The Evaluation of Economic Forecasts

Citations

Cited by:

1. Jose A. Lopez & Christian Walter, 1997. "Is implied correlation worth calculating? Evidence from foreign exchange options and historical data," Research Paper 9730, Federal Reserve Bank of New York.
   • Jose A. Lopez & Christian Walter, 2000. "Is implied correlation worth calculating? Evidence from foreign exchange options and historical data," Working Paper Series 2000-02, Federal Reserve Bank of San Francisco.
2. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
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.
   • López Moctezuma Gabriel & Capistrán Carlos, 2010. "Forecast Revisions of Mexican Inflation and GDP Growth," Working Papers 2010-11, Banco de México.
4. 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.
   • Alain Hecq & Jan P.A.M. Jacobs & Michalis P. Stamatogiannis, 2016. "Testing for News and Noise in Non-Stationary Time Series Subject to Multiple Historical Revisions," CIRANO Working Papers 2016s-01, CIRANO.
   • Hecq, A.W. & Jacobs, J.P.A.M. & Stamatogiannis, M., 2016. "Testing for news and noise in non-stationary time series subject to multiple historical revisions," Research Memorandum 004, Maastricht University, Graduate School of Business and Economics (GSBE).
5. Becker, Ralf & Clements, Adam E., 2008. "Are combination forecasts of S&P 500 volatility statistically superior?," International Journal of Forecasting, Elsevier, vol. 24(1), pages 122-133.
   • Ralf Becker & Adam Clements, 2007. "Are combination forecasts of S&P 500 volatility statistically superior?," NCER Working Paper Series 17, National Centre for Econometric Research.
6. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
7. 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.
   • Wieland, Volker & Wolters, Maik Hendrik, 2012. "Forecasting and policy making," IMFS Working Paper Series 62, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
8. McMillan, David G., 2009. "The confusing time-series behaviour of real exchange rates: Are asymmetries important?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 692-711, October.
9. Benchimol, Jonathan & El-Shagi, Makram & Saadon, Yossi, 2022. "Do expert experience and characteristics affect inflation forecasts?," Journal of Economic Behavior & Organization, Elsevier, vol. 201(C), pages 205-226.
   • Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," CFDS Discussion Paper Series 2020/6, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
   • 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.
   • Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2022. "Do expert experience and characteristics affect inflation forecasts?," Post-Print emse-04624966, HAL.
10. Carola Conces Binder & Rodrigo Sekkel, 2024. "Central bank forecasting: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 342-364, April.
    • Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
11. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    • David Hendry & Michael P. Clements, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Papers 2002-W11, Economics Group, Nuffield College, University of Oxford.
    • Clements, Michael P. & Hendry, David F., 2001. "Economic forecasting: some lessons from recent research," Working Paper Series 82, European Central Bank.
    • Hendry, David F & Michael P. Clements, 2002. "Economic Forecasting: Some Lessons from Recent Research," Royal Economic Society Annual Conference 2002 99, Royal Economic Society.
    • David Hendry & Michael P. Clements & Department of Economics & University of Warwick, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Series Working Papers 78, University of Oxford, Department of Economics.
12. N. Antonakakis & J. Darby, 2013. "Forecasting volatility in developing countries' nominal exchange returns," Applied Financial Economics, Taylor & Francis Journals, vol. 23(21), pages 1675-1691, November.
    • Antonakakis, Nikolaos & Darby, Julia, 2012. "Forecasting Volatility in Developing Countries' Nominal Exchange Returns," MPRA Paper 40875, University Library of Munich, Germany.
13. repec:imd:wpaper:wp2010-25 is not listed on IDEAS
14. Oliver Merz & Raphael Flepp & Egon Franck, 2019. "Does sentiment harm market efficiency? An empirical analysis using a betting exchange setting," Working Papers 381, University of Zurich, Department of Business Administration (IBW).
15. 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.
    • Allan Timmermann & Graham Elliott & Ivana Komunjer, 2004. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Econometric Society 2004 North American Summer Meetings 601, Econometric Society.
    • Graham Elliott & Ivana Komunjer & Allan Timmermann, 2005. "Biases In Macroeconomic Forecasts: Irrationality Or Asymmetric Loss?," CAMA Working Papers 2005-14, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
16. 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.
    • Pincheira, Pablo & Hardy, Nicolas, 2022. "Correlation Based Tests of Predictability," MPRA Paper 112014, University Library of Munich, Germany.
17. Long H. Vo, 2017. "Estimating Financial Volatility with High-Frequency Returns," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(2), pages 84-114, October.
18. Pedersen, Michael, 2015. "What affects the predictions of private forecasters? The role of central bank forecasts in Chile," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1043-1055.
19. Do, Linh Phuong Catherine & Lin, Kuan-Heng & Molnár, Peter, 2016. "Electricity consumption modelling: A case of Germany," Economic Modelling, Elsevier, vol. 55(C), pages 92-101.
20. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, "undated". "Evaluating Density Forecasts," CARESS Working Papres 97-18, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
    • Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," Center for Financial Institutions Working Papers 97-37, Wharton School Center for Financial Institutions, University of Pennsylvania.
    • Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating density forecasts," Working Papers 97-6, Federal Reserve Bank of Philadelphia.
    • Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," NBER Technical Working Papers 0215, National Bureau of Economic Research, Inc.
21. Carlos Díaz, 2018. "Extracting information shocks from the Bank of England inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(3), pages 316-326, April.
    • Carlos Diaz Vela, 2016. "Extracting the Information Shocks from the Bank of England Inflation Density Forecasts," Discussion Papers in Economics 16/13, Division of Economics, School of Business, University of Leicester.
22. Jan Jacobs & Jan-Egbert Sturm, 2009. "The information content of KOF indicators on Swiss current account data revisions," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(2), pages 161-181.
    • Jan Jacobs & Jan-Egbert Sturm, 2008. "The Information Content of KOF Indicators on Swiss Current Account Data Revisions," CESifo Working Paper Series 2370, CESifo.
    • Jan P.A.M. Jacobs & Jan-Egbert Sturm, 2008. "The information content of KOF indicators on Swiss current account data revisions," KOF Working papers 08-202, KOF Swiss Economic Institute, ETH Zurich.
23. Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
24. 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.
25. Eicher, Theo S. & Kawai, Reina, 2024. "Systemic bias of IMF reserve and debt forecasts for program countries," International Journal of Forecasting, Elsevier, vol. 40(3), pages 985-1001.
26. Malte Knuppel & Fabian Kruger & Marc-Oliver Pohle, 2022. "Score-based calibration testing for multivariate forecast distributions," Papers 2211.16362, arXiv.org, revised Dec 2023.
    • Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
27. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
28. Christina Ziegler, 2009. "Testing Predicitive Ability of Business Cycle Indicators for the Euro Area," ifo Working Paper Series 69, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
29. Helder Ferreira de Mendonça & João Pedro Neves Maia, 2022. "Interest rate expectations based on Taylor rule versus central bank’s survey: which performs better in a large emerging economy?," Applied Economics, Taylor & Francis Journals, vol. 54(39), pages 4532-4544, August.
30. Malte Knüppel & Guido Schultefrankenfeld, 2012. "How Informative Are Central Bank Assessments of Macroeconomic Risks?," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 87-139, September.
    • Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "How informative are central bank assessments of macroeconomic risks?," Discussion Paper Series 1: Economic Studies 2011,13, Deutsche Bundesbank.
31. repec:kap:iaecre:v:14:y:2008:i:1:p:112-124 is not listed on IDEAS
32. J. Scott Armstrong & Michael C. Grohman, 1972. "A Comparative Study of Methods for Long-Range Market Forecasting," Management Science, INFORMS, vol. 19(2), pages 211-221, October.
    • Armstrong, J. Scott & C., Michael, 1972. "A Comparative Study of Methods for Long-Range Market Forecasting," MPRA Paper 81673, University Library of Munich, Germany.
    • JS Armstrong & Michael C. Grohman, 2004. "A Comparative Study of Methods for Long-Range Market Forecasting," General Economics and Teaching 0412010, University Library of Munich, Germany.
33. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, vol. 32(2), pages 571-583.
    • Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," Working Papers 2015-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    • Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
34. Dilip Kumar, 2016. "Sudden changes in crude oil price volatility: an application of extreme value volatility estimator," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 4(3/4), pages 215-234.
35. Katharina Glass & Ulrich Fritsche, 2015. "Real-time Macroeconomic Data and Uncertainty," Macroeconomics and Finance Series 201406, University of Hamburg, Department of Socioeconomics.
36. Pascal Bührig & Klaus Wohlrabe, 2015. "Revisionen der deutschen Industrieproduktion und die ifo Indikatoren," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(21), pages 27-31, November.
37. Jozef Barunik & Lukas Vacha, 2015. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1347-1364, August.
    • Jozef Barunik & Lukas Vacha, 2012. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Papers 1202.1854, arXiv.org, revised Feb 2013.
    • Baruník, Jozef & Vácha, Lukáš, 2014. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," FinMaP-Working Papers 16, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
38. Lise Pichette & Marie-Noëlle Robitaille, 2017. "Assessing the Business Outlook Survey Indicator Using Real-Time Data," Discussion Papers 17-5, Bank of Canada.
39. Baris Soybilgen & Ege Yazgan, 2017. "An evaluation of inflation expectations in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 17(1), pages 1-31–38.
    • Baris Soybilgen & Ege Yazgan, 2016. "An Evaluation Of Inflation Expectations In Turkey," Working Papers 1601, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
40. Panopoulou, Ekaterini & Pantelidis, Theologos, 2015. "Speculative behaviour and oil price predictability," Economic Modelling, Elsevier, vol. 47(C), pages 128-136.
    • Ekaterini Panopoulou & Theologos Pantelidis, 2014. "Speculative behaviour and oil price predictability," Discussion Paper Series 2014_09, Department of Economics, University of Macedonia, revised Dec 2014.
41. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    • Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
42. Busch, Thomas & Christensen, Bent Jesper & Nielsen, Morten Ørregaard, 2011. "The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets," Journal of Econometrics, Elsevier, vol. 160(1), pages 48-57, January.
    • Thomas Busch & Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007. "The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets," CREATES Research Papers 2007-09, Department of Economics and Business Economics, Aarhus University.
    • Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
43. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
44. 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.
45. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    • Barbara Rossi, 2013. "Exchange Rate Predictability," Working Papers 690, Barcelona School of Economics.
    • Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers 1369, Department of Economics and Business, Universitat Pompeu Fabra.
    • Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
46. Pericoli, Marcello & Taboga, Marco, 2012. "Bond risk premia, macroeconomic fundamentals and the exchange rate," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 42-65.
    • Taboga, Marco & Pericoli, Marcello, 2008. "Bond risk premia, macroeconomic fundamentals and the exchange rate," MPRA Paper 9523, University Library of Munich, Germany.
    • Marcello Pericoli & Marco Taboga, 2009. "Bond risk premia, macroeconomic fundamentals and the exchange rate," Temi di discussione (Economic working papers) 699, Bank of Italy, Economic Research and International Relations Area.
47. J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
    • J. James Reade & Carl Singleton & Leighton Vaughan Williams, 2020. "Betting markets for English Premier League results and scorelines: evaluating a forecasting model," Economics Discussion Papers em-dp2020-03, Department of Economics, University of Reading.
48. Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.
49. Bouwman, Kees E. & Jacobs, Jan P.A.M., 2011. "Forecasting with real-time macroeconomic data: The ragged-edge problem and revisions," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 784-792.
    • Bouwman, Kees E. & Jacobs, Jan P.A.M., 2005. "Forecasting with real-time macroeconomic data: the ragged-edge problem and revisions," CCSO Working Papers 200505, University of Groningen, CCSO Centre for Economic Research.
50. Silvia Muzzioli & Luca Gambarelli & Bernard De Baets, 2018. "Indices for Financial Market Volatility Obtained Through Fuzzy Regression," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1659-1691, November.
51. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    • Tara M. Sinclair & H.O. Stekler, 2011. "Examining the Quality of Early GDP Component Estimates," Working Papers 2011-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Dec 2011.
52. 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.
    • WANG, Shin-Huei & BAUWENS, Luc & HSIAO, Cheng, 2012. "Forecasting long memory processes subject to structural breaks," LIDAM Discussion Papers CORE 2012048, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • WANG, Cindy Shin-Huei & BAUWENS, Luc & HSIAO, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," LIDAM Reprints CORE 2574, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
53. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37/2017, Bank of Finland.
    • Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37, Bank of Finland.
54. 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.
55. John W. Freebairn, 1975. "Forecasting For Australian Agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 19(3), pages 154-174, December.
    • Freebairn, John W., 1975. "Forecasting For Australian Agriculture," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 19(3), pages 1-21, December.
56. Pablo Pincheira B. & Nicolás Fernández, 2011. "Jaque Mate a las Proyecciones de Consenso," Working Papers Central Bank of Chile 630, Central Bank of Chile.
57. Barbara Rossi & Tatevik Sekhposyan, 2016. "Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 507-532, April.
    • 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.
    • Barbara Rossi & Tatevik Sekhposyany, 2014. "Forecast Rationality Tests in the Presence of Instabilities, With Applications to Federal Reserve and Survey Forecasts," Working Papers 765, Barcelona School of Economics.
    • Rossi, Barbara & Sekhposyan, Tatevik, 2016. "Forecast Rationality Tests in the Presence of Instabilities, With Applications to Federal Reserve and Survey Forecasts," CEPR Discussion Papers 11391, C.E.P.R. Discussion Papers.
58. Luo, Xingguo & Ye, Zinan, 2015. "Predicting volatility of the Shanghai silver futures market: What is the role of the U.S. options market?," Finance Research Letters, Elsevier, vol. 15(C), pages 68-77.
59. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.
60. 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.
61. Stanislav Bozhkov & Habin Lee & Uthayasankar Sivarajah & Stella Despoudi & Monomita Nandy, 2020. "Idiosyncratic risk and the cross-section of stock returns: the role of mean-reverting idiosyncratic volatility," Annals of Operations Research, Springer, vol. 294(1), pages 419-452, November.
62. Clemens J. M. Kool & Daniel L. Thornton, 2015. "How Effective Is Central Bank Forward Guidance?," Review, Federal Reserve Bank of St. Louis, vol. 97(4), pages 303-322.
    • Clemens J. M. Kool & Daniel L. Thornton, 2012. "How effective is central bank forward guidance?," Working Papers 2012-063, Federal Reserve Bank of St. Louis.
    • Clemens J. M. Kool Author-Name-First Clemens J. M. & Daniel L. Thornton Author-Name-First Daniel L., 2014. "How Effective Is Central Bank Forward Guidance?," Working Papers CASMEF 1405, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    • C.J.M. Kool & D.L. Thornton, 2012. "How Effective Is Central Bank Forward Guidance?," Working Papers 12-05, Utrecht School of Economics.
63. Veloce, William, 1996. "An evaluation of the leading indicators for the Canadian economy using time series analysis," International Journal of Forecasting, Elsevier, vol. 12(3), pages 403-416, September.
64. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    • Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," CARF F-Series CARF-F-219, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," CIRJE F-Series CIRJE-F-742, CIRJE, Faculty of Economics, University of Tokyo.
    • Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 10/34, University of Canterbury, Department of Economics and Finance.
    • Caporin, M. & McAleer, M.J., 2010. "Ranking multivariate GARCH models by problem dimension," Econometric Institute Research Papers EI 2010-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
65. Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren, 2017. "A comparative assessment of alternative ex ante measures of inflation uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 76-89.
66. Silva Lopes, Artur, 1994. "A "hipótese das expectativas racionais": teoria e realidade (uma visita guiada à literatura até 1992) [The "rational expectations hypothesis": theory and reality (a guided tour ," MPRA Paper 9699, University Library of Munich, Germany, revised 23 Jul 2008.
67. Clements, Michael P., 2019. "Do forecasters target first or later releases of national accounts data?," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1240-1249.
    • 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.
68. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    • Tara M. Sinclair & H.O. Stekler & Warren Carnow, 2012. "A New Approach For Evaluating Economic Forecasts," Working Papers 2012-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    • Tara Sinclair & Herman O. Stekler & Warren Carnow, 2012. "A New Approach For Evaluating Economic Forecasts," Working Papers 2012-2, The George Washington University, Institute for International Economic Policy.
69. Magnus Kvåle Helliesen & Håvard Hungnes & Terje Skjerpen, 2022. "Revisions in the Norwegian National Accounts: accuracy, unbiasedness and efficiency in preliminary figures," Empirical Economics, Springer, vol. 62(3), pages 1079-1121, March.
    • Magnus Kvåle Helliesen & Håvard Hungnes & Terje Skjerpen, 2020. "Revisions in the Norwegian National Accounts. Accuracy, unbiasedness and efficiency in preliminary figures," Discussion Papers 924, Statistics Norway, Research Department.
70. Pao‐Lin Tien & Tara M. Sinclair & Edward N. Gamber, 2021. "Do Fed Forecast Errors Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 686-712, June.
    • Pao-Lin Tien & Tara M. Sinclair & Edward N. Gamber, 2015. "Do Fed Forecast Errors Matter?," Wesleyan Economics Working Papers 2015-004, Wesleyan University, Department of Economics.
    • Pao-Lin Tien & Tara M. Sinclair & Edward N. Gamber, 2016. "Do Fed Forecast Errors Matter?," Working Papers 2016-007, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    • Tara Sinclair & Pao-Lin Tien & Edward Gamber, 2016. "Do Fed Forecast Errors Matter?," Working Papers 2016-14, The George Washington University, Institute for International Economic Policy, revised Aug 2018.
    • Pao-Lin Tien & Tara M. Sinclair & Edward N. Gamber, 2016. "Do Fed forecast errors matter?," CAMA Working Papers 2016-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
71. Harris, Richard D.F. & Stoja, Evarist & Yilmaz, Fatih, 2011. "A cyclical model of exchange rate volatility," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 3055-3064, November.
    • Evarist Stoja & Richard D. F. Harris & Fatih Yilmaz, 2010. "A Cyclical Model of Exchange Rate Volatility," Bristol Economics Discussion Papers 10/618, School of Economics, University of Bristol, UK.
72. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
73. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," Center for Financial Institutions Working Papers 99-05, Wharton School Center for Financial Institutions, University of Pennsylvania.
    • Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.
    • Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," NBER Working Papers 6845, National Bureau of Economic Research, Inc.
74. Cezary A. Kapuscinski & Kyle Thomson, 2014. "Experiment Estimates of Indigenous Employment from Administrative Data," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 17(2), pages 139-161.
75. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    • Nguyen, Hoang & Virbickaite, Audrone, 2022. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Working Papers 2022:5, Örebro University, School of Business.
76. Michael T. Belongia, 1988. "Are economic forecasts by government agencies biased? Accurate?," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 15-23.
77. M. Mogliani & T. Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
78. Cordis, Adriana S. & Kirby, Chris, 2014. "Discrete stochastic autoregressive volatility," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 160-178.
79. 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.
    • Thomas Jobert & Lionel Persyn, 2011. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Working Papers halshs-00721673, HAL.
80. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2015. "Forecasting implied volatility indices worldwide: A new approach," MPRA Paper 72084, University Library of Munich, Germany.
81. repec:zbw:bofrdp:2017_037 is not listed on IDEAS
82. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
83. Söderström, Ulf & Iversen, Jens & LASEEN, PER & Lundvall, Henrik, 2016. "Real-Time Forecasting for Monetary Policy Analysis: The Case of Sveriges Riksbank," CEPR Discussion Papers 11203, C.E.P.R. Discussion Papers.
    • Iversen, Jens & Laséen, Stefan & Lundvall, Henrik & Söderström, Ulf, 2016. "Real-Time Forecasting for Monetary Policy Analysis: The Case of Sveriges Riksbank," Working Paper Series 318, Sveriges Riksbank (Central Bank of Sweden).
84. Kashyap, Ravi, 2020. "David vs Goliath (You against the Markets), A dynamic programming approach to separate the impact and timing of trading costs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
85. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
    • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
86. Ziemer, Rod F. & White, Fred C., 1982. "Equilibrium Versus Disequilibrium In The Market For Non-Fed Cattle," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 7(2), pages 1-10, December.
87. Chrétien, Stéphane & Ortega, Juan-Pablo, 2014. "Multivariate GARCH estimation via a Bregman-proximal trust-region method," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 210-236.
88. Peng, Qing & Li, Jie & Zhao, Yu & Wu, Han, 2021. "The informational content of implied volatility: Application to the USD/JPY exchange rates," Journal of Asian Economics, Elsevier, vol. 76(C).
89. Harris, Richard D.F. & Wang, Pengguo, 2019. "Model-based earnings forecasts vs. financial analysts' earnings forecasts," The British Accounting Review, Elsevier, vol. 51(4), pages 424-437.
90. Andrew J. Patton & Kevin Sheppard, 2008. "Evaluating Volatility and Correlation Forecasts," OFRC Working Papers Series 2008fe22, Oxford Financial Research Centre.
    • Kevin Sheppard & Andrew J. Patton, 2008. "Evaluating Volatility and Correlation Forecasts," Economics Series Working Papers 2008fe22, University of Oxford, Department of Economics.
91. Jagric, Timotej & Beko, Jani, 2011. "How Good are the Growth and Inflation Forecasts for Slovenia?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 47-67, December.
92. 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.
93. Yeh, Jin-Huei & Yun, Mu-Shu, 2023. "Assessing jump and cojumps in financial asset returns with applications in futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
94. Jeremy J. Nalewaik, 2016. "Inflation Expectations and the Stabilization of Inflation : Alternative Hypotheses," Finance and Economics Discussion Series 2016-035, Board of Governors of the Federal Reserve System (U.S.).
95. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2014. "Does the Macroeconomy Predict UK Asset Returns in a Nonlinear Fashion? Comprehensive Out-of-Sample Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 510-535, August.
    • 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.
96. 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.
    • Clements, Michael P., 2012. "US inflation expectations and heterogeneous loss functions, 1968–2010," Economic Research Papers 270653, University of Warwick - Department of Economics.
    • Clements, Michael P., 2012. "US inflation expectations and heterogeneous loss functions, 1968–2010," The Warwick Economics Research Paper Series (TWERPS) 986, University of Warwick, Department of Economics.
97. Richard Jong-A-Pin & Jan-Egbert Sturm & Jakob de Haan & Jakob de Haan, 2012. "Using Real-Time Data to Test for Political Budget Cycles," CESifo Working Paper Series 3939, CESifo.
    • Jan-Egbert Sturm & Richard Jong-A-Pin & Jakob de Haan, 2012. "Using Real-Time Data to Test for Political Budget Cycles," KOF Working papers 12-313, KOF Swiss Economic Institute, ETH Zurich.
    • Jong-A-Pin, Richard & Sturm, Jan-Egbert & Haan, Jakob de, 2012. "Using real-time data to test for political budget cycles," Research Report 12010-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
98. Haugom, Erik & Langeland, Henrik & Molnár, Peter & Westgaard, Sjur, 2014. "Forecasting volatility of the U.S. oil market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 1-14.
99. Hans Christian Müller-Dröge & Tara M. Sinclair & H.O. Stekler, 2014. "Evaluating Forecasts of a Vector of Variables: a German Forecasting Competition," CAMA Working Papers 2014-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Hans Christian Müller-Dröge & Tara M. Sinclair & Herman O. Stekler, 2014. "Evaluating Forecasts Of A Vector Of Variables: A German Forecasting Competition," Working Papers 2014-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    • Tara M. Sinclair & Hans Christian Müller-Dröge & Herman Stekler, 2014. "Evaluating Forecasts of a Vector of Variables: A German Forecasting Competition," Working Papers 2014-17, The George Washington University, Institute for International Economic Policy.
100. Wang, Xiaohu & Xiao, Weilin & Yu, Jun, 2023. "Modeling and forecasting realized volatility with the fractional Ornstein–Uhlenbeck process," Journal of Econometrics, Elsevier, vol. 232(2), pages 389-415.
101. 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.
102. Eleni Argiri & Stephen G. Hall & Angeliki Momtsia & Daphne Marina Papadopoulou & Ifigeneia Skotida & George S. Tavlas & Yongli Wang, 2024. "An evaluation of the inflation forecasting performance of the European Central Bank, the Federal Reserve, and the Bank of England," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 932-947, July.
103. Hofer Helmut & Weyerstraß Klaus & Schmidt Torsten, 2011. "Practice and Prospects of Medium-term Economic Forecasting," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 153-171, February.
     • Hofer, Helmut & Schmidt, Torsten & Weyerstrass, Klaus, 2010. "Practice and Prospects of Medium-term Economic Forecasting," Ruhr Economic Papers 177, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
     • Helmut Hofer & Torsten Schmidt & Klaus Weyerstrass, 2010. "Practice and prospects of medium-term economic forecasting," NRN working papers 2010-12, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
104. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
105. Isiklar, Gultekin, 2005. "On aggregation bias in fixed-event forecast efficiency tests," Economics Letters, Elsevier, vol. 89(3), pages 312-316, December.
     • Gultekin Isiklar, 2004. "On aggregation bias in fixed-event forecast efficiency tests," Econometrics 0412011, University Library of Munich, Germany, revised 28 Dec 2004.
106. Ahumada, H. & Cornejo, M., 2016. "Forecasting food prices: The case of corn, soybeans and wheat," International Journal of Forecasting, Elsevier, vol. 32(3), pages 838-848.
107. Byun, Suk Joon & Cho, Hangjun, 2013. "Forecasting carbon futures volatility using GARCH models with energy volatilities," Energy Economics, Elsevier, vol. 40(C), pages 207-221.
108. Michel Beine & Charles S. Bos & Sébastien Laurent, 2007. "The Impact of Central Bank FX Interventions on Currency Components," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 154-183.
     • Michel Beine & Charles S. Bos & Sebastian Laurent, 2005. "The Impact of Central Bank FX Interventions on Currency Components," Tinbergen Institute Discussion Papers 05-103/4, Tinbergen Institute.
     • Michel Beine & Charles Bos & Sébastien Laurent, 2007. "The impact of Central Bank FX interventions on currency components," ULB Institutional Repository 2013/10419, ULB -- Universite Libre de Bruxelles.
     • BEINE, Michel & BOS, Charles S. & LAURENT, Sébastien, 2006. "The impact of Central Bank FX interventions on currency components," LIDAM Reprints CORE 1980, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
109. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, Center for Economic and Financial Research (CEFIR).
     • Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).
110. Härdle, Wolfgang Karl & Mungo, Julius, 2008. "Value-at-risk and expected shortfall when there is long range dependence," SFB 649 Discussion Papers 2008-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
111. Victor Zarnowitz, 1984. "Business Cycles Analysis and Expectational Survey Data," NBER Working Papers 1378, National Bureau of Economic Research, Inc.
112. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
113. Matteo Barigozzi & Marco Capasso, 2007. "A Multivariate Perspective for Modeling and Forecasting Inflation's Conditional Mean and Variance," LEM Papers Series 2007/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
114. Leilane de Freitas Rocha Cambara & Roberto Meurer, Gilberto Tadeu Lima, 2019. "Deviating from Perfect Foresight but not from Theoretical Consistency: The Behavior of Inflation Expectations in Brazil," Working Papers, Department of Economics 2019_36, University of São Paulo (FEA-USP).
115. Seaman, Brian & Bowman, John, 2022. "Applicability of the M5 to Forecasting at Walmart," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1468-1472.
116. Pérignon, Christophe & Smith, Daniel R., 2010. "The level and quality of Value-at-Risk disclosure by commercial banks," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 362-377, February.
     • Christophe Perignon & D. Smith, 2009. "The Level and Quality of Value-at-Risk Disclosure by Commercial Banks," Post-Print hal-00496102, HAL.
     • Christophe Perignon & Daniel R. Smith, 2010. "The level and quality of Value-at-Risk disclosure by commercial banks," Post-Print hal-00528391, HAL.
117. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
118. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
     • Ager, Philipp & Kappler, Marcus & Osterloh, Steffen, 2007. "The Accuracy and Efficiency of the Consensus Forecasts: A Further Application and Extension of the Pooled Approach," ZEW Discussion Papers 07-058, ZEW - Leibniz Centre for European Economic Research.
119. Marine Carrasco & Barbara Rossi, 2016. "In-Sample Inference and Forecasting in Misspecified Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 313-338, July.
     • 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.
     • Rossi, Barbara & Carrasco, Marine, 2016. "In-sample Inference and Forecasting in Misspecified Factor Models," CEPR Discussion Papers 11388, C.E.P.R. Discussion Papers.
120. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
     • Rossi, Barbara & Inoue, Atsushi, 2011. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," CEPR Discussion Papers 8542, C.E.P.R. Discussion Papers.
     • 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.
     • Barbara Rossi & Atsushi Inoue, 2012. "Out-of-sample forecast tests robust to the choice of window size," Economics Working Papers 1404, Department of Economics and Business, Universitat Pompeu Fabra.
121. Gaglianone, Wagner Piazza & Giacomini, Raffaella & Issler, João Victor & Skreta, Vasiliki, 2022. "Incentive-driven inattention," Journal of Econometrics, Elsevier, vol. 231(1), pages 188-212.
     • Wagner Piazza Gaglianone & Raffaella Giacomini & João Victor Issler & Vasiliki Skreta, 2018. "Incentive-driven Inattention," Working Papers Series 485, Central Bank of Brazil, Research Department.
     • Skreta, Vasiliki & Giacomini, Raffaella & Gaglianone, Wagner & Issler, Joao, 2019. "Incentive-driven Inattention," CEPR Discussion Papers 13619, C.E.P.R. Discussion Papers.
     • Gaglianone, Wagner Piazza & Giacomini, Raffaella & Issler, João Victor & Skreta, Vasiliki, 2019. "Incentive-driven Inattention," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 811, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
122. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
     • Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
     • Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
     • Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
123. François-Éric Racicot & Raymond Théoret & Alain Coën, 2008. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 112-124, February.
     • Francois-Éric Racicot & Raymond Théoret & Alain Coen, 2006. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," RePAd Working Paper Series UQO-DSA-wp152006, Département des sciences administratives, UQO.
124. Christopher Hansman & Harrison Hong & Áureo de Paula & Vishal Singh, 2020. "A Sticky-Price View of Hoarding," NBER Working Papers 27051, National Bureau of Economic Research, Inc.
     • de Paula, Aureo & Hansman, Christopher & Hong, Harrison & Singh, Vishal, 2020. "A Sticky-Price View of Hoarding," CEPR Discussion Papers 14633, C.E.P.R. Discussion Papers.
125. Andrew C. Chang & Trace J. Levinson, 2020. "Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting," Finance and Economics Discussion Series 2020-090, Board of Governors of the Federal Reserve System (U.S.).
126. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
127. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
128. Heilemann Ullrich & Stekler Herman O., 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, De Gruyter, vol. 14(2), pages 235-253, May.
     • Ullrich Heilemann & Herman O. Stekler, 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, Verein für Socialpolitik, vol. 14(2), pages 235-253, May.
129. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
130. Baillie, Richard T. & Morana, Claudio, 2009. "Modelling long memory and structural breaks in conditional variances: An adaptive FIGARCH approach," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1577-1592, August.
     • Richard T. Baillie & Claudio Morana, 2007. "Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach," ICER Working Papers - Applied Mathematics Series 11-2007, ICER - International Centre for Economic Research.
     • Richard T. Baillie & Claudio Morana, 2014. "Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach," Working Papers 593, Queen Mary University of London, School of Economics and Finance.
131. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
     • Dimpfl, Thomas & Jank, Stephan, 2011. "Can Internet search queries help to predict stock market volatility?," University of Tübingen Working Papers in Business and Economics 18, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
     • Dimpfl, Thomas & Jank, Stephan, 2011. "Can internet search queries help to predict stock market volatility?," CFR Working Papers 11-15, University of Cologne, Centre for Financial Research (CFR).
132. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
     • Dean Croushore, 2006. "An evaluation of inflation forecasts from surveys using real-time data," Working Papers 06-19, Federal Reserve Bank of Philadelphia.
133. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
134. Torben G. ANDERSEN & Tim BOLLERSLEV & Nour MEDDAHI, 2002. "Correcting The Errors : A Note On Volatility Forecast Evaluation Based On High-Frequency Data And Realized Volatilities," Cahiers de recherche 21-2002, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
     • ANDERSEN, Torben G. & BOLLERSLEV, Tim & MEDDAHI, Nour, 2002. "Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," Cahiers de recherche 2002-21, Universite de Montreal, Departement de sciences economiques.
     • Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," CIRANO Working Papers 2002s-91, CIRANO.
135. Victor Zarnowitz & Charlotte Boschan & Geoffrey H. Moore & Josephine Su, 1972. "Business Cycle Analysis of Econometric Model Simulations," NBER Chapters, in: Econometric Models of Cyclical Behavior, Volumes 1 and 2, pages 311-541, National Bureau of Economic Research, Inc.
136. Kambouroudis, Dimos S. & McMillan, David G., 2015. "Is there an ideal in-sample length for forecasting volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 114-137.
137. Nam, Minho & Go, Minji, 2018. "Nexus between Inflation, Inflation Perceptions and Expectations," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 40(3), pages 45-68.
138. Caporin, M. & McAleer, M.J., 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," Econometric Institute Research Papers EI 2010-57, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
     • Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," KIER Working Papers 724, Kyoto University, Institute of Economic Research.
     • Massimiliano Caporin & Michael McAleer, 2010. "Model Selection and Testing of Conditional and Stochastic Volatility Models," Working Papers in Economics 10/58, University of Canterbury, Department of Economics and Finance.
139. Marcell Göttert & Robert Lehmann, 2021. "Tax Revenue Forecast Errors: Wrong Predictions of the Tax Base or the Elasticity?," CESifo Working Paper Series 9148, CESifo.
140. G.R. Pasha & Tahira Qasim & Muhammad Aslam, 2007. "Estimating and Forecasting Volatility of Financial Time Series in Pakistan with GARCH-type Models," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 12(2), pages 115-149, Jul-Dec.
141. Kumar, Dilip & Maheswaran, S., 2014. "Modeling and forecasting the additive bias corrected extreme value volatility estimator," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 166-176.
142. Aït-Sahalia, Yacine & Mancini, Loriano, 2008. "Out of sample forecasts of quadratic variation," Journal of Econometrics, Elsevier, vol. 147(1), pages 17-33, November.
143. 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.
144. Berg Tim Oliver, 2015. "Time Varying Fiscal Multipliers in Germany," Review of Economics, De Gruyter, vol. 66(1), pages 13-46, April.
     • Berg, Tim Oliver, 2014. "Time Varying Fiscal Multipliers in Germany," MPRA Paper 57223, University Library of Munich, Germany.
145. Boos, Dominik & Grob, Linus, 2023. "Tracking speculative trading," Journal of Financial Markets, Elsevier, vol. 64(C).
146. 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.
147. 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.
     • Yang K. Lu & Pierre Perron, 2008. "Modeling and Forecasting Stock Return Volatility Using a Random Level Shift Model," Boston University - Department of Economics - Working Papers Series wp2008-012, Boston University - Department of Economics.
148. Sebastian Bayer & Timo Dimitriadis, 2018. "Regression Based Expected Shortfall Backtesting," Papers 1801.04112, arXiv.org, revised Sep 2019.
149. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
     • 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.
150. Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
151. Fabiana Gomez & David Pacini, 2015. "Counting Biased Forecasters: An Application of Multiple Testing Techniques," Bristol Economics Discussion Papers 15/661, School of Economics, University of Bristol, UK.
152. Fuentes, Julieta & Poncela, Pilar & Rodríguez, Julio, 2014. "Selecting and combining experts from survey forecasts," DES - Working Papers. Statistics and Econometrics. WS ws140905, Universidad Carlos III de Madrid. Departamento de Estadística.
153. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "How to Estimate Beta?," Hannover Economic Papers (HEP) dp-617, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
154. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
     • Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
     • Caporin, M. & McAleer, M.J., 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Econometric Institute Research Papers EI2012-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
     • Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Documentos de Trabajo del ICAE 2012-06, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2012.
     • Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
155. Forth, John & Bryson, Alex & Phan, Van & Ritchie, Felix & Singleton, Carl & Stokes, Lucy & Whittard, Damian, 2024. "Revisiting Sample Bias in the UK's Annual Survey of Hours and Earnings, with Implications for Estimates of Low Pay and the Bite of the National Living Wage," IZA Discussion Papers 17291, Institute of Labor Economics (IZA).
156. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.
     • Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
157. Marek RUSNAK, 2013. "Revisions to the Czech National Accounts: Properties and Predictability," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(3), pages 244-261, July.
158. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "Estimating beta: Forecast adjustments and the impact of stock characteristics for a broad cross-section," Journal of Financial Markets, Elsevier, vol. 44(C), pages 91-118.
159. Feunou, Bruno & Okou, Cédric, 2019. "Good Volatility, Bad Volatility, and Option Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(2), pages 695-727, April.
     • Bruno Feunou & Cédric Okou, 2017. "Good Volatility, Bad Volatility and Option Pricing," Staff Working Papers 17-52, Bank of Canada.
160. Leif Anders Thorsrud, 2016. "Nowcasting using news topics Big Data versus big bank," Working Papers No 6/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
     • Leif Anders Thorsrud, 2016. "Nowcasting using news topics. Big Data versus big bank," Working Paper 2016/20, Norges Bank.
161. Benchimol, Jonathan & El-Shagi, Makram, 2020. "Forecast performance in times of terrorism," Economic Modelling, Elsevier, vol. 91(C), pages 386-402.
     • Jonathan Benchimol & Makram El-Shagi, 2017. "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series 2017/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
     • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast Performance in Times of Terrorism," Globalization Institute Working Papers 390, Federal Reserve Bank of Dallas.
     • Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
     • Jonathan Benchimol & Makram El-Shagi, 2020. "Forecast performance in times of terrorism," Post-Print halshs-03248938, HAL.
162. Mamatzakis, E. & Koutsomanoli-Filippaki, A., 2014. "Testing the rationality of DOE's energy price forecasts under asymmetric loss preferences," Energy Policy, Elsevier, vol. 68(C), pages 567-575.
163. Andrew Patton & Allan Timmermann, 2012. "Forecast Rationality Tests Based on Multi-Horizon Bounds," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-17.
     • 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.
     • Timmermann, Allan & Patton, Andrew, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," CEPR Discussion Papers 8194, C.E.P.R. Discussion Papers.
164. Gael M. Martin & Andrew Reidy & Jill Wright, 2006. "Assessing the Impact of Market Microstructure Noise and Random Jumps on the Relative Forecasting Performance of Option-Implied and Returns-Based Volatility," Monash Econometrics and Business Statistics Working Papers 10/06, Monash University, Department of Econometrics and Business Statistics.
165. Rituparna Sen & Pulkit Mehrotra, 2016. "Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 137-150, June.
166. Nikolaus Hautsch & Lada M. Kyj & Roel C. A. Oomen, 2012. "A blocking and regularization approach to high‐dimensional realized covariance estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(4), pages 625-645, June.
     • Hautsch, Nikolaus & Kyj, Lada M. & Hautsch, Nikolaus, 2009. "A blocking and regularization approach to high dimensional realized covariance estimation," CFS Working Paper Series 2009/20, Center for Financial Studies (CFS).
     • Hautsch, Nikolaus & Kyj, Lada M. & Oomen, Roel C.A., 2009. "A blocking and regularization approach to high dimensional realized covariance estimation," SFB 649 Discussion Papers 2009-049, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
167. Mr. Marcos Poplawski Ribeiro & Jan-Christoph Rülke, 2011. "Fiscal Expectations Under the Stability and Growth Pact: Evidence from Survey Data," IMF Working Papers 2011/048, International Monetary Fund.
168. Frieder Meyer-Bullerdiek, 2024. "The Quality of Blume and Vasicek Betas for forecasting systematic risk: Evidence from a German stock portfolio," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(6), pages 1-1.
169. Cavaca, Igor Bastos & Meurer, Roberto, 2024. "The asymmetry and uncertainty effects on the response of the yield curve to Brazilian monetary policy," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 831-844.
170. 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.
171. Taylor, James W., 2020. "A strategic predictive distribution for tests of probabilistic calibration," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1380-1388.
172. Dovern, Jonas & Jannsen, Nils, 2017. "Systematic errors in growth expectations over the business cycle," International Journal of Forecasting, Elsevier, vol. 33(4), pages 760-769.
     • Dovern, Jonas & Jannsen, Nils, 2015. "Systematic errors in growth expectations over the business cycle," Kiel Working Papers 1989, Kiel Institute for the World Economy (IfW Kiel).
173. Benjamin Beckers & Samya Beidas-Strom, 2015. "Forecasting the Nominal Brent Oil Price with VARs—One Model Fits All?," IMF Working Papers 2015/251, International Monetary Fund.
174. Christoffersen, Peter & Jacobs, Kris, 2004. "The importance of the loss function in option valuation," Journal of Financial Economics, Elsevier, vol. 72(2), pages 291-318, May.
     • Peter Christoffersen & Kris Jacobs, 2003. "The Importance of the Loss Function in Option Valuation," CIRANO Working Papers 2003s-52, CIRANO.
175. J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
     • J. James Reade & Carl Singleton & Alasdair Brown, 2019. "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics Discussion Papers em-dp2019-18, Department of Economics, University of Reading, revised 01 Aug 2020.
176. Kappler, Marcus, 2007. "Projecting the Medium-Term: Outcomes and Errors for GDP Growth," ZEW Discussion Papers 07-068, ZEW - Leibniz Centre for European Economic Research.
177. McCracken,M.W. & West,K.D., 2001. "Inference about predictive ability," Working papers 14, Wisconsin Madison - Social Systems.
178. Zeno Ronald R. Abenoja & Jasmin E. Dacio & Sarah Jane A. Castañares & Jan Christopher G. Ocampo & Mark Rex S. Romaraog, 2022. "The BSP's Forecasting and Policy Analysis System," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 59(1), pages 77-107, June.
179. Julien Champagne & Guillaume Poulin‐Bellisle & Rodrigo Sekkel, 2020. "Introducing the Bank of Canada staff economic projections database," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 114-129, January.
180. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
181. KANGASSALO Pertti & TAKALA Kari, 2010. "Measuring the Usefulness of Consumers’ Inflation Expectations in Finland," EcoMod2003 330700076, EcoMod.
182. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
     • Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
     • Gaglianone, Wagner Piazza & Linton, Oliver & Lima, Luiz Renato Regis de Oliveira, 2008. "Evaluating Value-at-Risk models via Quantile regressions," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 679, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
     • Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel Smith, 2010. "Evaluating Value-at-Risk Models via Quantile Regression," NCER Working Paper Series 67, National Centre for Econometric Research.
     • Wagner P. Gaglianone & Luiz Renato Lima & Oliver Linton, 2008. "Evaluating Value-at-Risk Models via Quantile Regressions," Working Papers Series 161, Central Bank of Brazil, Research Department.
     • Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel, 2009. "Evaluating Value-at-Risk models via Quantile Regression," UC3M Working papers. Economics we094625, Universidad Carlos III de Madrid. Departamento de Economía.
183. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
184. Ali Alami & Eric Renault, 2001. "Risque de modèle de volatilité," CIRANO Working Papers 2001s-06, CIRANO.
185. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
186. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
187. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
188. Dudley Gilder & Leonidas Tsiaras, 2020. "Volatility forecasts embedded in the prices of crude‐oil options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1127-1159, July.
189. Thomas Dimpfl & Tobias Langen, 2019. "How Unemployment Affects Bond Prices: A Mixed Frequency Google Nowcasting Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 551-573, August.
190. MacDonald, Stephen & Ash, Mark & Cooke, Bryce, 2017. "The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets," MPRA Paper 87545, University Library of Munich, Germany.
191. 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.
192. Eleonora Granziera & Pirkka Jalasjoki & Maritta Paloviita, 2021. "The Bias and Efficiency of the ECB Inflation Projections: a State Dependent Analysis," Working Paper 2021/1, Norges Bank.
193. Döpke, Jörg & Fritsche, Ulrich & Müller, Karsten, 2019. "Has macroeconomic forecasting changed after the Great Recession? Panel-based evidence on forecast accuracy and forecaster behavior from Germany," Journal of Macroeconomics, Elsevier, vol. 62(C).
194. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
195. Trino-Manuel Ñíguez, 2008. "Volatility and VaR forecasting in the Madrid Stock Exchange," Spanish Economic Review, Springer;Spanish Economic Association, vol. 10(3), pages 169-196, September.
196. 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.
     • Franses, Ph.H.B.F. & Welz, M., 2018. "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Econometric Institute Research Papers EI2018-47, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
197. West, Kenneth D & McCracken, Michael W, 1998. "Regression-Based Tests of Predictive Ability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 817-840, November.
     • West, K.D. & McCracken, M.W., 1997. "Regression-Based Tests of Predictive Ability," Working papers 9710, Wisconsin Madison - Social Systems.
     • Kenneth D. West & Michael W. McCracken, 1998. "Regression-Based Tests of Predictive Ability," NBER Technical Working Papers 0226, National Bureau of Economic Research, Inc.
198. Becker, Ralf & Clements, Adam E. & McClelland, Andrew, 2009. "The jump component of S&P 500 volatility and the VIX index," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1033-1038, June.
     • Ralf Becker & Adam Clements & Andrew McClelland, 2008. "The Jump component of S&P 500 volatility and the VIX index," NCER Working Paper Series 24, National Centre for Econometric Research.
199. Juan Manuel Julio Román, 2011. "Modeling Data Revisions," Borradores de Economia 7929, Banco de la Republica.
     • Juan Manuel Julio, 2011. "Modeling Data Revisions," Borradores de Economia 641, Banco de la Republica de Colombia.
200. Patrick Rizzetto, 2018. "GDP by Industry in Real Time: Are Revisions Well Behaved?," Staff Analytical Notes 2018-40, Bank of Canada.
201. Michael Clements, 2016. "Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2016-08, Henley Business School, University of Reading.
202. Christensen, Bent Jesper & Kjær, Mads Markvart & Veliyev, Bezirgen, 2023. "The incremental information in the yield curve about future interest rate risk," Journal of Banking & Finance, Elsevier, vol. 155(C).
     • Bent Jesper Christensen & Mads Markvart Kjær & Bezirgen Veliyev, 2021. "The incremental information in the yield curve about future interest rate risk," CREATES Research Papers 2021-11, Department of Economics and Business Economics, Aarhus University.
203. 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.
     • Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2016. "Applying a Microfounded-Forecasting Approach to Predict Brazilian Inflation," Working Papers Series 436, Central Bank of Brazil, Research Department.
204. Kuethe, Todd H. & Hubbs, Todd & Sanders, Dwight R., 2018. "Evaluating the USDA’s Net Farm Income Forecast," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(3), September.
205. Carstensen Kai & Wohlrabe Klaus & Ziegler Christina, 2011. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 82-106, February.
     • Kai Carstensen & Klaus Wohlrabe & Christina Ziegler, 2010. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," CESifo Working Paper Series 3158, CESifo.
     • Carstensen, Kai & Wohlrabe, Klaus & Ziegler, Christina, 2011. "Predictive ability of business cycle indicators under test: A case study for the Euro area industrial production," Munich Reprints in Economics 19953, University of Munich, Department of Economics.
     • Carstensen, Kai & Wohlrabe, Klaus & Ziegler, Christina, 2010. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Discussion Papers in Economics 11442, University of Munich, Department of Economics.
206. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
207. Becker, Ralf & Clements, Adam E. & White, Scott I., 2006. "On the informational efficiency of S&P500 implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 17(2), pages 139-153, August.
208. Francesco Audrino & Simon D. Knaus, 2016. "Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1485-1521, December.
     • Audrino, Francesco & Knaus, Simon, 2012. "Lassoing the HAR model: A Model Selection Perspective on Realized Volatility Dynamics," Economics Working Paper Series 1224, University of St. Gallen, School of Economics and Political Science.
209. Cepparulo, Alessandra & Gastaldi, Francesca & Giuriato, Luisa & Sacchi, Agnese, 2011. "Budgeting versus implementing fiscal policy:the Italian case," MPRA Paper 32474, University Library of Munich, Germany.
210. I. J. Macfarlane & J. R. Hawkins, 1983. "Economic Forecasts and Their Assessment," The Economic Record, The Economic Society of Australia, vol. 59(4), pages 321-331, December.
     • I.J. Macfarlane & J.R. Hawkins, 1983. "Economic Forecasts and Their Assessment," RBA Research Discussion Papers rdp8302, Reserve Bank of Australia.
211. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
     • 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).
     • Gaglianone, Wagner Piazza & Issler, João Victor, 2015. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 766, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
212. Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2011. "Evaluating Value-at-Risk Models with Desk-Level Data," Management Science, INFORMS, vol. 57(12), pages 2213-2227, December.
     • Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2005. "Evaluating Value-at-Risk models with desk-level data," Working Paper Series 010, North Carolina State University, Department of Economics, revised Dec 2006.
     • 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.
213. Clements, Michael P., 2024. "Survey expectations and adjustments for multiple testing," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 338-354.
214. Zhu, Xuehong & Zhang, Hongwei & Zhong, Meirui, 2017. "Volatility forecasting using high frequency data: The role of after-hours information and leverage effects," Resources Policy, Elsevier, vol. 54(C), pages 58-70.
215. Michael T. Belongia & Peter N. Ireland, 2018. "Monetary Policy Lessons from the Greenbook," Boston College Working Papers in Economics 955, Boston College Department of Economics.
216. Cherif Guermat & Richard D. F. Harris, 2006. "Bias in the estimation of non-linear transformations of the integrated variance of returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 481-494.
217. Xiao, Jinzhi, 2015. "Essays on the forecasts of ending stocks," ISU General Staff Papers 201501010800005902, Iowa State University, Department of Economics.
218. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
     • Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tedongap, 2013. "Which Parametric Model for Conditional Skewness?," Staff Working Papers 13-32, Bank of Canada.
219. Scotti, Chiara, 2016. "Surprise and uncertainty indexes: Real-time aggregation of real-activity macro-surprises," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 1-19.
     • Chiara Scotti, 2013. "Surprise and uncertainty indexes: real-time aggregation of real-activity macro surprises," International Finance Discussion Papers 1093, Board of Governors of the Federal Reserve System (U.S.).
220. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
221. Duan, Fang, 2022. "Forecasting risk measures based on structural breaks in the correlation matrix," Ruhr Economic Papers 945, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
222. Jianlei Han & Martina Linnenluecke & Zhangxin Liu & Zheyao Pan & Tom Smith, 2019. "A general equilibrium approach to pricing volatility risk," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-18, April.
223. Dooyeon Cho & Dong-Eun Rhee, 2015. "An assessment of inflation targeting in a quantitative monetary business cycle framework: evidence from four early adopters," Applied Economics, Taylor & Francis Journals, vol. 47(32), pages 3395-3413, July.
224. Aretz, Kevin & Eser Arisoy, Y., 2023. "The Pricing of Skewness Over Different Return Horizons," Journal of Banking & Finance, Elsevier, vol. 148(C).
225. Andrade, P. & Ghysels, E. & Idier, J., 2012. "Tails of Inflation Forecasts and Tales of Monetary Policy," Working papers 407, Banque de France.
226. Andrea Bucci & Giulio Palomba & Eduardo Rossi, 2019. "Does macroeconomics help in predicting stock markets volatility comovements? A nonlinear approach," Working Papers 440, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
227. Michael P Clements, 2014. "Assessing the Evidence of Macro- Forecaster Herding: Forecasts of Inflation and Output Growth," ICMA Centre Discussion Papers in Finance icma-dp2014-12, Henley Business School, University of Reading.
228. Jörg Döpke & Ulrich Fritsche & Karsten Müller, 2018. "Has Macroeconomic Forecasting changed after the Great Recession? - Panel-based Evidence on Accuracy and Forecaster Behaviour from Germany," Macroeconomics and Finance Series 201803, University of Hamburg, Department of Socioeconomics.
229. Golinski, Adam & Madeira, Joao & Rambaccussing, Dooruj, 2014. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices," SIRE Discussion Papers 2015-79, Scottish Institute for Research in Economics (SIRE).
     • Adam Goliński & João Madeira & Dooruj Rambaccussing, 2015. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices," Dundee Discussion Papers in Economics 284, Economic Studies, University of Dundee.
230. Michael Groemling, 2005. "Konjunkturprognosen – Verfahren, Erfolgskontrolle und Prognosefehler," Departmental Discussion Papers 123, University of Goettingen, Department of Economics.
231. David Rey, 2005. "Market Timing And Model Uncertainty: An Exploratory Study For The Swiss Stock Market," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 19(3), pages 239-260, October.
232. Capistrán, Carlos, 2008. "Bias in Federal Reserve inflation forecasts: Is the Federal Reserve irrational or just cautious?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1415-1427, November.
     • 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.
     • Capistrán Carlos, 2006. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Working Papers 2006-14, Banco de México.
     • Carmona, Carlos Capistran, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," University of California at San Diego, Economics Working Paper Series qt6v28v0b6, Department of Economics, UC San Diego.
233. Khoa Hoang & Robert Faff, 2021. "Is the ex‐ante equity risk premium always positive? Evidence from a new conditional expectations model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 95-124, March.
234. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
235. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
     • Barbara Rossi & Tatevik Sekhposyan, 2010. "Understanding Models' Forecasting Performance," Working Papers 10-56, Duke University, Department of Economics.
236. Golinski, Adam & Madeira, Joao & Rambaccussing, Dooruj, 2014. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model," MPRA Paper 58554, University Library of Munich, Germany.
237. Yoichi Tsuchiya, 2022. "Evaluating plant managers’ production plans over business cycles: asymmetric loss and rationality," SN Business & Economics, Springer, vol. 2(8), pages 1-29, August.
238. Ceci, Vladimiro & Manganelli, Simone & Vecchiato, Walter, 2002. "Sensitivity analysis of volatility: a new tool for risk management," Working Paper Series 194, European Central Bank.
239. Alexander Foltas & Christian Pierdzioch, 2022. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 29(10), pages 867-872, June.
     • 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.
240. Regmi, Hari & Kuethe, Todd H. & Foster, Kenneth A., 2022. "Evaluation of USDA's Agricultural Exports Projections," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322363, Agricultural and Applied Economics Association.
241. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
242. Pablo Pincheira Brown & Nicolás Hardy, 2024. "The mean squared prediction error paradox," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2298-2321, September.
     • Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
243. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
244. Breuer Christian, 2015. "On the Rationality of Medium-Term Tax Revenue Forecasts: Evidence from Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(1), pages 22-40, February.
     • Christian Breuer, 2014. "On the Rationality of Medium-Term Tax Revenue Forecasts: Evidence from Germany," ifo Working Paper Series 176, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
245. Sergey V. Chernenko, 2004. "The information content of forward and futures prices: market expectations and the price of risk," International Finance Discussion Papers 808, Board of Governors of the Federal Reserve System (U.S.).
246. Julieta Caunedo & Riccardo Dicecio & Ivana Komunjer & Michael T. Owyang, 2020. "Asymmetry, Complementarities, and State Dependence in Federal Reserve Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(1), pages 205-228, February.
     • Julieta Caunedo & Riccardo DiCecio & Ivana Komunjer & Michael T. Owyang, 2013. "Asymmetry, Complementarities, and State Dependence in Federal Reserve Forecasts," Working Papers 2013-012, Federal Reserve Bank of St. Louis, revised 29 Dec 2017.
247. Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
     • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
     • Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," Working Papers 2017-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
248. Bauwens, Luc & Sucarrat, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: A forecast evaluation," International Journal of Forecasting, Elsevier, vol. 26(4), pages 885-907, October.
     • 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.
     • BAUWENS, Luc & SUCARRAT, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: a forecast evaluation," LIDAM Reprints CORE 2234, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
     • BAUWENS, Luc & SUCARRAT, Genaro, 2006. "General to specific modelling of exchange rate volatility: a forecast evaluation," LIDAM Discussion Papers CORE 2006021, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
     • Bauwens, Luc & Sucarrat, Genaro, 2008. "General to specific modelling of exchange rate volatility : a forecast evaluation," UC3M Working papers. Economics we081810, Universidad Carlos III de Madrid. Departamento de Economía.
249. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
250. Pagano Patrizio & Pisani Massimiliano, 2009. "Risk-Adjusted Forecasts of Oil Prices," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-28, June.
     • Patrizio Pagano & Massimiliano Pisani, 2006. "Risk-Adjusted Forecasts of Oil Prices," Temi di discussione (Economic working papers) 585, Bank of Italy, Economic Research and International Relations Area.
     • Pagano, Patrizio & Pisani, Massimiliano, 2009. "Risk-adjusted forecasts of oil prices," Working Paper Series 999, European Central Bank.
251. Messina, Jeffrey D. & Sinclair, Tara M. & Stekler, Herman, 2015. "What can we learn from revisions to the Greenbook forecasts?," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 54-62.
     • Tara M. Sinclair & Jeff Messina & Herman Stekler, 2014. "What Can We Learn From Revisions to the Greenbook Forecasts?," Working Papers 2014-14, The George Washington University, Institute for International Economic Policy.
     • 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.
252. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Dynamic Factor GARCH: Multivariate Volatility Forecast for a Large Number of Series," LEM Papers Series 2006/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
253. Kumar, Dilip & Maheswaran, S., 2014. "A new approach to model and forecast volatility based on extreme value of asset prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 128-140.
254. Foltas, Alexander & Pierdzioch, Christian, 2020. "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers 21, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
255. Ralf Becker & Adam Clements & Christopher Coleman-Fenn, 2009. "Forecast performance of implied volatility and the impact of the volatility risk premium," NCER Working Paper Series 45, National Centre for Econometric Research.
256. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.
257. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
258. Pablo Pincheira-Brown & Andrea Bentancor & Nicolás Hardy, 2023. "An Inconvenient Truth about Forecast Combinations," Mathematics, MDPI, vol. 11(18), pages 1-24, September.
259. Chen, Chun-Hung & Yu, Wei-Choun & Zivot, Eric, 2012. "Predicting stock volatility using after-hours information: Evidence from the NASDAQ actively traded stocks," International Journal of Forecasting, Elsevier, vol. 28(2), pages 366-383.
260. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
     • Geert Bekaert & Marie Hoerova, 2013. "The VIX, the Variance Premium and Stock Market Volatility," NBER Working Papers 18995, National Bureau of Economic Research, Inc.
     • Hoerova, Marie & Bekaert, Geert, 2014. "The VIX, the variance premium and stock market volatility," Working Paper Series 1675, European Central Bank.
261. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
     • Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
262. Sinclair, Tara M. & Stekler, H.O. & Carnow, Warren, 2015. "Evaluating a vector of the Fed’s forecasts," International Journal of Forecasting, Elsevier, vol. 31(1), pages 157-164.
     • Tara M. Sinclair & H.O. Stekler & Warren Carnow, 2012. "Evaluating A Vector Of The Fed’S Forecasts," Working Papers 2012-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
     • Tara Sinclair & Herman O. Stekler & Warren Carrow, 2012. "Evaluating a Vector of the Fed's Forecasts," Working Papers 2012-3, The George Washington University, Institute for International Economic Policy.
263. Eskandar A. Tooma, 2003. "Modeling and Forecasting Egyptian Stock Market Volatility Before and After Price Limits," Working Papers 0310, Economic Research Forum, revised Apr 2003.
264. repec:lan:wpaper:470 is not listed on IDEAS
265. Xiao, Jihong & Wen, Fenghua & Zhao, Yupei & Wang, Xiong, 2021. "The role of US implied volatility index in forecasting Chinese stock market volatility: Evidence from HAR models," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 311-333.
266. Sanders, Dwight R. & Manfredo, Mark R. & Boris, Keith, 2009. "Evaluating information in multiple horizon forecasts: The DOE's energy price forecasts," Energy Economics, Elsevier, vol. 31(2), pages 189-196.
267. Roberto Luis Olinto Ramos & Patrice T. Robitaille & Rebeca de la Rocque Palis, 2004. "News or noise? an analysis of Brazilian GDP announcements," International Finance Discussion Papers 776, Board of Governors of the Federal Reserve System (U.S.).
268. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
269. Lena Dr䧥r & Jan-Oliver Menz & Ulrich Fritsche, 2014. "Perceived inflation under loss aversion," Applied Economics, Taylor & Francis Journals, vol. 46(3), pages 282-293, January.
     • Lena Dräger & Jan-Oliver Menz & Ulrich Fritsche, 2011. "Perceived Inflation under Loss Aversion," Macroeconomics and Finance Series 201105, University of Hamburg, Department of Socioeconomics.
270. Frank-Oliver Aldenhoff, 2007. "Are economic forecasts of the International Monetary Fund politically biased? A public choice analysis," The Review of International Organizations, Springer, vol. 2(3), pages 239-260, September.
271. Ravi Kashyap, 2016. "Hong Kong -- Shanghai Connect / Hong Kong -- Beijing Disconnect (?): Scaling the Great Wall of Chinese Securities Trading Costs," Papers 1603.01341, arXiv.org, revised Sep 2019.
272. Sergey V. Smirnov & Daria A. Avdeeva, 2016. "Wishful Bias in Predicting Us Recessions: Indirect Evidence," HSE Working papers WP BRP 135/EC/2016, National Research University Higher School of Economics.
273. Michael P. Cameron & Jacques Poot, 2010. "A Stochastic Sub-national Population Projection Methodology with an Application to the Waikato Region of New Zealand," Population Studies Centre Discussion Papers dp-70, University of Waikato, Te Ngira Institute for Population Research.
274. Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2021. "Forecasting the production side of GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 458-480, April.
     • Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2018. "Forecasting the production side of GDP," Working Papers 2018-16, Swiss National Bank.
275. Tianlun Fei & Xiaoquan Liu & Conghua Wen, 2023. "Forecasting stock return volatility: Realized volatility‐type or duration‐based estimators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1594-1621, November.
276. Luo, Xingguo & Qin, Shihua & Ye, Zinan, 2016. "The information content of implied volatility and jumps in forecasting volatility: Evidence from the Shanghai gold futures market," Finance Research Letters, Elsevier, vol. 19(C), pages 105-111.
277. Gavriilidis, Konstantinos & Kambouroudis, Dimos S. & Tsakou, Katerina & Tsouknidis, Dimitris A., 2018. "Volatility forecasting across tanker freight rates: The role of oil price shocks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 376-391.
     • Konstantinos Gavriilidis & Dimos S. Kambouroudis & Katerina Tsakou & Dimitris S. Tsouknidis, 2018. "Volatility forecasting across tanker freight rates: the role of oil price shocks," Working Papers 2018-27, Swansea University, School of Management.
278. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2021. "The bias and efficiency of the ECB inflation projections: A state dependent analysis," Bank of Finland Research Discussion Papers 7/2021, Bank of Finland.
279. repec:hum:wpaper:sfb649dp2008-006 is not listed on IDEAS
280. Elaad, Guy & Reade, J. James & Singleton, Carl, 2020. "Information, prices and efficiency in an online betting market," Finance Research Letters, Elsevier, vol. 35(C).
     • Guy Elaad & J. James Reade & Carl Singleton, 2019. "Information, prices and efficiency in an online betting market," Economics Discussion Papers em-dp2019-10, Department of Economics, University of Reading.
281. Apostolos Kourtis & Raphael N. Markellos & Lazaros Symeonidis, 2016. "An International Comparison of Implied, Realized, and GARCH Volatility Forecasts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(12), pages 1164-1193, December.
282. Isengildina Massa, Olga & Stewart, Shamar & Hassman, Colburn H., 2021. "RETURN DIVERGENCE IN COMMODITY ETFs: NATURE AND CAUSES," 2021 Annual Meeting, August 1-3, Austin, Texas 313896, Agricultural and Applied Economics Association.
283. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
284. 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.
     • Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers 2008-010, Federal Reserve Bank of St. Louis.
285. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
     • Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Working Papers in Economics 11/23, University of Canterbury, Department of Economics and Finance.
     • Michael McAleer & Massimiliano Caporin, 2011. "Ranking Multivariate GARCH Models by Problem Dimension:An Empirical Evaluation," KIER Working Papers 778, Kyoto University, Institute of Economic Research.
     • Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Documentos de Trabajo del ICAE 2011-20, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
286. repec:lan:wpaper:425 is not listed on IDEAS
287. 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.
288. Trino-Manuel Ñíguez, 2003. "Volatility And Var Forecasting For The Ibex-35 Stock-Return Index Using Figarch-Type Processes And Different Evaluation Criteria," Working Papers. Serie AD 2003-33, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
289. Alasdair Brown & Fuyu Yang, 2021. "Framing effects and the market selection hypothesis: Evidence from real‐world isomorphic bets," Southern Economic Journal, John Wiley & Sons, vol. 88(1), pages 399-413, July.
290. Torsten Schmidt & Helmut Hofer & Klaus Weyerstrass, 2010. "Practice and Prospects of Medium-term Economic Forecasting," Ruhr Economic Papers 0177, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
291. 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.
292. Brown, Alasdair & Reade, J. James, 2019. "The wisdom of amateur crowds: Evidence from an online community of sports tipsters," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1073-1081.
293. Caruso, Alberto, 2019. "Macroeconomic news and market reaction: Surprise indexes meet nowcasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1725-1734.
     • Alberto Caruso, 2018. "Macroeconomic News and Market Reaction: Surprise Indexes meet Nowcasting," Working Papers ECARES 2018-06, ULB -- Universite Libre de Bruxelles.
294. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.
295. Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465.
     • Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465, April.
     • 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.
296. repec:zbw:bofrdp:037 is not listed on IDEAS
297. Tara M. Sinclair & H.O. Stekler, 2011. "Differences in Early GDP Component Estimates Between Recession and Expansion," Working Papers 2011-05, The George Washington University, Institute for International Economic Policy.
298. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
299. Clements, Michael P., 2006. "Internal consistency of survey respondentsíforecasts: Evidence based on the Survey of Professional Forecasters," Economic Research Papers 269742, University of Warwick - Department of Economics.
     • Clements, Michael P, 2006. "Internal consistency of survey respondents.forecasts : Evidence based on the Survey of Professional Forecasters," The Warwick Economics Research Paper Series (TWERPS) 772, University of Warwick, Department of Economics.
300. Martínez-Martin, Jaime & Morris, Richard & Onorante, Luca & Piersanti, Fabio M., 2019. "Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box," Working Paper Series 2335, European Central Bank.
301. Karine Bouthevillain, 1993. "La prévision macro-économique : précision relative et consensus," Économie et Prévision, Programme National Persée, vol. 108(2), pages 97-126.
302. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
303. Ahmed, Mohamed Shaker & El-Masry, Ahmed A. & Al-Maghyereh, Aktham I. & Kumar, Satish, 2024. "Cryptocurrency volatility: A review, synthesis, and research agenda," Research in International Business and Finance, Elsevier, vol. 71(C).
304. Panagiotis Lazaris & Anastasios Petropoulos & Vasileios Siakoulis & Evangelos Stavroulakis & Nikolaos Vlachogiannakis, 2021. "Interest rate pass through in the deposit and loan products provided by Greek banks," Working Papers 287, Bank of Greece.
305. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
306. Auffhammer, Maximilian, 2007. "The rationality of EIA forecasts under symmetric and asymmetric loss," Resource and Energy Economics, Elsevier, vol. 29(2), pages 102-121, May.
     • Auffhammer, Maximilian, 2005. "The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2ts415ts, Department of Agricultural & Resource Economics, UC Berkeley.
307. Adam Elbourne & Henk Kranendonk & Rob Luginbuhl & Bert Smid & Martin Vromans, 2008. "Evaluating CPB's published GDP growth forecasts; a comparison with individual and pooled VAR based forecasts," CPB Document 172, CPB Netherlands Bureau for Economic Policy Analysis.
308. Kelly, Bryan T. & Moskowitz, Tobias J. & Pruitt, Seth, 2021. "Understanding momentum and reversal," Journal of Financial Economics, Elsevier, vol. 140(3), pages 726-743.
309. 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.
     • Ivana Komunjer & Michael T. Owyang, 2007. "Multivariate forecast evaluation and rationality testing," Working Papers 2007-047, Federal Reserve Bank of St. Louis.
     • Komunjer, Ivana & OWYANG, MICHAEL, 2007. "Multivariate Forecast Evaluation And Rationality Testing," University of California at San Diego, Economics Working Paper Series qt81w8m5sf, Department of Economics, UC San Diego.
310. Lehmann Robert & Wollmershäuser Timo, 2020. "The macroeconomic projections of the German government: A comparison to an independent forecasting institution," German Economic Review, De Gruyter, vol. 21(2), pages 235-270, June.
     • Robert Lehmann & Timo Wollmershäuser, 2019. "The Macroeconomic Projections of the German Government: A Comparison to an Independent Forecasting Institution," CESifo Working Paper Series 7460, CESifo.
311. 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.
312. Thomas Lustenberger & Enzo Rossi, 2022. "The Social Value of Information: A Test of a Beauty and Nonbeauty Contest," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(7), pages 2125-2148, October.
     • Thomas Lustenberger & Dr. Enzo Rossi, 2017. "The Social Value of Information: A Test of a Beauty and Non-Beauty Contest," Working Papers 2017-17, Swiss National Bank.
     • Lustenberger, Thomas & Rossi, Enzo, 2018. "The Social Value of Information: A Test of a Beauty and Non-Beauty Contest," Working papers 2018/05, Faculty of Business and Economics - University of Basel.
313. repec:bof:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
314. Cenesizoglu, Tolga & de Oliveira Ferrazoli Ribeiro, Fabio & Reeves, Jonathan J., 2017. "Beta forecasting at long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 936-957.
315. Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
316. Dean Croushore, 2012. "Forecast bias in two dimensions," Working Papers 12-9, Federal Reserve Bank of Philadelphia.
317. Wu, Xinyu & Hou, Xinmeng, 2020. "Forecasting volatility with component conditional autoregressive range model," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
318. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
     • Giovanni Angelini & Luca De Angelis & Carl Singleton, 2019. "Informational efficiency and behaviour within in-play prediction markets," Economics Discussion Papers em-dp2019-20, Department of Economics, University of Reading, revised 01 Apr 2021.
319. Timmermann, Allan & Burjack, Rafael & Qu, Ritong, 2019. "Fluctuations in Economic Uncertainty and Transmission of Monetary Policy Shocks: Evidence Using Daily Surveys from Brazil," CEPR Discussion Papers 14097, C.E.P.R. Discussion Papers.
320. Hautsch, Nikolaus & Kyj, Lada M. & Malec, Peter, 2011. "The merit of high-frequency data in portfolio allocation," CFS Working Paper Series 2011/24, Center for Financial Studies (CFS).
     • Hautsch, Nikolaus & Kyj, Lada M. & Malec, Peter, 2011. "The merit of high-frequency data in portfolio allocation," SFB 649 Discussion Papers 2011-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
321. Anupam Dutta & Debojyoti Das, 2022. "Forecasting realized volatility: New evidence from time‐varying jumps in VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2165-2189, December.
322. Anastasios Petropoulos & Vasilis Siakoulis & Dionysios Mylonas & Aristotelis Klamargias, 2018. "A combined statistical framework for forecasting default rates of Greek Financial Institutions' credit portfolios," Working Papers 243, Bank of Greece.
323. Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019. "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
324. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2004. "Analytical Evaluation Of Volatility Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(4), pages 1079-1110, November.
     • Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Analytic Evaluation of Volatility Forecasts," CIRANO Working Papers 2002s-90, CIRANO.
325. Brown, Alasdair & Reade, J. James & Vaughan Williams, Leighton, 2019. "When are prediction market prices most informative?," International Journal of Forecasting, Elsevier, vol. 35(1), pages 420-428.
326. Rajesh, Raj & Srivastava, Vineet, 2020. "GDP Growth Forecasts of the Reserve Bank of India – A Performance Assessment," MPRA Paper 104131, University Library of Munich, Germany, revised 11 Oct 2020.
327. Goodhart, Charles & Bin Lim, Wen, 2008. "Do errors in forecasting inflation lead to errors in forecasting interest rates?," LSE Research Online Documents on Economics 24432, London School of Economics and Political Science, LSE Library.
328. repec:zbw:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
329. Ruhnau, Oliver & Hennig, Patrick & Madlener, Reinhard, 2020. "Economic implications of forecasting electricity generation from variable renewable energy sources," Renewable Energy, Elsevier, vol. 161(C), pages 1318-1327.
330. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
331. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage combination from a real-time dataset," CSEF Working Papers 274, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
     • Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
332. 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.
     • Cepni, Oguzhan & Clements, Michael P., 2021. "How Local is the Local Inflation Factor? Evidence from Emerging European Countries," Working Papers 8-2021, Copenhagen Business School, Department of Economics.
333. Choi, Kyongwook & Yu, Wei-Choun & Zivot, Eric, 2010. "Long memory versus structural breaks in modeling and forecasting realized volatility," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 857-875, September.
     • 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.
334. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2021. "The bias and efficiency of the ECB inflation projections: a State dependent analysis," Research Discussion Papers 7/2021, Bank of Finland.
335. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2020. "Revealing forecaster's preferences: A Bayesian multivariate loss function approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 412-437, April.
336. 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.
337. Chiu, Adrian & Wieladek, Tomasz, 2012. "Did output gap measurement improve over time?," Discussion Papers 36, Monetary Policy Committee Unit, Bank of England.
338. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
339. 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.
     • Dimitriadis, Timo & Patton, Andrew J. & Schmidt, Patrick W., 2020. "Testing forecast rationality for measures of central tendency," Hohenheim Discussion Papers in Business, Economics and Social Sciences 12-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
340. Rajkumar Janardanan & Xiao Qiao & K. Geert Rouwenhorst, 2019. "On commodity price limits," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(8), pages 946-961, August.
341. Jörg Breitung & Malte Knüppel, 2021. "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
     • Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
342. Liu, Hung-Chun & Chiang, Shu-Mei & Cheng, Nick Ying-Pin, 2012. "Forecasting the volatility of S&P depositary receipts using GARCH-type models under intraday range-based and return-based proxy measures," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 78-91.
343. Vincent Su & Josephine Su, 1975. "An Evaluation of ASA/NBER Business Outlook Survey Forecasts," NBER Chapters, in: Explorations in Economic Research, Volume 2, number 4, pages 588-618, National Bureau of Economic Research, Inc.
344. Sucarrat, Genaro, 2020. "Identification of Volatility Proxies as Expectations of Squared Financial Return," MPRA Paper 101953, University Library of Munich, Germany.
345. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
346. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
347. Bulkley, George & Harris, Richard D.F. & Nawosah, Vivekanand, 2015. "Can behavioral biases explain the rejections of the expectation hypothesis of the term structure of interest rates?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 179-193.
348. LAURENT, Sébastien & VIOLANTE, Francesco, 2012. "Volatility forecasts evaluation and comparison," LIDAM Reprints CORE 2414, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
349. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
350. Sinclair, Tara M. & Joutz, Fred & Stekler, H.O., 2010. "Can the Fed predict the state of the economy?," Economics Letters, Elsevier, vol. 108(1), pages 28-32, July.
     • Tara Sinclair & Frederick L. Joutz, 2009. "Can the Fed Predict the State of the Economy?," Working Papers 2008-06, The George Washington University, Institute for International Economic Policy.
     • Tara M. Sinclair & Fred Joutz & Herman O. Stekler, 2009. "Can the Fed Predict the State of the Economy?," Working Papers 2009-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Mar 2010.
351. Korbinian Breitrainer & Atanas Hristov, 2015. "Evaluation des Eurozone Economic Outlook," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(24), pages 67-73, December.
352. Cambara, Leilane de Freitas Rocha & Meurer, Roberto & Lima, Gilberto Tadeu, 2022. "Deviating from full rationality but not from theoretical consistency: The behavior of inflation expectations in Brazil," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 492-501.
353. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
     • Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
354. Bleher, Johannes & Dimpfl, Thomas, 2022. "Knitting Multi-Annual High-Frequency Google Trends to Predict Inflation and Consumption," Econometrics and Statistics, Elsevier, vol. 24(C), pages 1-26.
355. Maria Elvira Mancino & Simona Sanfelici, 2011. "Covariance Estimation and Dynamic Asset-Allocation under Microstructure Effects via Fourier Methodology," Palgrave Macmillan Books, in: Greg N. Gregoriou & Razvan Pascalau (ed.), Financial Econometrics Modeling: Market Microstructure, Factor Models and Financial Risk Measures, chapter 1, pages 3-32, Palgrave Macmillan.
     • Mancino Maria Elvira & Simona Sanfelici, 2009. "Covariance estimation and dynamic asset allocation under microstructure effects via Fourier methodology," Working Papers - Mathematical Economics 2009-09, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
356. Selma Chaker & Nour Meddahi, 2013. "A Distributional Approach to Realized Volatility," Staff Working Papers 13-49, Bank of Canada.
357. George A. Christodoulakis & Emmanuel C. Mamatzakis, 2008. "An assessment of the EU growth forecasts under asymmetric preferences," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 483-492.
358. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
359. Jan P. A. M. Jacobs & Simon van Norden, 2010. "Lessons from the latest data on U.S. productivity," Working Papers 11-1, Federal Reserve Bank of Philadelphia.
     • Jan P.A.M. Jacobs & Simon van Norden, 2010. "Lessons From the Latest Data on U.S. Productivity," CAMA Working Papers 2010-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
     • Jan P.A.M. Jacobs & Simon van Norden, 2010. "Lessons From the Latest Data on U.S. Productivity," CIRANO Working Papers 2010s-46, CIRANO.
360. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
361. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
362. Eicher, Theo S. & Kuenzel, David J. & Papageorgiou, Chris & Christofides, Charis, 2019. "Forecasts in times of crises," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1143-1159.
     • Theo S. Eicher & David J. Kuenzel & Mr. Chris Papageorgiou & Mr. Charalambos Christofides, 2018. "Forecasts in Times of Crises," IMF Working Papers 2018/048, International Monetary Fund.
363. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
364. Gellatly, Colin, 1979. "Forecasting N.S.W. Beef Production: An Evaluation of Alternative Techniques," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 47(02), pages 1-14, August.
365. Eduardo Rossi & Paolo Santucci de Magistris, 2013. "A No‐Arbitrage Fractional Cointegration Model for Futures and Spot Daily Ranges," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(1), pages 77-102, January.
366. 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.
367. Mahalia Jackman & Simon Naitram, 2015. "Research Note: Nowcasting Tourist Arrivals in Barbados – Just Google it!," Tourism Economics, , vol. 21(6), pages 1309-1313, December.
368. Aromí, J. Daniel, 2019. "Medium term growth forecasts: Experts vs. simple models," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1085-1099.
369. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
     • Rossi, Barbara, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," CEPR Discussion Papers 14472, C.E.P.R. Discussion Papers.
     • 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.
370. Massimiliano Marcellino & Dalibor Stevanovic, 2022. "The demand and supply of information about inflation," CIRANO Working Papers 2022s-27, CIRANO.
     • Massimiliano Marcellino & Dalibor Stevanovic, 2022. "The demand and supply of information about inflation," Working Papers 22-06, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2022.
371. Michael P. Clements, 2018. "Do Macroforecasters Herd?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 265-292, March.
372. Grömling, Michael, 2002. "Konjunkturprognosen: Methoden, Risiken und Treffsicherheiten," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, vol. 29(2), pages 18-26.
373. Ash, J. C. K. & Smyth, D. J. & Heravi, S. M., 1997. "The accuracy of OECD forecasts of the international economy: balance of payments," Journal of International Money and Finance, Elsevier, vol. 16(6), pages 969-987, December.
374. Huisman, Ronald & Van der Sar, Nico L. & Zwinkels, Remco C.J., 2021. "Volatility expectations and disagreement," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 379-393.
375. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Generalized Dynamic Factor Model + GARCH Exploiting Multivariate Information for Univariate Prediction," LEM Papers Series 2006/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
376. repec:hum:wpaper:sfb649dp2015-023 is not listed on IDEAS
377. A. Amendola & V. Candila, 2016. "Evaluation of volatility predictions in a VaR framework," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 695-709, May.
378. Krog, David Russell, 1988. "Plant-process model corn yield forecasts for Iowa," ISU General Staff Papers 1988010108000010686, Iowa State University, Department of Economics.
379. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
     • Jon Faust & John H. Rogers & Jonathan H. Wright, 2000. "News and noise in G-7 GDP announcements," International Finance Discussion Papers 690, Board of Governors of the Federal Reserve System (U.S.).
380. repec:lan:wpaper:539557 is not listed on IDEAS
381. Solomon Polachek, 2003. "Mincer's Overtaking Point and the Life Cycle Earnings Distribution," Review of Economics of the Household, Springer, vol. 1(4), pages 273-304, December.
     • Solomon Polachek, 2002. "Mincer s Overtaking Point on the Lifecycle Earnings Distribution," LIS Working papers 310, LIS Cross-National Data Center in Luxembourg.
     • Polachek, Solomon, 2003. "Mincer's Overtaking Point and the Lifecycle Earnings Distribution," IZA Discussion Papers 865, Institute of Labor Economics (IZA).
382. Arai, Natsuki & Iizuka, Nobuo & Yamamoto, Yohei, 2022. "The Efficiency of the Government’s Revenue Projections," Discussion paper series HIAS-E-122, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
383. John M Maheu & Thomas H McCurdy, 2007. "Modeling foreign exchange rates with jumps," Working Papers tecipa-279, University of Toronto, Department of Economics.
384. Isengildina-Massa, Olga & MacDonald, Stephen & Xie, Ran, 2012. "A Comprehensive Evaluation of USDA Cotton Forecasts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(1), pages 1-16, April.
385. Verónica Cañal-Fernández, 2012. "Accuracy and reliability of Spanish regional accounts (CRE-95)," Empirical Economics, Springer, vol. 43(3), pages 1299-1320, December.
386. Chiu Adrian & Wieladek Tomasz, 2013. "Is the “Great Recession” really so different from the past?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 1037-1084, October.
     • Chiu, Adrian & Wieladek, Tomasz, 2015. "Is the ‘Great Recession’ really so different from the past?," Discussion Papers 40, Monetary Policy Committee Unit, Bank of England.
387. Schrimpf, Andreas & Wang, Qingwei, 2010. "A reappraisal of the leading indicator properties of the yield curve under structural instability," International Journal of Forecasting, Elsevier, vol. 26(4), pages 836-857, October.
388. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
389. 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.
390. David Edmund Allen, 2020. "Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?," JRFM, MDPI, vol. 13(9), pages 1-25, September.
391. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
392. Janis Becker & Christian Leschinski, 2021. "Estimating the volatility of asset pricing factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 269-278, March.
     • Becker, Janis & Leschinski, Christian, 2018. "Estimating the Volatility of Asset Pricing Factors," Hannover Economic Papers (HEP) dp-631, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
393. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
394. Monique Reid & Pierre Siklos, 2023. "Rationality and biases insights from disaggregated firm level inflation expectations data," Working Papers 11050, South African Reserve Bank.
395. Smets, Frank & Warne, Anders & Wouters, Rafael, 2014. "Professional forecasters and real-time forecasting with a DSGE model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 981-995.
396. Papastamos, Dimitrios & Matysiak, George & Stevenson, Simon, 2015. "Assessing the accuracy and dispersion of real estate investment forecasts," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 141-152.
397. 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.
     • Chun Liu & John M Maheu, 2007. "Are there Structural Breaks in Realized Volatility?," Working Papers tecipa-304, University of Toronto, Department of Economics.
398. Brinca Pedro, 2013. "Monetary business cycle accounting for Sweden," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 1085-1119, October.
399. Thomas Jonsson & Pär Österholm, 2012. "The properties of survey-based inflation expectations in Sweden," Empirical Economics, Springer, vol. 42(1), pages 79-94, February.
     • Jonsson, Thomas & Österholm, Pär, 2009. "The Properties of Survey-Based Inflation Expectations in Sweden," Working Papers 114, National Institute of Economic Research.
400. Pierdzioch, Christian, 2023. "A bootstrap-based efficiency test of growth and inflation forecasts for Germany," Economics Letters, Elsevier, vol. 224(C).
401. Bizzozero, Paolo & Flepp, Raphael & Franck, Egon, 2018. "The effect of fast trading on price discovery and efficiency: Evidence from a betting exchange," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 126-143.
402. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Aug 2024.
403. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," PIER Working Paper Archive 05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
     • 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).
     • Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," NBER Working Papers 11188, National Bureau of Economic Research, Inc.
404. Butler, David & Butler, Robert & Eakins, John, 2021. "Expert performance and crowd wisdom: Evidence from English Premier League predictions," European Journal of Operational Research, Elsevier, vol. 288(1), pages 170-182.
405. Aramonte, Sirio & Giudice Rodriguez, Marius del & Wu, Jason, 2013. "Dynamic factor Value-at-Risk for large heteroskedastic portfolios," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4299-4309.
     • Sirio Aramonte & Marius del Giudice Rodriguez & Jason J. Wu, 2011. "Dynamic factor value-at-risk for large, heteroskedastic portfolios," Finance and Economics Discussion Series 2011-19, Board of Governors of the Federal Reserve System (U.S.).
406. Katharina Glass, 2018. "Predictability of Euro Area Revisions," Macroeconomics and Finance Series 201801, University of Hamburg, Department of Socioeconomics.
407. Guillaume Marois & Patrick Sabourin & Alain Bélanger, 2020. "Implementing Dynamics of Immigration Integration in Labor Force Participation Projection in EU28," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 39(2), pages 339-363, April.
408. Yves Dominicy & Harry-Paul Vander Elst, 2015. "Macro-Driven VaR Forecasts: From Very High to Very Low Frequency Data," Working Papers ECARES ECARES 2015-41, ULB -- Universite Libre de Bruxelles.
409. Yang, Cai & Gong, Xu & Zhang, Hongwei, 2019. "Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect," Resources Policy, Elsevier, vol. 61(C), pages 548-563.
410. Roland Döhrn, 2023. "Are German National Accounts informationally efficient?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 23-42, March.
411. Berge, Travis J., 2018. "Understanding survey-based inflation expectations," International Journal of Forecasting, Elsevier, vol. 34(4), pages 788-801.
     • Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
412. 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.
     • Tae-Hwy Lee & Yiyao Wang, 2014. "Asymmetric Loss in the Greenbook and the Survey of Professional Forecasters," Working Papers 201407, University of California at Riverside, Department of Economics.
413. Sinha, Pankaj & Jayaraman, Prabha, 2012. "Empirical analysis of the forecast error impact of classical and bayesian beta adjustment techniques," MPRA Paper 37662, University Library of Munich, Germany.
414. Gebhard Kirchgässner, 2005. "On the Rationality of the General Public," University of St. Gallen Department of Economics working paper series 2005 2005-13, Department of Economics, University of St. Gallen.
415. Jack Narayan & James Cicarelli, 1982. "A Note on the Informational Contents of Alternative Forecasting Benchmarks," Eastern Economic Journal, Eastern Economic Association, vol. 8(4), pages 309-314, Oct-Dec.
416. Jones, Jacob T. & Sinclair, Tara M. & Stekler, Herman O., 2020. "A textual analysis of Bank of England growth forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1478-1487.
     • Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised May 2019.
417. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
418. Peter Hansen & Asger Lunde, 2003. "Consistent Preordering with an Estimated Criterion Function, with an Application to the Evaluation and Comparison of Volatility Models," Working Papers 2003-01, Brown University, Department of Economics.
419. 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.
420. Zhongjun Qu & Pierre Perron, 2008. "A Stochastic Volatility Model with Random Level Shifts: Theory and Applications to S&P 500 and NASDAQ Return Indices," Boston University - Department of Economics - Working Papers Series wp2008-007, Boston University - Department of Economics.
421. 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.
422. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
     • Bucci, Andrea, 2017. "Forecasting realized volatility: a review," MPRA Paper 83232, University Library of Munich, Germany.
423. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
424. repec:zbw:bofrdp:2021_007 is not listed on IDEAS
425. Clements, Michael P., 2021. "Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 37(2), pages 634-646.
     • Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
426. Hiroyuki Kawakatsu, 2021. "Information in daily data volatility measurements," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1642-1656, April.
427. George Babich & John Goodhew, 1978. "Short Term Econometric Forecasting and Seasonal Adjustment," The Economic Record, The Economic Society of Australia, vol. 54(2), pages 229-236, August.
428. Henning Fischer & Marta García-Bárzana & Peter Tillmann & Peter Winker, 2014. "Evaluating FOMC forecast ranges: an interval data approach," Empirical Economics, Springer, vol. 47(1), pages 365-388, August.
     • Henning Fischer & Marta García-Bárzana & Peter Tillmann & Peter Winker, 2012. "Evaluating FOMC forecast ranges: an interval data approach," MAGKS Papers on Economics 201213, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
429. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
430. Martin M. Andreasen & Andrew C. Meldrum, 2018. "A Shadow Rate or a Quadratic Policy Rule? The Best Way to Enforce the Zero Lower Bound in the United States," Finance and Economics Discussion Series 2018-056, Board of Governors of the Federal Reserve System (U.S.).
431. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
432. Chaker Aloui & Hela BEN HAMIDA, 2015. "Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 30-54, January.
433. 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.
     • Massimo Guidolin & Francesco Chincoli, 2017. "Linear and Nonlinear Predictability in Investment Style Factors: Multivariate Evidence," BAFFI CAREFIN Working Papers 1754, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
434. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
435. repec:lan:wpaper:413 is not listed on IDEAS
436. Jef Vuchelen & Maria-Isabel Gutierrez, 2005. "Do the OECD 24 month horizon growth forecasts for the G7-countries contain information?," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 855-862.
437. Bob Krebs, 2019. "Revisions to Quarterly National Accounts data in Luxembourg," BCL working papers 136, Central Bank of Luxembourg.
438. Jacobs, Jan P.A.M. & van Norden, Simon, 2016. "Why are initial estimates of productivity growth so unreliable?," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 200-213.
439. Florian Peters & Simas Kucinskas, 2018. "Measuring Biases in Expectation Formation," Tinbergen Institute Discussion Papers 18-058/IV, Tinbergen Institute.
440. Didier Borowski & Carine Bouthevillain & Catherine Doz & Pierre Malgrange & Pierre Morin, 1991. "Vingt ans de prévisions macro-économiques : une évaluation sur données françaises," Économie et Prévision, Programme National Persée, vol. 99(3), pages 43-65.
441. Dwight R. Sanders & Mark R. Manfredo, 2008. "Multiple horizons and information in USDA production forecasts," Agribusiness, John Wiley & Sons, Ltd., vol. 24(1), pages 55-66.
     • Sanders, Dwight R. & Manfredo, Mark R., 2006. "Multiple Horizons and Information in USDA Production Forecasts," 2006 Conference, April 17-18, 2006, St. Louis, Missouri 18997, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
442. Sarno, Lucio & Thornton, Daniel L & Valente, Giorgio, 2005. "Federal Funds Rate Prediction," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 449-471, June.
     • Sarno, Lucio & Daniel l Thornton & Giorgio Valente, 2003. "Federal Funds Rate Prediction," Royal Economic Society Annual Conference 2003 183, Royal Economic Society.
     • Lucio Sarno & Daniel L. Thornton & Giorgio Valente, 2004. "Federal funds rate prediction," Working Papers 2002-005, Federal Reserve Bank of St. Louis.
     • Sarno, Lucio & Thornton, Daniel L & Valente, Giorgio, 2004. "Federal Funds Rate Prediction," CEPR Discussion Papers 4587, C.E.P.R. Discussion Papers.
443. Yoichi Tsuchiya, 2021. "The value added of the Bank of Japan's range forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 817-833, August.
444. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
445. Lixiong Yang, 2020. "State-dependent biases and the quality of China’s preliminary GDP announcements," Empirical Economics, Springer, vol. 59(6), pages 2663-2687, December.
446. 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.
447. Filippo Gusella & Giorgio Ricchiuti, 2022. "A State-Space Approach for Time-Series Prediction of an Heterogeneous Agent Model," Working Papers - Economics wp2022_20.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
448. Kuruc, Kevin, 2022. "Are IMF rescue packages effective? A synthetic control analysis of macroeconomic crises," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 38-53.
449. Eicher, Theo S. & Rollinson, Yuan Gao, 2023. "The accuracy of IMF crises nowcasts," International Journal of Forecasting, Elsevier, vol. 39(1), pages 431-449.
450. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
451. Thomakos, Dimitrios D. & Guerard, John Jr., 2004. "Naive, ARIMA, nonparametric, transfer function and VAR models: A comparison of forecasting performance," International Journal of Forecasting, Elsevier, vol. 20(1), pages 53-67.
452. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
453. David Feldman & Xin Xu, 2018. "Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles)," Annals of Operations Research, Springer, vol. 262(2), pages 493-518, March.
454. Schanne, Norbert, 2012. "The formation of experts' expectations on labour markets : do they run with the pack?," IAB-Discussion Paper 201225, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
455. Maghyereh Aktham Issa & Awartani Basel, 2012. "Modeling and Forecasting Value-at-Risk in the UAE Stock Markets: The Role of Long Memory, Fat Tails and Asymmetries in Return Innovations," Review of Middle East Economics and Finance, De Gruyter, vol. 8(1), pages 1-22, August.
456. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
457. Pirschel, Inske & Wolters, Maik H., 2014. "Forecasting German key macroeconomic variables using large dataset methods," Kiel Working Papers 1925, Kiel Institute for the World Economy (IfW Kiel).
     • Pirschel, Inske & Wolters, Maik, 2014. "Forecasting German key macroeconomic variables using large dataset methods," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100587, Verein für Socialpolitik / German Economic Association.
458. Ayala, Astrid & Blazsek, Szabolcs, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
459. 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.
460. Oikonomou, Ioannis & Stancu, Andrei & Symeonidis, Lazaros & Wese Simen, Chardin, 2019. "The information content of short-term options," Journal of Financial Markets, Elsevier, vol. 46(C).
461. Guy, Kester & Lowe, Shane, 2012. "Tracing the Liquidity Effects on Bank Stability in Barbados," MPRA Paper 52205, University Library of Munich, Germany.
462. Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020. "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, vol. 58(1), pages 107-137, January.
463. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
     • Philip Ramirez & J. James Reade & Carl Singleton, 2021. "Betting on a buzz, mispricing and inefficiency in online sportsbooks," Economics Discussion Papers em-dp2021-10, Department of Economics, University of Reading, revised 27 Jul 2022.
464. Frantisek Brazdik & Zuzana Humplova & Frantisek Kopriva, 2014. "Evaluating a Structural Model Forecast: Decomposition Approach," Research and Policy Notes 2014/02, Czech National Bank.
     • Frantisek Brazdik & Zuzana Humplova & Frantisek Kopriva, 2015. "Evaluating a Structural Model Forecast: Decomposition Approach," Working Papers 2015/12, Czech National Bank.
465. Bermingham, Colin, 2006. "A Look at Data Revisions in the Quarterly National Accounts," Quarterly Bulletin Articles, Central Bank of Ireland, pages 93-105, July.
466. Ruud H. Koning & Renske Zijm, 2023. "Betting market efficiency and prediction in binary choice models," Annals of Operations Research, Springer, vol. 325(1), pages 135-148, June.
467. 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.
468. Gregory Connor & Lisa R. Goldberg & Robert A. Korajczyk, 2010. "Portfolio Risk Analysis," Economics Books, Princeton University Press, edition 1, number 9224.
469. Goodhart, Charles & Bin Lim, Wen, 2008. "Interest rate forecasts: a pathology," LSE Research Online Documents on Economics 24431, London School of Economics and Political Science, LSE Library.
470. Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
471. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
     • Andrew Patton, 2006. "Volatility Forecast Comparison using Imperfect Volatility Proxies," Research Paper Series 175, Quantitative Finance Research Centre, University of Technology, Sydney.
472. Angus Campbell & Daniel R. Smith, 2022. "An empirical investigation of the quality of value‐at‐risk disclosure in Australia," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(1), pages 469-491, March.
473. David E. Rapach & Jack K. Strauss, 2005. "Forecasting employment growth in Missouri with many potentially relevant predictors: an analysis of forecast combining methods," Regional Economic Development, Federal Reserve Bank of St. Louis, issue Nov, pages 97-112.
474. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
475. Youssef, Manel & Belkacem, Lotfi & Mokni, Khaled, 2015. "Value-at-Risk estimation of energy commodities: A long-memory GARCH–EVT approach," Energy Economics, Elsevier, vol. 51(C), pages 99-110.
476. Hakki Ozturk & Umit Erol & Asli Yuksel, 2016. "Extreme Value Volatility Estimators and Realized Volatility of Istanbul Stock Exchange: Evidence from Emerging Market," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(8), pages 1-71, August.
477. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
478. Carl Bonham & Richard Cohen & Shigeyuki Abe, 2006. "The Rationality and Heterogeneity of Survey Forecasts of the Yen-Dollar Exchange Rate: A Reexamination," Working Papers 200611, University of Hawaii at Manoa, Department of Economics.
479. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
480. Jeff Fleming & Chris Kirby, 2013. "Component-Driven Regime-Switching Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 263-301, March.
481. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
482. Boskabadi, Elahe, 2022. "Economic policy uncertainty and forecast bias in the survey of professional forecasters," MPRA Paper 115081, University Library of Munich, Germany.
483. Caroline Flodberg & Pär Österholm, 2017. "A Statistical Anaysis of Revisions in Swedish National Accounts Data," Finnish Economic Papers, Finnish Economic Association, vol. 28(1), pages 10-33, Autumn.
     • Flodberg, Caroline & Österholm, Pär, 2015. "A Statistical Analysis of Revisions of Swedish National Accounts Data," Working Papers 136, National Institute of Economic Research.
484. 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.
485. Victor Zarnowitz, 1982. "Expectations and Forecasts from Business Outlook Surveys," NBER Working Papers 0845, National Bureau of Economic Research, Inc.
486. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "A No Arbitrage Fractional Cointegration Analysis Of The Range Based Volatility," CREATES Research Papers 2009-31, Department of Economics and Business Economics, Aarhus University.
487. Kaelo Ntwaepelo & Grivas Chiyaba, 2022. "Financial Stability Surveillance Tools: Evaluating the Performance of Stress Indices," Economics Discussion Papers em-dp2022-06, Department of Economics, University of Reading.
488. Chaker Aloui, 2015. "Volatility forecasting and risk management in some MENA stock markets: a nonlinear framework," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 5(2), pages 160-192.
489. Çelik, Sibel & Ergin, Hüseyin, 2014. "Volatility forecasting using high frequency data: Evidence from stock markets," Economic Modelling, Elsevier, vol. 36(C), pages 176-190.
490. Pincheira, Pablo & Hardy, Nicolas, 2020. "The Mean Squared Prediction Error Paradox: A summary," MPRA Paper 105020, University Library of Munich, Germany.
491. repec:ags:jrapmc:122314 is not listed on IDEAS
492. Peter, Eckley, 2015. "(Non)rationality of consumer inflation perceptions," MPRA Paper 77082, University Library of Munich, Germany.
493. Visser, Marcel P., 2008. "Forecasting S&P 500 Daily Volatility using a Proxy for Downward Price Pressure," MPRA Paper 11100, University Library of Munich, Germany.
494. Reade, J. James & Vaughan Williams, Leighton, 2019. "Polls to probabilities: Comparing prediction markets and opinion polls," International Journal of Forecasting, Elsevier, vol. 35(1), pages 336-350.
495. Blagov, Boris & Krause, Clara & Schmidt, Torsten & Exß, Franziska & Heinisch, Katja & Holtemöller, Oliver, 2024. "Frühzeitige Ermittlung stabiler Ergebnisse zum Bruttoinlandsprodukt bzw. realen Wirtschaftswachstum und der Bruttowertschöpfung auf Länderebene. Endbericht," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 296879, Fall.
496. Hempenius, A.L., 1981. "Forecast accuracy analysis : Applied to forecasts of the Dutch Central Planning Bureau, 1964-1978," Other publications TiSEM d96d78f5-f5e0-43f3-93c2-6, Tilburg University, School of Economics and Management.
497. Kempkes, Gerhard, 2012. "Cyclical adjustment in fiscal rules: Some evidence on real-time bias for EU-15 countries," Discussion Papers 15/2012, Deutsche Bundesbank.
498. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
499. repec:zbw:bofitp:2015_012 is not listed on IDEAS
500. Bespalova, Olga, 2020. "GDP forecasts: Informational asymmetry of the SPF and FOMC minutes," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1531-1540.
501. Eddie Casey & Diarmaid Smyth, 2016. "Revisions to Macroeconomic Data: Ireland and the OECD," The Economic and Social Review, Economic and Social Studies, vol. 47(1), pages 33-68.
502. Yasemin Ulu, 2015. "Rationality of inflation-output forecasts of MMS survey: international evidence," Applied Economics, Taylor & Francis Journals, vol. 47(12), pages 1187-1198, March.
503. 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.
504. Wang, Weichen & An, Ran & Zhu, Ziwei, 2024. "Volatility prediction comparison via robust volatility proxies: An empirical deviation perspective," Journal of Econometrics, Elsevier, vol. 239(2).
505. Miller, Thomas W. & Rapach, David E., 2013. "An intra-week efficiency analysis of bookie-quoted NFL betting lines in NYC," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 10-23.
506. Klaus-Peter Hellwig, 2018. "Overfitting in Judgment-based Economic Forecasts: The Case of IMF Growth Projections," IMF Working Papers 2018/260, International Monetary Fund.
507. Andrew J. Patton & Allan Timmermann, 2005. "Testable Implications of Forecast Optimality," STICERD - Econometrics Paper Series 485, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
     • 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.
508. Ralf Fendel & Jan Heins & Oliver Mohr, 2020. "The Effect of the ECB’s Forward Guidance on Interest Rate Forecasts," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 12(8), pages 1-52, August.
509. Clements, Michael P., 2021. "Rounding behaviour of professional macro-forecasters," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1614-1631.
510. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
511. repec:hum:wpaper:sfb649dp2011-059 is not listed on IDEAS
512. Catherine Doz, 1993. "Note sur les tests de rationalité des prévisions," Économie et Prévision, Programme National Persée, vol. 108(2), pages 129-133.
513. Nikolay Gospodinov, 2016. "The role of commodity prices in forecasting U.S. core inflation," FRB Atlanta Working Paper 2016-5, Federal Reserve Bank of Atlanta.
514. Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
515. McMillan, David G. & Kambouroudis, Dimos, 2009. "Are RiskMetrics forecasts good enough? Evidence from 31 stock markets," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 117-124, June.
516. André Binette & Dmitri Tchebotarev, 2017. "Evaluating Real GDP Growth Forecasts in the Bank of Canada Monetary Policy Report," Staff Analytical Notes 17-21, Bank of Canada.
517. repec:zbw:rwirep:0177 is not listed on IDEAS
518. Bengtsson, Ola & Ekeblom, Daniel, 2014. "The Bright but Right View? New Evidence on Entrepreneurial Optimism," Working Papers 2014:1, Lund University, Department of Economics.
519. Enders, Walter & Pascalau, Razvan, 2015. "Pretesting for multi-step-ahead exchange rate forecasts with STAR models," International Journal of Forecasting, Elsevier, vol. 31(2), pages 473-487.
520. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
521. Jaehyuk Choi & Desheng Ge & Kyu Ho Kang & Sungbin Sohn, 2023. "Yield spread selection in predicting recession probabilities," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1772-1785, November.
522. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
523. Bengtsson, Ola & Ekeblom, Daniel, 2014. "The Bright but Right View? A New Type of Evidence on Entrepreneurial Optimism," Working Paper Series 1008, Research Institute of Industrial Economics.
524. Victor Zarnowitz, 1983. "Rational Expectations and Macroeconomic Forecasts," NBER Working Papers 1070, National Bureau of Economic Research, Inc.
525. Brown, Alasdair & Yang, Fuyu, 2019. "The wisdom of large and small crowds: Evidence from repeated natural experiments in sports betting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 288-296.
526. St'ephane Chr'etien & Juan-Pablo Ortega, 2011. "Multivariate GARCH estimation via a Bregman-proximal trust-region method," Papers 1101.5475, arXiv.org.
527. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
     • Linlin Niu & Xiu Xu & Ying Chen, 2015. "An Adaptive Approach to Forecasting Three Key Macroeconomic Variables for Transitional China," SFB 649 Discussion Papers SFB649DP2015-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
     • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland, Institute for Economies in Transition.
528. Etienne, Xiaoli L. & Farhangdoost, Sara & Hoffman, Linwood A. & Adam, Brian D., 2023. "Forecasting the U.S. season-average farm price of corn: Derivation of an alternative futures-based forecasting model," Journal of Commodity Markets, Elsevier, vol. 30(C).
529. Hempenius, A.L., 1981. "Forecast accuracy analysis : Applied to forecasts of the Dutch Central Planning Bureau, 1964-1978," Research Memorandum FEW 90, Tilburg University, School of Economics and Management.
530. Mr. Charalambos G Tsangarides, 2010. "Crisis and Recovery: Role of the Exchange Rate Regime in Emerging Market Countries," IMF Working Papers 2010/242, International Monetary Fund.
531. Sucarrat, Genaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.
532. McMillan, David G. & Speight, Alan E.H. & Evans, Kevin P., 2008. "How useful is intraday data for evaluating daily Value-at-Risk?: Evidence from three Euro rates," Journal of Multinational Financial Management, Elsevier, vol. 18(5), pages 488-503, December.
533. Gharsallah, Sofian & Sucarrat, Genaro, 2019. "Hvor presise er prognosene i Nasjonalbudsjettet? [How precise are the forecasts of the Norwegian national budget?]," MPRA Paper 96850, University Library of Munich, Germany.
534. Silvia Muzzioli & Luca Gambarelli & Bernard Baets, 2020. "Option implied moments obtained through fuzzy regression," Fuzzy Optimization and Decision Making, Springer, vol. 19(2), pages 211-238, June.
535. Victor Zarnowitz, 1978. "On the Accuracy and Properties of Recent Macroeconomic Forecasts," NBER Working Papers 0229, National Bureau of Economic Research, Inc.
536. repec:wyi:journl:002213 is not listed on IDEAS
537. Helder Ferreira de Mendonça & Pedro Mendes Garcia & José Valentim Machado Vicente, 2021. "Rationality and anchoring of inflation expectations: An assessment from survey‐based and market‐based measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1027-1053, September.
538. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.
539. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
540. 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.
541. Lauter, Tobias & Prokopczuk, Marcel, 2022. "Measuring commodity market quality," Journal of Banking & Finance, Elsevier, vol. 145(C).
542. Sucarrat, Genaro, 2021. "Identification of volatility proxies as expectations of squared financial returns," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1677-1690.
543. Dutta, Anupam & Park, Donghyun & Uddin, Gazi Salah & Kanjilal, Kakali & Ghosh, Sajal, 2024. "Do dirty and clean energy investments react to infectious disease-induced uncertainty?," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
544. Sergey V. Smirnov, 2014. "Predicting US Recessions: Does a Wishful Bias Exist?," HSE Working papers WP BRP 77/EC/2014, National Research University Higher School of Economics.
545. 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.
546. Hegarty, Tadgh & Whelan, Karl, 2024. "Comparing Two Methods for Testing the Efficiency of Sports Betting Markets," MPRA Paper 121382, University Library of Munich, Germany.
547. Vuchelen, Jef & Gutierrez, Maria-Isabel, 2005. "A direct test of the information content of the OECD growth forecasts," International Journal of Forecasting, Elsevier, vol. 21(1), pages 103-117.
548. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
549. Ariful Hoque & Chandrasekhar Krishnamurti, 2012. "Modeling moneyness volatility in measuring exchange rate volatility," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 8(4), pages 365-380, September.
550. Bermingham, Colin, 2006. "An Examination of Data Revisions in the Quarterly National Accounts," Research Technical Papers 10/RT/06, Central Bank of Ireland.
551. Kyriazi, Foteini & Thomakos, Dimitrios D. & Guerard, John B., 2019. "Adaptive learning forecasting, with applications in forecasting agricultural prices," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1356-1369.
552. Bogoev, Jane & Ramadani, Gani, 2012. "GDP Data Revisions in Macedonia – Is There Any Systematic Pattern?," MPRA Paper 70170, University Library of Munich, Germany, revised Sep 2014.
553. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.
554. Philip Hans Franses, 2021. "Testing bias in professional forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1086-1094, September.
555. Andersson, Michael K. & Karlsson, Gustav & Svensson, Josef, 2007. "The Riksbank’s Forecasting Performance," Working Paper Series 218, Sveriges Riksbank (Central Bank of Sweden).
556. repec:dgr:rugsom:12010-eef is not listed on IDEAS
557. Güçbilmez, Ufuk, 2014. "Why do some Chinese technology firms avoid ChiNext and go public in the US?," International Review of Financial Analysis, Elsevier, vol. 36(C), pages 179-194.
558. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.
559. Weyerstrass, Klaus, 2015. "Forecasting Accuracy of a Multi-Country Macroeconometric Model for the Former Yugoslavia/Capacidad predictiva de los modelos estructurales frente a modelos de series temporales. Aplicación a un sistem," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 463-486, Mayo.
560. William J. Procasky & Anwen Yin, 2022. "Forecasting high‐yield equity and CDS index returns: Does observed cross‐market informational flow have predictive power?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1466-1490, August.