Approach," FMG Discussion Papers dp568, Financial Markets Group.
    25. Sproule, Robert & Gosselin, Gabriel, 2023. "Is the research agenda for calendar anomalies “much do about nothing”?," MPRA Paper 117001, University Library of Munich, Germany.
    26. Michael D. Hausfeld & Gordon C. Rausser & Gareth J. Macartney & Michael P. Lehmann & Sathya S. Gosselin, 2014. "Antitrust class proceedings – Then and now," Research in Law and Economics, in: The Law and Economics of Class Actions, volume 26, pages 77-133, Emerald Group Publishing Limited.
    27. White, Halbert & Timmermann, Allan & Sullivan, Ryan, 2001. "Forecast Evaluation with Shared Data Sets," CEPR Discussion Papers 3060, C.E.P.R. Discussion Papers.
    28. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    29. Chan, Kam Fong & Gray, Philip & Gray, Stephen & Zhong, Angel, 2020. "Political uncertainty, market anomalies and Presidential honeymoons," Journal of Banking & Finance, Elsevier, vol. 113(C).
    30. Ilias Tsiakas, 2010. "The Economic Gains Of Trading Stocks Around Holidays," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 1-26, March.
    31. David M. Kaplan & Longhao Zhuo, 2017. "Frequentist size of Bayesian inequality tests," Working Papers 1709, Department of Economics, University of Missouri, revised 14 Jul 2019.
    32. Rebecca M. Baker & Tahani Coolen-Maturi & Frank P. A. Coolen, 2017. "Nonparametric predictive inference for stock returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(8), pages 1333-1349, June.
    33. Gleason, Katherine I. & Klock, Mark, 2006. "Intangible capital in the pharmaceutical and chemical industry," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 300-314, May.
    34. Kim, Jae H. & Shamsuddin, Abul, 2023. "Stock market anomalies: An extreme bounds analysis," International Review of Financial Analysis, Elsevier, vol. 90(C).
    35. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.
    36. Cai, Lili & Swanson, Norman R., 2011. "In- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 743-764, September.
    37. Kim-Leng Goh & Kim-Lian Kok, 2006. "Beating the Random Walk: Intraday Seasonality and Volatility in a Developing Stock Market," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 5(1), pages 41-59, April.
    38. Eddie C. M. Hui & Ka Kwan Kevin Chan, 2018. "Testing Calendar Effects of International Equity and Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 56(1), pages 140-158, January.
    39. Ülkü, Numan & Rogers, Madeline, 2018. "Who drives the Monday effect?," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 46-65.
    40. Sven Bouman & Ben Jacobsen, 2002. "The Halloween Indicator, "Sell in May and Go Away": Another Puzzle," American Economic Review, American Economic Association, vol. 92(5), pages 1618-1635, December.
    41. Laurens Swinkels & Pim van Vliet, 2012. "An anatomy of calendar effects," Journal of Asset Management, Palgrave Macmillan, vol. 13(4), pages 271-286, August.
    42. Pesaran, M.H. & Timmermann, A., 2004. "‘Real Time Econometrics’," Cambridge Working Papers in Economics 0432, Faculty of Economics, University of Cambridge.
    43. Bertrand Maillet & Thierry Michel, 2005. "Technical Analysis Profitability when Exchange Rates are Pegged: A Note," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00308979, HAL.
    44. Dragan Tevdovski & Martin Mihajlov & Igor Sazdovski, 2012. "The Day Of The Week Effect In South Eastern Europe Stock Markets," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 3, pages 20-24, September.
    45. Alt, Raimund & Fortin, Ines & Weinberger, Simon, 2011. "The Monday effect revisited: An alternative testing approach," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 447-460, June.
    46. Powell, John G. & Shi, Jing & Smith, Tom & Whaley, Robert E., 2009. "Political regimes, business cycles, seasonalities, and returns," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1112-1128, June.
    47. Joseph P & Romano & Azeem M. Shaikh & Michael Wolf, 2005. "Formalized Data Snooping Based on Generalized Error Rates," IEW - Working Papers 259, Institute for Empirical Research in Economics - University of Zurich.
    48. Oded Galor & Omer Moav, 2005. "Land Inequality and the Origin of Divergence and Overtaking in the Growth Process: Theory and Evidence," 2005 Meeting Papers 24, Society for Economic Dynamics.
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    65. John C. Frain, 2008. "Maximum Likelihood Estimates of Regression Coefficients with alpha-stable residuals and Day of Week effects in Total Returns on Equity Indices," Trinity Economics Papers tep0108, Trinity College Dublin, Department of Economics, revised May 2008.
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    67. Foong Soon Cheong, 2016. "Debunking Two Myths of the Weekend Effect," IJFS, MDPI, vol. 4(2), pages 1-9, April.
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    72. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
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    74. Georgios Bampinas & Stilianos Fountas & Theodore Panagiotidis, 2015. "The day-of-the-week effect is weak: Evidence from the European Real Estate Sector," Discussion Paper Series 2015_02, Department of Economics, University of Macedonia, revised May 2015.
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  47. Perez-Quiros, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 259-306, July.
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  48. Timmermann, Allan, 2001. "Structural Breaks, Incomplete Information, and Stock Prices," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 299-314, July.
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  52. Clive Granger & Allan Timmermann, 1999. "Data mining with local model specification uncertainty: a discussion of Hoover and Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 220-225.

    Cited by:

    1. Teodosio Perez-Amaral & Giampiero M. Gallo & Halbert White, 2003. "Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)," Documentos de Trabajo del ICAE 0309, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Luc, BAUWENS & Genaro, SUCARRAT, 2006. "General to Specific Modelling of Exchange Rate Volatility : a Forecast Evaluation," Discussion Papers (ECON - Département des Sciences Economiques) 2006013, Université catholique de Louvain, Département des Sciences Economiques.
    3. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
    4. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    5. Beenstock, Michael & Szpiro, George, 2002. "Specification search in nonlinear time-series models using the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 811-835, May.
    6. Alvaro Escribano & Genaro Sucarrat, 2011. "Automated model selection in finance: General-to-speci c modelling of the mean and volatility speci cations," Working Papers 2011-09, Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales.
    7. Genaro Sucarrat & Alvaro Escribano, 2012. "Automated Model Selection in Finance: General-to-Specific Modelling of the Mean and Volatility Specifications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(5), pages 716-735, October.
    8. Sucarrat, Genaro, 2009. "Automated financial multi-path GETS modelling," UC3M Working papers. Economics we093620, Universidad Carlos III de Madrid. Departamento de Economía.
    9. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).

  53. Blake, David & Lehmann, Bruce N & Timmermann, Allan, 1999. "Asset Allocation Dynamics and Pension Fund Performance," The Journal of Business, University of Chicago Press, vol. 72(4), pages 429-461, October.

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    1. Stephen Satchell & Wei Xia, 2005. "Estimation of the Risk Attitude of the Representative UK Pension Fund Investor," Birkbeck Working Papers in Economics and Finance 0509, Birkbeck, Department of Economics, Mathematics & Statistics.
    2. Fischer, Andreas M. & Greminger, Rafael P. & Grisse, Christian & Kaufmann, Sylvia, 2021. "Portfolio rebalancing in times of stress," Journal of International Money and Finance, Elsevier, vol. 113(C).
    3. Hamdani, Assaf & Kandel, Eugene & Mugerman, Yevgeny & Yafeh, Yishay, 2017. "Incentive Fees and Competition in Pension Funds: Evidence from a Regulatory Experiment," Journal of Law, Finance, and Accounting, now publishers, vol. 2(1), pages 49-86, June.
    4. Dirk Broeders & Kristy Jansen, 2021. "Pension Funds and Drivers of Heterogeneous Investment Strategies," Working Papers 712, DNB.
    5. Eduardo Roca & Victor Wong, 2008. "An analysis of the sensitivity of Australian superannuation funds to market movements: a Markov regime switching approach," Applied Financial Economics, Taylor & Francis Journals, vol. 18(7), pages 583-597.
    6. Kirsten L. MacDonald & Robert J. Bianchi & Michael E. Drew, 2020. "Equity risk versus retirement adequacy: asset allocation solutions for KiwiSaver," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(4), pages 3851-3873, December.
    7. José Alvarez & Laura Andreu & Cristina Ortiz & José Sarto, 2014. "A nonparametric approach to market timing: evidence from Spanish mutual funds," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(1), pages 119-132, January.
    8. Bijapur, Mohan & Croci, Manuela & Zaidi, Rida, 2012. "Do asset regulations impede portfolio diversification? evidence from European life insurance funds," LSE Research Online Documents on Economics 56618, London School of Economics and Political Science, LSE Library.
    9. Basu, Anup & Drew, Michael, 2006. "Appropriateness of Default Investment Options in Defined Contribution Plans: The Australian Evidence," MPRA Paper 3314, University Library of Munich, Germany, revised 02 Nov 2006.
    10. Akshentseva, Ksenya (Акшенцева, Ксения) & Abramov, Alexander (Абрамов, Александр) & Chernovа, Maria (Чернова, Мария), 2015. "Problems of Formation and Evaluation of Strategies for Portfolio Investment of Pension Reserves, Accruals and Collective Investments in Russia [Проблемы Формирования И Оценки Результативности Страт," Published Papers mn24, Russian Presidential Academy of National Economy and Public Administration.
    11. Lang, Gunnar & Shen, Yu & Xu, Xian, 2014. "Chinese pension fund investment efficiency: Evidence from CNCSSF stock holdings," ZEW Discussion Papers 14-007, ZEW - Leibniz Centre for European Economic Research.
    12. Anastasia Petraki & Anna Zalewska, 2017. "Jumping over a low hurdle: personal pension fund performance," Review of Quantitative Finance and Accounting, Springer, vol. 48(1), pages 153-190, January.
    13. Mercedes Alda, 2021. "The dilemma between fund‐style consistency and active management over the economic cycle. Evidence from pension funds," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2219-2240, April.
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    15. Darolles, Serge & Vaissié, Mathieu, 2012. "The alpha and omega of fund of hedge fund added value," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1067-1078.
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    19. Blake, David & Cairns, Andrew & Dowd, Kevin, 2008. "Turning pension plans into pension planes: What investment strategy designers of defined contribution pension plans can learn from commercial aircraft designers," MPRA Paper 33749, University Library of Munich, Germany.
    20. Dirk W.G.A. Broeders & Damiaan H.J. Chen & Peter A. Minderhoud & C.J. Willem Schudel, 2021. "Pension Funds' Herding," International Journal of Central Banking, International Journal of Central Banking, vol. 17(1), pages 285-330, March.
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    22. Matthew Spiegel & Harry Mamaysky & Hong Zhang, 2005. "Improved Forecasting of Mutual Fund Alphas and Betas," Yale School of Management Working Papers amz2361, Yale School of Management, revised 01 Mar 2006.
    23. Alda, Mercedes & Vicente, Ruth, 2020. "Behavioural analysis of socially responsible investment managers: specialists versus non-specialists," Research in International Business and Finance, Elsevier, vol. 54(C).
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    25. Fabrice Hervé, 2006. "Famille de fonds de pension, performance et persistance de la performance," Working Papers CREGO 1060903, Université de Bourgogne - CREGO EA7317 Centre de recherches en gestion des organisations.
    26. Dariusz Stanko, 2003. "Performance Evaluation of Public Pension Funds: The Reformed Pension System in Poland," Finance 0306002, University Library of Munich, Germany.
    27. Blake, David, 2003. "Financial system requirements for successful pension reform," LSE Research Online Documents on Economics 24862, London School of Economics and Political Science, LSE Library.
    28. Manuel Ammann & Sebastian Fischer & Florian Weigert, 2018. "Risk Factor Exposure Variation and Mutual Fund Performance," Working Papers on Finance 1817, University of St. Gallen, School of Finance, revised Nov 2018.
    29. John Board & Charles Sutcliffe, 2005. "Joined-Up Pensions Policy in the UK: An Asset-Libility Model for Simultaneously Determining the Asset Allocation and Contribution Rate," ICMA Centre Discussion Papers in Finance icma-dp2005-11, Henley Business School, University of Reading.
    30. Jacobs, Heiko & Müller, Sebastian & Weber, Martin, 2014. "How should individual investors diversify? An empirical evaluation of alternative asset allocation policies," Journal of Financial Markets, Elsevier, vol. 19(C), pages 62-85.
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    32. Artiga González, Tanja & van Lelyveld, Iman & Lučivjanská, Katarína, 2020. "Pension fund equity performance: Patience, activity or both?," Journal of Banking & Finance, Elsevier, vol. 115(C).
    33. Manuel Ammann & Christian Ehmann, 2017. "Is Governance Related to Investment Performance and Asset Allocation? Empirical Evidence from Swiss Pension Funds," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 153(3), pages 293-339, July.
    34. Broeders, Dirk & Chen, An, 2010. "Pension regulation and the market value of pension liabilities: A contingent claims analysis using Parisian options," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1201-1214, June.
    35. Lawrence Kryzanowski & Abdul Rahman, 2008. "Portfolio performance ambiguity and benchmark inefficiency revisited," Journal of Asset Management, Palgrave Macmillan, vol. 9(5), pages 321-332, December.
    36. Blake, David, 2003. "The United Kingdom pension system: key issues," LSE Research Online Documents on Economics 24851, London School of Economics and Political Science, LSE Library.
    37. Lehmann, Bruce & Timmermann, Allan, 2007. "Performance measurement and evaluation," LSE Research Online Documents on Economics 24505, London School of Economics and Political Science, LSE Library.
    38. Jiang, George J. & Yao, Tong & Yu, Tong, 2007. "Do mutual funds time the market? Evidence from portfolio holdings," Journal of Financial Economics, Elsevier, vol. 86(3), pages 724-758, December.
    39. Fabrice Hervé, 2006. "Les fonds de pension protègent-ils les investisseurs des évolutions du marché?," Working Papers CREGO 1060101, Université de Bourgogne - CREGO EA7317 Centre de recherches en gestion des organisations.
    40. Clare, Andrew & Sherman, Meadhbh Brid & Thomas, Steve, 2016. "Multi-asset class mutual funds: Can they time the market? Evidence from the US, UK and Canada," Research in International Business and Finance, Elsevier, vol. 36(C), pages 212-221.
    41. Harry Mamaysky & Matthew Spiegel & Hong Zhang, 2008. "Estimating the Dynamics of Mutual Fund Alphas and Betas," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 233-264, January.
    42. Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2010. "Decentralized investment management: evidence from the pension fund industry," MPRA Paper 35767, University Library of Munich, Germany.
    43. Ian Tonks, 2002. "(UBS Pensions Series 1) Performance Persistence of Pension Fund Managers," FMG Discussion Papers dp423, Financial Markets Group.
    44. Al Janabi, Mazin A.M., 2014. "Optimal and investable portfolios: An empirical analysis with scenario optimization algorithms under crisis market prospects," Economic Modelling, Elsevier, vol. 40(C), pages 369-381.
    45. Farah, N. & Satchell, S.E., 2003. "A Loss Aversion Performance Measure," Cambridge Working Papers in Economics 0333, Faculty of Economics, University of Cambridge.
    46. Blake, David & Sarno, Lucio & Zinna, Gabriele, 2017. "The market for lemmings: The herding behavior of pension funds," Journal of Financial Markets, Elsevier, vol. 36(C), pages 17-39.
    47. Anup K. Basu & Michael E. Drew, 2009. "The Case for Gender‐Sensitive Superannuation Plan Design," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 42(2), pages 177-189, June.
    48. Luis Ferruz & Luis Vicente & Laura Andreu, 2009. "Performance persistence and its influence on money and investor flows into Spanish pension plans," Review of Quantitative Finance and Accounting, Springer, vol. 32(1), pages 85-100, January.
    49. Carmen-Pilar Mart¨ª-Ballester, 2012. "A Comparative Analysis of the Performance of Collective Investment Institutions," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 43-52, May.
    50. Keith Cuthbertson & Dirk Nitzsche & Niall O' Sullivan, 2004. "UK Mutual Fund Performance: Genuine Stock-Picking Ability or Luck," Money Macro and Finance (MMF) Research Group Conference 2004 55, Money Macro and Finance Research Group.
    51. MacLean, Leonard & Zhao, Yonggan & Ziemba, William, 2006. "Dynamic portfolio selection with process control," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 317-339, February.
    52. Willie Dion Reddic, 2021. "Under pressure: investment behaviour of insurers under different financial and regulatory conditions," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 46(1), pages 1-20, January.
    53. Ammann, Manuel & Fischer, Sebastian & Weigert, Florian, 2020. "Factor exposure variation and mutual fund performance," CFR Working Papers 20-06, University of Cologne, Centre for Financial Research (CFR).
    54. Victor Soucik & David E. Allen, 2006. "Benchmarking Australian fixed interest fund performance: finding the optimal factors," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 46(5), pages 865-898, December.
    55. Bijapur, Mohan & Croci, Manuela & Zaidi, Rida, 2012. "Do Asset Regulations Impede Portfolio Diversification? Evidence from European Life Insurance Funds," MPRA Paper 54265, University Library of Munich, Germany.
    56. Gökçen, Umut & Yalçın, Atakan, 2015. "The case against active pension funds: Evidence from the Turkish Private Pension System," Emerging Markets Review, Elsevier, vol. 23(C), pages 46-67.
    57. Anastasia Petraki & Anna Zalewska, 2013. "Jumping over a low hurdle: Personal pension fund performance," The Centre for Market and Public Organisation 13/305, The Centre for Market and Public Organisation, University of Bristol, UK.
    58. Daniella Acker & Nigel W. Duck, 2006. "A Tournament Model of Fund Management," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9‐10), pages 1460-1483, November.
    59. Maximilian Vermorken & Marc Gendebien & Alphons Vermorken & Thomas Schröder, 2013. "Skilled monkey or unlucky manager?," Journal of Asset Management, Palgrave Macmillan, vol. 14(5), pages 267-277, October.
    60. Christoph Gort & Mei Wang, 2010. "Overconfidence and Active Management," Chapters, in: Brian Bruce (ed.), Handbook of Behavioral Finance, chapter 12, Edward Elgar Publishing.
    61. Gordon L. Clark & Emiko Caerlewy‐Smith & John C. Marshall, 2009. "Solutions to the Asset Allocation Problem by Informed Respondents: The Significance of the Size‐of‐Bet and the 1/N Heuristic," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 12(2), pages 251-271, September.
    62. Brown, Keith C. & Garlappi, Lorenzo & Tiu, Cristian, 2010. "Asset allocation and portfolio performance: Evidence from university endowment funds," Journal of Financial Markets, Elsevier, vol. 13(2), pages 268-294, May.
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    1. Costello, Greg & Fraser, Patricia & Groenewold, Nicolaas, 2011. "House prices, non-fundamental components and interstate spillovers: The Australian experience," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 653-669, March.
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  55. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.

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    6. M. Hashem Pesaran, 2000. "The Cost Efficiency of UK Debt Management: A Recursive Modelling Approach," CESifo Working Paper Series 346, CESifo.
    7. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    8. Fernandez, Pablo & Aguirreamalloa, Javier & Liechtenstein, Heinrich, 2009. "The equity premium puzzle: High required equity premium, undervaluation and self fulfilling prophecy," IESE Research Papers D/821, IESE Business School.
    9. Paz-Pardo, Gonzalo, 2021. "Homeownership and portfolio choice over the generations," Working Paper Series 2522, European Central Bank.
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    11. Tarek Zaher, 2017. "The Value of Active Investment Strategies," NFI Working Papers 2017-WP-02, Indiana State University, Scott College of Business, Networks Financial Institute.
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    390. Bekiros, S. & Georgoutsos, D., 2006. "Direction-of-Change Forecasting using a Volatility- Based Recurrent Neural Network," CeNDEF Working Papers 06-16, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    391. Pierdzioch, Christian & Schertler, Andrea, 2005. "Investing in European Stock Markets for High-Technology Firms," Kiel Working Papers 1265, Kiel Institute for the World Economy (IfW Kiel).
    392. Chevapatrakul, Thanaset, 2013. "Return sign forecasts based on conditional risk: Evidence from the UK stock market index," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2342-2353.
    393. Benink, Harald A. & Gordillo, José Luis & Pardo, Juan Pablo & Stephens, Christopher R., 2010. "Market efficiency and learning in an artificial stock market: A perspective from Neo-Austrian economics," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 668-688, September.
    394. dos Santos Maciel, Leandro, 2023. "Brazilian stock-market efficiency before and after COVID-19: The roles of fractality and predictability," Global Finance Journal, Elsevier, vol. 58(C).
    395. Bhandari, Avishek, 2020. "Long memory and fractality among global equity markets: A multivariate wavelet approach," MPRA Paper 99653, University Library of Munich, Germany.
    396. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal.
    397. Steven Y. K. Wong & Jennifer Chan & Lamiae Azizi & Richard Y. D. Xu, 2020. "Time-varying neural network for stock return prediction," Papers 2003.02515, arXiv.org, revised Jan 2021.
    398. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
    399. Driffill John & Kenc Turalay & Sola Martin & Spagnolo Fabio, 2009. "The Effects of Different Parameterizations of Markov-Switching in a CIR Model of Bond Pricing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-24, March.
    400. Christos Avdoulas & Stelios Bekiros, 2018. "Nonlinear Forecasting of Euro Area Industrial Production Using Evolutionary Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 521-530, August.
    401. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578, April.
    402. Schnaubelt, Matthias & Seifert, Oleg, 2020. "Valuation ratios, surprises, uncertainty or sentiment: How does financial machine learning predict returns from earnings announcements?," FAU Discussion Papers in Economics 04/2020, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    403. Shangkun Deng & Kazuki Yoshiyama & Takashi Mitsubuchi & Akito Sakurai, 2015. "Hybrid Method of Multiple Kernel Learning and Genetic Algorithm for Forecasting Short-Term Foreign Exchange Rates," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 49-89, January.
    404. Giannetti, A., 2007. "The short term predictive ability of earnings-price ratios: The recent evidence (1994-2003)," The Quarterly Review of Economics and Finance, Elsevier, vol. 47(1), pages 26-39, March.
    405. Cooper, Michael J. & Jackson, William III & Patterson, Gary A., 2003. "Evidence of predictability in the cross-section of bank stock returns," Journal of Banking & Finance, Elsevier, vol. 27(5), pages 817-850, May.
    406. Snudden, Stephen, 2018. "Targeted growth rates for long-horizon crude oil price forecasts," International Journal of Forecasting, Elsevier, vol. 34(1), pages 1-16.
    407. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    408. Liam Gallagher, 1999. "A multi-country analysis of the temporary and permanent components of stock prices," Applied Financial Economics, Taylor & Francis Journals, vol. 9(2), pages 129-142.
    409. Anthony Garratt & Kevin Lee, 2006. "Investing Under Model Uncertainty: Decision Based Evaluation of Exchange Rate and Interest Rate Forecasts in the US, UK and Japan," Birkbeck Working Papers in Economics and Finance 0616, Birkbeck, Department of Economics, Mathematics & Statistics.
    410. David R Gallagher & Peter A Gardner & Camille H Schmidt, 2015. "Style factor timing: An application to the portfolio holdings of US fund managers," Australian Journal of Management, Australian School of Business, vol. 40(2), pages 318-350, May.
    411. Shamsuddin, Abul F. M. & Hillier, John R., 2004. "Fundamental determinants of the Australian price-earnings multiple," Pacific-Basin Finance Journal, Elsevier, vol. 12(5), pages 565-576, November.
    412. Hartmann, Daniel & Pierdzioch, Christian, 2007. "Exchange rates, interventions, and the predictability of stock returns in Japan," Journal of Multinational Financial Management, Elsevier, vol. 17(2), pages 155-172, April.

  56. Timmermann, Allan, 1995. "Cointegration Tests of Present Value Models with a Time-Varying Discount Factor," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 17-31, Jan.-Marc.

    Cited by:

    1. Yen-Hsiao Chen & Lianfeng Quan, 2013. "Rational speculative bubbles in the Asian stock markets: Tests on deterministic explosive bubbles and stochastic explosive root bubbles," Journal of Asset Management, Palgrave Macmillan, vol. 14(3), pages 195-208, June.
    2. Bohl, Martin T. & Siklos, Pierre L., 2004. "The present value model of U.S. stock prices redux: a new testing strategy and some evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 208-223, May.
    3. Nélson Leitão Paes & Cássio Da Nóbrega Besarria & Marcelo Eduardo Alves Da Silva, 2018. "Bubbles In The Prices Of Housing? Evidence To Brazil?S Economy," Anais do XLIV Encontro Nacional de Economia [Proceedings of the 44th Brazilian Economics Meeting] 118, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    4. Engsted, Tom & Hviid, Simon J. & Pedersen, Thomas Q., 2016. "Explosive bubbles in house prices? Evidence from the OECD countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 14-25.
    5. A. Durre & P. Giot, 2007. "An International Analysis of Earnings, Stock Prices and Bond Yields," Post-Print hal-00171145, HAL.
    6. Ky-Hyang Yuhn & Sang Bong Kim & Joo Ha Nam, 2015. "Bubbles and the Weibull distribution: was there an explosive bubble in US stock prices before the global economic crisis?," Applied Economics, Taylor & Francis Journals, vol. 47(3), pages 255-271, January.
    7. Ye, Yonggang & Chang, Tsangyao & Hung, Ken & Lu, Yang-Cheng, 2011. "Revisiting rational bubbles in the G-7 stock markets using the Fourier unit root test and the nonparametric rank test for cointegration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(2), pages 346-357.
    8. Gallagher, Liam A & Taylor, Mark P, 2001. "Risky Arbitrage, Limits of Arbitrage, and Nonlinear Adjustment in the Dividend-Price Ratio," Economic Inquiry, Western Economic Association International, vol. 39(4), pages 524-536, October.
    9. Edward Bernard Bastiaan de Rivera y Rivera & Diógenes Manoel Leiva Martin & Emerson Fernandes Marçal & Leonardo Fernando Cruz Basso, 2012. "Present value model between prices and dividends with constant and time-varying expected returns: enterprise-level Brazilian stock market evidence from non-stationary panels," Brazilian Business Review, Fucape Business School, vol. 9(4), pages 51-86, October.
    10. Ripamonti, Alexandre, 2016. "Corwin-Schultz bid-ask spread estimator in the Brazilian stock market," MPRA Paper 79459, University Library of Munich, Germany.
    11. Priestley, Richard, 2001. "Time-varying persistence in expected returns," Journal of Banking & Finance, Elsevier, vol. 25(7), pages 1271-1286, July.
    12. Wang, Peijie & Brand, Steven, 2015. "A new approach to estimating value–income ratios with income growth and time-varying yields," European Journal of Operational Research, Elsevier, vol. 242(1), pages 182-187.
    13. Tsangyao Chang & Wen-Chi Liu, 2008. "Rational Bubbles in the Korea Stock Market? Further Evidence based on Nonlinear and Nonparametric Cointegration Tests," Economics Bulletin, AccessEcon, vol. 3(34), pages 1-12.
    14. Onour, Ibrahim, 2009. "Rational bubbles and volatility persistence in India stock market," MPRA Paper 18545, University Library of Munich, Germany.
    15. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    16. GIOT, Pierre & PETITJEAN, Mikael, 2006. "The information content of the Bond-Equity Yield Ratio: better than a random walk?," LIDAM Discussion Papers CORE 2006089, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Bohl, Martin T., 2003. "Periodically collapsing bubbles in the US stock market?," International Review of Economics & Finance, Elsevier, vol. 12(3), pages 385-397.
    18. Binswanger, Mathias, 2004. "Stock returns and real activity in the G-7 countries: did the relationship change during the 1980s?," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 237-252, May.
    19. Ullah, Irfan & Ahmed, Mumtaz, 2021. "Identifying Phases of Ebullience in EFTA Stock Markets," MPRA Paper 109633, University Library of Munich, Germany.
    20. Vyacheslav Mikhed & Petr Zemcik, 2007. "Do House Prices Reflect Fundamentals? Aggregate and Panel Data Evidence," CERGE-EI Working Papers wp337, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    21. J. Cunado & L. A. Gil-Alana & F. Perez de Gracia, 2007. "Testing for stock market bubbles using nonlinear models and fractional integration," Applied Financial Economics, Taylor & Francis Journals, vol. 17(16), pages 1313-1321.
    22. Ripamonti, Alexandre, 2020. "Financial institutions, asymmetric information and capital structure adjustments," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 75-83.
    23. Engsted, Tom, 2006. "Explosive bubbles in the cointegrated VAR model," Finance Research Letters, Elsevier, vol. 3(2), pages 154-162, June.
    24. Cunado, J. & Gil-Alana, L.A. & de Gracia, F. Perez, 2005. "A test for rational bubbles in the NASDAQ stock index: A fractionally integrated approach," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2633-2654, October.
    25. Christophe Boucher, 2003. "Stock Market Valuation : the Role of the Macroeconomic Risk Premium," Finance 0305011, University Library of Munich, Germany.
    26. Glen Donaldson & Mark Kamstra & Lisa Kramer, 2003. "Stare down the barrel and center the crosshairs: Targeting the ex ante equity premium," FRB Atlanta Working Paper 2003-4, Federal Reserve Bank of Atlanta.
    27. Alexandre Ripamonti & Raphael Videira & Denis Ichimura, 2020. "Asymmetric information and daily stock prices in Brazil," Estudios Gerenciales, Universidad Icesi, vol. 36(157), pages 465-472, December.
    28. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    29. Nasseh, Alireza & Strauss, Jack, 2000. "Stock prices and domestic and international macroeconomic activity: a cointegration approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(2), pages 229-245.
    30. John Goddard & David Mcmillan & John Wilson, 2008. "Dividends, prices and the present value model: firm-level evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 14(3), pages 195-210.
    31. Kanas, Angelos, 2005. "Nonlinearity in the stock price-dividend relation," Journal of International Money and Finance, Elsevier, vol. 24(4), pages 583-606, June.
    32. Fanelli, Luca, 2002. "A new approach for estimating and testing the linear quadratic adjustment cost model under rational expectations and I(1) variables," Journal of Economic Dynamics and Control, Elsevier, vol. 26(1), pages 117-139, January.
    33. Nasseh, Alireza & Strauss, Jack, 2004. "Stock prices and the dividend discount model: did their relation break down in the 1990s?," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 191-207, May.

  57. Timmermann, Allan, 1994. "Present value models with feedback : Solutions, stability, bubbles, and some empirical evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 18(6), pages 1093-1119, November.

    Cited by:

    1. Roman Frydman & Michael Goldberg & Nicholas Mangee, 2015. "New Evidence for the Present-Value Model of Stock Prices: Why the REH Version Failed Empirically," Working Papers Series 2, Institute for New Economic Thinking.
    2. William R. Parke & George A. Waters, 2011. "On the Evolutionary Stability of Rational Expectations," Working Paper Series 20111002, Illinois State University, Department of Economics.
    3. Dimitris Georgoutsos & Georgios Kouretas, 2004. "A Multivariate I(2) cointegration analysis of German hyperinflation," Applied Financial Economics, Taylor & Francis Journals, vol. 14(1), pages 29-41.
    4. Boyan Jovanovic, 2007. "Bubbles in Prices of Exhaustible Resources," NBER Working Papers 13320, National Bureau of Economic Research, Inc.
    5. Parke, William R. & Waters, George A., 2007. "An evolutionary game theory explanation of ARCH effects," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2234-2262, July.
    6. Fanelli, Luca, 2006. "Multi-equational linear quadratic adjustment cost models with rational expectations and cointegration," Journal of Economic Dynamics and Control, Elsevier, vol. 30(3), pages 445-456, March.
    7. Burda, Michael C., 2021. "Valuing cryptocurrencies: Three easy pieces," IRTG 1792 Discussion Papers 2021-011, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Brandt, M.W.Michael W. & Zeng, Qi & Zhang, Lu, 2004. "Equilibrium stock return dynamics under alternative rules of learning about hidden states," Journal of Economic Dynamics and Control, Elsevier, vol. 28(10), pages 1925-1954, September.
    9. Fanelli, Luca, 2007. "Present Value Relations, Granger Noncausality, And Var Stability," Econometric Theory, Cambridge University Press, vol. 23(6), pages 1254-1260, December.
    10. Krishnamoorthy Charith & Andrey Davydenko, 2021. "Informational Value of Dividend Initiations: Impact of Cash Dividends on Share Prices of Manufacturing Companies in Sri Lanka," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(3), pages 1-13, March.
    11. Andrey Davydenko & Krishnamoorthy Charith, 2021. "Informationswert von Dividendenausschüttungen: Einfluss von Bardividenden auf die Aktienkurse von produzierenden Unternehmen in Sri Lanka [Informational value of dividend initiations: Impact of cas," Post-Print hal-03359177, HAL.
    12. Sirnes, Espen, 1997. "Theories and Tests for Bubbles," MPRA Paper 53464, University Library of Munich, Germany, revised 1997.
    13. Fanelli, Luca, 2002. "A new approach for estimating and testing the linear quadratic adjustment cost model under rational expectations and I(1) variables," Journal of Economic Dynamics and Control, Elsevier, vol. 26(1), pages 117-139, January.

  58. Pesaran, M. Hashem & Timmermann, Allan G., 1994. "A generalization of the non-parametric Henriksson-Merton test of market timing," Economics Letters, Elsevier, vol. 44(1-2), pages 1-7.
    See citations under working paper version above.
  59. Timmermann, Allan, 1994. "Why do dividend yields forecast stock returns?," Economics Letters, Elsevier, vol. 46(2), pages 149-158, October.

    Cited by:

    1. Fredj Jawadi, 2009. "Essay in dividend modelling and forecasting: does nonlinearity help?," Applied Financial Economics, Taylor & Francis Journals, vol. 19(16), pages 1329-1343.

  60. Timmermann, Allan, 1994. "Can Agents Learn to Form Rational Expectations? Some Results on Convergence and Stability of Learning in the UK Stock Market," Economic Journal, Royal Economic Society, vol. 104(425), pages 777-797, July.

    Cited by:

    1. George W. Evans, 2011. "Comment on "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing"," NBER Chapters, in: NBER Macroeconomics Annual 2011, Volume 26, pages 61-71, National Bureau of Economic Research, Inc.
    2. Kapetanios, George & Mitchell, James & Shin, Yongcheol, 2014. "A nonlinear panel data model of cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 179(2), pages 134-157.
    3. Barucci, Emilio & Landi, Leonardo, 1996. "Speculative dynamics with bounded rationality learning," European Journal of Operational Research, Elsevier, vol. 91(2), pages 284-300, June.
    4. Sampson, Michael, 2003. "New Eras and Stock Market Bubbles," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 297-315, September.
    5. George W. Evans, 2012. "Comment," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 61-71.
    6. Rotheli, Tobias F., 2001. "Acquisition of costly information: an experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 46(2), pages 193-208, October.
    7. Basdevant, Olivier, 2005. "Learning process and rational expectations: An analysis using a small macro-economic model for New Zealand," Economic Modelling, Elsevier, vol. 22(6), pages 1074-1089, December.
    8. Shively, Philip A., 2007. "Asymmetric temporary and permanent stock-price innovations," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 120-130, January.
    9. Massimo Guidolin, 2013. "Markov switching models in asset pricing research," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 1, pages 3-44, Edward Elgar Publishing.
    10. Branch, William A. & Evans, George W., 2010. "Learning about Risk and Return: A Simple Model of Bubbles and Crashes," SIRE Discussion Papers 2010-33, Scottish Institute for Research in Economics (SIRE).

  61. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    See citations under working paper version above.

Chapters

  1. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.

    Cited by:

    1. Maurin, Laurent & Drechsel, Katja, 2008. "Flow of conjunctural information and forecast of euro area economic activity," Working Paper Series 925, European Central Bank.
    2. Bergemann, Dirk & Ottaviani, Marco, 2021. "Information Markets and Nonmarkets," CEPR Discussion Papers 16459, C.E.P.R. Discussion Papers.
    3. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    4. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    5. Kakuho Furukawa & Ryohei Hisano & Yukio Minoura & Tomoyuki Yagi, 2022. "A Nowcasting Model of Industrial Production using Alternative Data and Machine Learning Approaches," Bank of Japan Working Paper Series 22-E-16, Bank of Japan.
    6. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    7. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    8. Stylianos Asimakopoulos & Joan Paredes & Thomas Warmedinger, 2020. "Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(1), pages 369-390, January.
    9. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    10. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    11. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
    12. Carlo Altavilla & Matteo Ciccarelli, 2006. "Inflation Forecasts, Monetary Policy and Unemployment Dynamics: Evidence from the US and the Euro Area," Discussion Papers 7_2006, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
    13. Yannick Viossat & Andriy Zapechelnyuk, 2013. "No-regret Dynamics and Fictitious Play," Post-Print hal-00713871, HAL.
    14. Lee, Kevin & Olekalns, Nils & Shields, Kalvinder, 2009. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real-Time Data are Available," CEPR Discussion Papers 7426, C.E.P.R. Discussion Papers.
    15. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    16. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
    17. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    18. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    19. Michael D. Bordo & Pierre Siklos, 2019. "The Transformation and Performance of Emerging Market Economies Across the Great Divide of the Global Financial Crisis," NBER Working Papers 26342, National Bureau of Economic Research, Inc.
    20. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    21. Narayan Kundan Kishor, 2021. "Forecasting real‐time economic activity using house prices and credit conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 213-227, March.
    22. Menkhoff, Lukas & Sakha, Sahra, 2017. "Estimating risky behavior with multiple-item risk measures," Journal of Economic Psychology, Elsevier, vol. 59(C), pages 59-86.
    23. Barbara Annicchiarico & Fabio Di Dio & Francesca Diluiso, 2022. "Climate Actions, Market Beliefs and Monetary Policy," CEIS Research Paper 535, Tor Vergata University, CEIS, revised 25 Mar 2022.
    24. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    25. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    26. Ghysels, Eric & Ozkan, Nazire, 2015. "Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1009-1020.
    27. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    28. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    29. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    30. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    31. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    32. Matteo Manera & Massimiliano Serati & Michele Plotegher, 2008. "Modeling Electricity Prices: From the State of the Art to a Draft of a New Proposal," Working Papers 2008.9, Fondazione Eni Enrico Mattei.
    33. Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    34. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    35. Wilson, Kevin J., 2017. "An investigation of dependence in expert judgement studies with multiple experts," International Journal of Forecasting, Elsevier, vol. 33(1), pages 325-336.
    36. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    37. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
    38. Winkelried, Diego, 2012. "Predicting quarterly aggregates with monthly indicators," Working Papers 2012-023, Banco Central de Reserva del Perú.
    39. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    40. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    41. Luis Fernando Melo & Rubén Albeiro Loaiza Maya, 2012. "Bayesian Forecast Combination for Inflation Using Rolling Windows: An Emerging Country Case," Borradores de Economia 9511, Banco de la Republica.
    42. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.
    43. Florian Eckert & Rob J Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports Using Bayesian Forecast Reconciliation," Monash Econometrics and Business Statistics Working Papers 14/19, Monash University, Department of Econometrics and Business Statistics.
    44. Peter Christoffersen & Jeremy Berkowitz & Denis Pelletier, 2008. "Evaluating Value-at-Risk Models with Desk-Level Data," CREATES Research Papers 2009-35, Department of Economics and Business Economics, Aarhus University.
    45. Clements, Michael P., 2010. "Why are survey forecasts superior to model forecasts?," The Warwick Economics Research Paper Series (TWERPS) 954, University of Warwick, Department of Economics.
    46. Schrimpf, Andreas, 2008. "International Stock Return Predictability Under Model Uncertainty," ZEW Discussion Papers 08-048, ZEW - Leibniz Centre for European Economic Research.
    47. WAN, Shui-Ki & WANG, Shin-Huei & WOO, Chi-Keung, 2012. "Total tourist arrival forecast: aggregation vs. disaggregation," LIDAM Discussion Papers CORE 2012039, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    48. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
    49. Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
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