A Bayesian approach to excess volatility,short-term underreaction and long-term overreaction during financial crises |
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| Institution: | 1. School of Statistics, Beijing Normal University, Beijing, China;2. Department of Quantitative Finance, National Tsing Hua University, Taiwan, China;3. Discipline of Business Analytics, University of Sydney Business School, Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, The Netherlands;4. Department of Quantitative Economics, Complutense University of Madrid, Spain, China;5. Department of Finance and Big Data Research Center, Asia University, Taiwan, China;6. Department of Economics and Finance, Hang Seng Management College, Hong Kong;7. Department of Economics, Lingnan University, Hong Kong;8. Department of Mathematics, Hong Kong Baptist University, Hong Kong;1. Faculty of Economics and Management of Mahdia, University of Monastir, Tunisia;2. Member of LAFICOIF, FSEG Tunis, University of Tunis EL Manar, Tunisia;1. Chair of Econometrics and Statistics, esp. in Transportation Science, Technische Universität Dresden, Würzburger Str. 35, 01187 Dresden, Germany;2. School of Business and Economics, Humboldt-Universität zu Berlin, Spandauer Strasse 1, 10178 Berlin, Germany;1. Department of Money and Banking, National Chengchi University, Taiwan, ROC;2. Department of Finance, National Dong Hwa University, Taiwan, ROC;3. Department of Economics and Finance, University of Dayton, OH, USA;1. School of Mathematics and Statistics, Xi’an Jiaotong University, China;2. School of Mathematics and Statistics, Suzhou University of Science and Technology, China;3. School of Statistics and Mathematics, Yunnan University of Finance and Economics, China;4. Department of Mathematics, Hong Kong Baptist University, Hong Kong;5. School of Statistics, Beijing Normal University, China;6. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, China |
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| Abstract: | In this paper, we introduce a new Bayesian approach to explain some market anomalies during financial crises and subsequent recovery. We assume that the earnings shock of an asset follows a random walk model with and without drift to incorporate the impact of financial crises. We further assume the earning shock follows an exponential family distribution to accommodate symmetric as well as asymmetric information. By using this model setting, we develop some properties on the expected earnings shock and its volatility, and establish properties of investor behavior on the stock price and its volatility during financial crises and the subsequent recovery. Thereafter, we develop properties to explain excess volatility, short-term underreaction, long-term overreaction, and their magnitude effects during financial crises and the subsequent recovery. We also explain why behavioral finance theory could be used to explain many of the asset pricing anomalies, but traditional asset pricing models cannot achieve this aim. |
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| Keywords: | Bayesian model Representative and conservative heuristics Excess volatility Underreaction and overreaction Magnitude effects Financial crises |
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