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Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics
Citations
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Cited by:
- Panagiotis Schizas & Dimitrios D. Thomakos, 2015. "Market timing and trading strategies using asset rotation: non-neutral market positioning for exploiting arbitrage opportunities," Quantitative Finance, Taylor & Francis Journals, vol. 15(2), pages 285-298, February.
- Hashmat Khan & Santosh Upadhayaya, 2020.
"Does business confidence matter for investment?,"
Empirical Economics, Springer, vol. 59(4), pages 1633-1665, October.
- Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
- Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Anthony S. Tay & Yiu Kuen Tse, 2006.
"Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics: International Evidence,"
PIER Working Paper Archive
06-016, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Anthony S. Tay & Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22481, East Asian Bureau of Economic Research.
- Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Anthony S. Tay & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22075, East Asian Bureau of Economic Research.
- Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
- Großmaß Lidan, 2014. "Liquidity and the Value at Risk," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(5), pages 572-602, October.
- Suzanne G. M. Fifield & David G. McMillan & Fiona J. McMillan, 2020. "Is there a risk and return relation?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(11), pages 1075-1101, July.
- 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.
- Filip Žikeš & Jozef Baruník, 2016.
"Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility,"
Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
- Filip Zikes & Jozef Barunik, 2013. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," Papers 1308.4276, arXiv.org.
- Žikeš, Filip & Baruník, Jozef, 2014. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," FinMaP-Working Papers 20, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Henriques, Irene & Sadorsky, Perry, 2023. "Forecasting rare earth stock prices with machine learning," Resources Policy, Elsevier, vol. 86(PA).
- Nyberg, Henri & Pönkä, Harri, 2016.
"International sign predictability of stock returns: The role of the United States,"
Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
- Henri Nyberg & Harri Pönkä, 2015. "International Sign Predictability of Stock Returns: The Role of the United States," CREATES Research Papers 2015-20, Department of Economics and Business Economics, Aarhus University.
- Gradojevic, Nikola & Erdemlioglu, Deniz & Gençay, Ramazan, 2020.
"A new wavelet-based ultra-high-frequency analysis of triangular currency arbitrage,"
Economic Modelling, Elsevier, vol. 85(C), pages 57-73.
- Nikola Gradojevic & Deniz Erdemlioglu & Ramazan Gençay, 2020. "A new wavelet-based ultra-high-frequency analysis of triangular currency arbitrage," Post-Print hal-02512423, HAL.
- Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017.
"Spillovers from the United States to Latin American and G7 stock markets: A VAR quantile analysis,"
Emerging Markets Review, Elsevier, vol. 31(C), pages 32-46.
- Helena Chuliá & Montserrat Guillén & Jorge M. Uribe, 2015. "“Spillovers From the United States to Latin American and G7 Stock Markets: a VAR Quantile Analysis”," IREA Working Papers 201525, University of Barcelona, Research Institute of Applied Economics, revised Oct 2015.
- Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578.
- Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
- Huck, Nicolas, 2010. "Pairs trading and outranking: The multi-step-ahead forecasting case," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1702-1716, December.
- Gao, Jiti & Liu, Fei & Peng, Bin & Yan, Yayi, 2023.
"Binary response models for heterogeneous panel data with interactive fixed effects,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 1654-1679.
- Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
- Firat Melih Yilmaz & Engin Yildiztepe, 2024. "Statistical Evaluation of Deep Learning Models for Stock Return Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 221-244, January.
- Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
- 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).
- Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
- Rick Bohte & Luca Rossini, 2019.
"Comparing the Forecasting of Cryptocurrencies by Bayesian Time-Varying Volatility Models,"
JRFM, MDPI, vol. 12(3), pages 1-18, September.
- Rick Bohte & Luca Rossini, 2019. "Comparing the forecasting of cryptocurrencies by Bayesian time-varying volatility models," Papers 1909.06599, arXiv.org.
- Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2021.
"Return signal momentum,"
Journal of Banking & Finance, Elsevier, vol. 124(C).
- Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2019. "Return Signal Momentum," QBS Working Paper Series 2019/04, Queen's University Belfast, Queen's Business School.
- Stelios Bekiros & Dimitris Georgoutsos, 2008. "Non-linear dynamics in financial asset returns: the predictive power of the CBOE volatility index," The European Journal of Finance, Taylor & Francis Journals, vol. 14(5), pages 397-408.
- Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2023. "Estimation and Inference for a Class of Generalized Hierarchical Models," Papers 2311.02789, arXiv.org, revised Apr 2024.
- Harri Pönkä, 2017.
"Predicting the direction of US stock markets using industry returns,"
Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
- Pönkä, Harri, 2014. "Predicting the direction of US stock markets using industry returns," MPRA Paper 62942, University Library of Munich, Germany.
- Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
- Fiorentini, Gabriele & Sentana, Enrique, 2021.
"New testing approaches for mean–variance predictability,"
Journal of Econometrics, Elsevier, vol. 222(1), pages 516-538.
- Gabriele Fiorentini & Enrique Sentana, 2018. "New Testing Approaches for Mean-Variance Predictability," Working Papers wp2018_1814, CEMFI.
- Gabriele Fiorentini & Enrique Sentana, 2019. "New testing approaches for mean-variance predictability," Working Paper series 19-01, Rimini Centre for Economic Analysis.
- Sentana, Enrique & Fiorentini, Gabriele, 2019. "New testing approaches for mean-variance predictability," CEPR Discussion Papers 13426, C.E.P.R. Discussion Papers.
- Gabriele Fiorentini & Enrique Sentana, 2019. "New testing approaches for mean-variance predictability," Econometrics Working Papers Archive 2019_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
- Gilbert W. Bassett, 2004.
"Pessimistic Portfolio Allocation and Choquet Expected Utility,"
Journal of Financial Econometrics, Oxford University Press, vol. 2(4), pages 477-492.
- Gilbert W. Bassett Jr Bassett & Roger Koenker & Gregory Kordas, 2004. "Pessimistic portfolio allocation and Choquet expected utility," CeMMAP working papers CWP09/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- James W. Taylor & Keming Yu, 2016. "Using auto-regressive logit models to forecast the exceedance probability for financial risk management," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1069-1092, October.
- Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
- Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
- Weijia Peng & Chun Yao, 2023. "Sector-level equity returns predictability with machine learning and market contagion measure," Empirical Economics, Springer, vol. 65(4), pages 1761-1798, October.
- Fokianos, Konstantinos & Moysiadis, Theodoros, 2017. "Binary time series models driven by a latent process," Econometrics and Statistics, Elsevier, vol. 2(C), pages 117-130.
- Ender Su & John Bilson, 2011. "Trading asymmetric trend and volatility by leverage trend GARCH in Taiwan stock index," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3891-3905.
- Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
- Liu, Xiaochun, 2015.
"Modeling time-varying skewness via decomposition for out-of-sample forecast,"
International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
- Liu, Xiaochun, 2011. "Modeling the time-varying skewness via decomposition for out-of-sample forecast," MPRA Paper 41248, University Library of Munich, Germany.
- Roch, Oriol, 2013. "Histogram-based prediction of directional price relatives," Finance Research Letters, Elsevier, vol. 10(3), pages 110-115.
- Haibin Xie & Yuying Sun & Pengying Fan, 2023. "Return direction forecasting: a conditional autoregressive shape model with beta density," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
- Harri Pönkä, 2018.
"Sentiment and sign predictability of stock returns,"
Economics Bulletin, AccessEcon, vol. 38(3), pages 1676-1684.
- Pönkä, Harri, 2017. "Sentiment and sign predictability of stock returns," MPRA Paper 81861, University Library of Munich, Germany.
- Lu, Fei & Ma, Feng & Guo, Qiang, 2023. "Less is more? New evidence from stock market volatility predictability," International Review of Financial Analysis, Elsevier, vol. 89(C).
- Guidolin, Massimo & Timmermann, Allan, 2006.
"Term structure of risk under alternative econometric specifications,"
Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
- Timmermann, Allan & Guidolin, Massimo, 2004. "Term Structure of Risk Under Alternative Econometric Specifications," CEPR Discussion Papers 4645, C.E.P.R. Discussion Papers.
- Massimo Guidolin & Allan Timmerman, 2005. "Term structure of risk under alternative econometric specifications," Working Papers 2005-001, Federal Reserve Bank of St. Louis.
- Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
- Pönkä, Harri, 2016.
"Real oil prices and the international sign predictability of stock returns,"
Finance Research Letters, Elsevier, vol. 17(C), pages 79-87.
- Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
- Sina Ehsani & Juhani T. Linnainmaa, 2022. "Factor Momentum and the Momentum Factor," Journal of Finance, American Finance Association, vol. 77(3), pages 1877-1919, June.
- Bruno Spilak & Wolfgang Karl Härdle, 2022.
"Tail-Risk Protection: Machine Learning Meets Modern Econometrics,"
Springer Books, in: Cheng-Few Lee & Alice C. Lee (ed.), Encyclopedia of Finance, edition 0, chapter 92, pages 2177-2211,
Springer.
- Spilak, Bruno & Härdle, Wolfgang Karl, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," IRTG 1792 Discussion Papers 2020-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
- de Resende, Charlene C. & Pereira, Adriano C.M. & Cardoso, Rodrigo T.N. & de Magalhães, A.R. Bosco, 2017. "Investigating market efficiency through a forecasting model based on differential equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 199-212.
- Syed Abul, Basher & Perry, Sadorsky, 2022. "Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?," MPRA Paper 113293, University Library of Munich, Germany.
- Liu, Jingzhen & Kemp, Alexander, 2019. "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, vol. 81(C), pages 672-686.
- Anatolyev, Stanislav & Baruník, Jozef, 2019.
"Forecasting dynamic return distributions based on ordered binary choice,"
International Journal of Forecasting, Elsevier, vol. 35(3), pages 823-835.
- Stanislav Anatolyev & Jozef Barunik, 2017. "Forecasting dynamic return distributions based on ordered binary choice," Papers 1711.05681, arXiv.org, revised Jan 2019.
- Ignacio Escanuela Romana & Clara Escanuela Nieves, 2023. "A spectral approach to stock market performance," Papers 2305.05762, arXiv.org.
- Turan Bali & Kamil Yilmaz, 2009. "The Intertemporal Relation between Expected Return and Risk on Currency," Koç University-TUSIAD Economic Research Forum Working Papers 0909, Koc University-TUSIAD Economic Research Forum, revised Nov 2009.
- Anatolyev, Stanislav, 2009.
"Nonparametric Retrospection and Monitoring of Predictability of Financial Returns,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 149-160.
- Stanislav Anatolyev, 2006. "Nonparametric retrospection and monitoring of predictability of financial returns," Working Papers w0071, Center for Economic and Financial Research (CEFIR).
- Stanislav Anatolyev, 2006. "Nonparametric retrospection and monitoring of predictability of financial returns," Working Papers w0071, New Economic School (NES).
- Stelios D. Bekiros, 2013.
"Irrational fads, short‐term memory emulation, and asset predictability,"
Review of Financial Economics, John Wiley & Sons, vol. 22(4), pages 213-219, November.
- Bekiros, Stelios D., 2013. "Irrational fads, short-term memory emulation, and asset predictability," Review of Financial Economics, Elsevier, vol. 22(4), pages 213-219.
- Thomakos, Dimitrios D. & Wang, Tao, 2010. "'Optimal' probabilistic and directional predictions of financial returns," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 102-119, January.
- Fokianos, Konstantinos & Truquet, Lionel, 2019. "On categorical time series models with covariates," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3446-3462.
- Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2023. "Estimation of Semiparametric Multi-Index Models Using Deep Neural Networks," Monash Econometrics and Business Statistics Working Papers 21/23, Monash University, Department of Econometrics and Business Statistics.
- Bury, Thomas, 2014. "Predicting trend reversals using market instantaneous state," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 79-91.
- S. D. Bekiros & D. A. Georgoutsos, 2008.
"Direction-of-change forecasting using a volatility-based recurrent neural network,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 407-417.
- Bekiros, S. & Georgoutsos, D., 2006. "Direction-of-Change Forecasting using a Volatility- Based Recurrent Neural Network," CeNDEF Working Papers 06-16, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- Adabi Firouzjaee , Bagher & Mehrara , Mohsen & Mohammadi , Shapour, 2014. "Optimal Portfolio Selection for Tehran Stock Exchange Using Conditional, Partitioned and Worst-case Value at Risk Measures," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 9(1), pages 1-30, October.
- Harris, Richard D.F. & Yilmaz, Fatih, 2009. "A momentum trading strategy based on the low frequency component of the exchange rate," Journal of Banking & Finance, Elsevier, vol. 33(9), pages 1575-1585, September.
- Riccardo Colacito & Eric Ghysels & Jinghan Meng & Wasin Siwasarit, 2016. "Skewness in Expected Macro Fundamentals and the Predictability of Equity Returns: Evidence and Theory," The Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 2069-2109.
- Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
- Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
- Huei-Wen Teng & Yu-Hsien Li, 2023. "Can deep neural networks outperform Fama-MacBeth regression and other supervised learning approaches in stock returns prediction with asset-pricing factors?," Digital Finance, Springer, vol. 5(1), pages 149-182, March.
- Frazier, David T. & Liu, Xiaochun, 2016. "A new approach to risk-return trade-off dynamics via decomposition," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 43-55.
- Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
- Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022.
"Geopolitical risks and historical exchange rate volatility of the BRICS,"
International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
- Afees A. Salisu & Juncal Cunado & Rangan Gupta, 2020. "Geopolitical Risks and Historical Exchange Rate Volatility of the BRICS," Working Papers 2020105, University of Pretoria, Department of Economics.
- De Nard, Gianluca & Engle, Robert F. & Ledoit, Olivier & Wolf, Michael, 2022.
"Large dynamic covariance matrices: Enhancements based on intraday data,"
Journal of Banking & Finance, Elsevier, vol. 138(C).
- Gianluca De Nard & Robert F. Engle & Olivier Ledoit & Michael Wolf, 2020. "Large dynamic covariance matrices: enhancements based on intraday data," ECON - Working Papers 356, Department of Economics - University of Zurich, revised Jan 2022.
- Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
- Moysiadis, Theodoros & Fokianos, Konstantinos, 2014. "On binary and categorical time series models with feedback," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 209-228.
- Huck, Nicolas, 2019. "Large data sets and machine learning: Applications to statistical arbitrage," European Journal of Operational Research, Elsevier, vol. 278(1), pages 330-342.
- Böyükaslan, Adem & Ecer, Fatih, 2021. "Determination of drivers for investing in cryptocurrencies through a fuzzy full consistency method-Bonferroni (FUCOM-F’B) framework," Technology in Society, Elsevier, vol. 67(C).
- 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.
- Rasika Yatigammana & Shelton Peiris & Richard Gerlach & David Edmund Allen, 2018. "Modelling and Forecasting Stock Price Movements with Serially Dependent Determinants," Risks, MDPI, vol. 6(2), pages 1-22, May.
- Stanislav Anatolyev, 2006. "Testing for predictability (in Russian)," Quantile, Quantile, issue 1, pages 39-42, September.
- Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017.
"Measuring uncertainty in the stock market,"
International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
- Helena Chuliá & Montserrat Guillén & Jorge M. Uribe, 2015. "“Measuaring Uncertainty in the Stock Market”," IREA Working Papers 201524, University of Barcelona, Research Institute of Applied Economics, revised Nov 2015.
- Barnhart, Scott W. & Giannetti, Antoine, 2009. "Negative earnings, positive earnings and stock return predictability: An empirical examination of market timing," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 70-86, January.
- Gu, Wentao & Peng, Yiqing, 2019. "Forecasting the market return direction based on a time-varying probability density model," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
- Dueker, Michael & Neely, Christopher J., 2007.
"Can Markov switching models predict excess foreign exchange returns?,"
Journal of Banking & Finance, Elsevier, vol. 31(2), pages 279-296, February.
- Michael J. Dueker & Christopher J. Neely, 2006. "Can Markov switching models predict excess foreign exchange returns?," Working Papers 2001-021, Federal Reserve Bank of St. Louis.
- Tianyi Wang & Sicong Cheng & Fangsheng Yin & Mei Yu, 2022. "Overnight volatility, realized volatility, and option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1264-1283, July.
- Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
- Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
- Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
- Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
- Bakshi, Gurdip & Panayotov, George, 2013. "Predictability of currency carry trades and asset pricing implications," Journal of Financial Economics, Elsevier, vol. 110(1), pages 139-163.
- Liang, Chao & Wang, Lu & Duong, Duy, 2024. "More attention and better volatility forecast accuracy: How does war attention affect stock volatility predictability?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 1-19.
- Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, August.
- Arnold Polanski & Evarist Stoja, 2010. "Incorporating higher moments into value-at-risk forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(6), pages 523-535.
- Liu, Jiadong & Papailias, Fotis & Quinn, Barry, 2021. "Direction-of-change forecasting in commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
- Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.
- Basak, Suryoday & Kar, Saibal & Saha, Snehanshu & Khaidem, Luckyson & Dey, Sudeepa Roy, 2019. "Predicting the direction of stock market prices using tree-based classifiers," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 552-567.
- Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.
- 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.
- Thomas Bury, 2013. "Predicting trend reversals using market instantaneous state," Papers 1310.8169, arXiv.org, revised Mar 2014.
- Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
- Pawel Dlotko & Wanling Qiu & Simon Rudkin, 2022. "Topological Data Analysis Ball Mapper for Finance," Papers 2206.03622, arXiv.org.
- Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009.
"Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches,"
Working Papers
w0136, New Economic School (NES).
- Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
- Ginker, Tim & Lieberman, Offer, 2017. "Robustness of binary choice models to conditional heteroscedasticity," Economics Letters, Elsevier, vol. 150(C), pages 130-134.
- Bekiros, Stelios D., 2010. "Heterogeneous trading strategies with adaptive fuzzy Actor-Critic reinforcement learning: A behavioral approach," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1153-1170, June.
- Chronopoulos, Dimitris K. & Papadimitriou, Fotios I. & Vlastakis, Nikolaos, 2018. "Information demand and stock return predictability," Journal of International Money and Finance, Elsevier, vol. 80(C), pages 59-74.
- Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
- Gilbert W. Bassett Jr Bassett & Roger Koenker & Gregory Kordas, 2004. "Pessimistic portfolio allocation and Choquet expected utility," CeMMAP working papers 09/04, Institute for Fiscal Studies.
- Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
- Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
- Luis H. R. Alvarez E. & Paavo Salminen, 2017.
"Timing in the presence of directional predictability: optimal stopping of skew Brownian motion,"
Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 86(2), pages 377-400, October.
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