A Bayesian approach to excess volatility, short-term underreaction and long-term overreaction during financial crises

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.

[1]  Wing-Keung Wong,et al.  A pseudo-Bayesian model in financial decision making with implications to market volatility, under- and overreaction , 2010, Eur. J. Oper. Res..

[2]  K. Lim,et al.  Foreign investors and stock price efficiency: Thresholds, underlying channels and investor heterogeneity , 2016 .

[3]  L. Blume,et al.  Learning to be rational , 1982 .

[4]  Terrance Odean,et al.  Learning to Be Overconfident , 1997 .

[5]  Hitoshi Matsushima,et al.  Behavioral aspects of arbitrageurs in timing games of bubbles and crashes , 2013, J. Econ. Theory.

[6]  A. Tversky,et al.  The weighing of evidence and the determinants of confidence , 1992, Cognitive Psychology.

[7]  R. Horvath,et al.  GARCH Models, Tail Indexes and Error Distributions: An Empirical Investigation , 2016 .

[8]  Kam-Wah Tsui,et al.  An extended multinomial‐Dirichlet model for error bounds for dollar‐unit sampling* , 1990 .

[9]  E. Fama,et al.  Multifactor Explanations of Asset Pricing Anomalies , 1996 .

[10]  E. Fama EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[11]  J. Tull Investor Trading and the Post-Earnings-Announcement Drift , 2010 .

[12]  Moshe Levy,et al.  Microscopic Simulation of Financial Markets: From Investor Behavior to Market Phenomena , 2000 .

[13]  Jonathan D. Levin Bubbles and Crashes , 2006 .

[14]  Frank J. Fabozzi,et al.  Market overreaction and underreaction: tests of the directional and magnitude effects , 2013 .

[15]  Wing-Keung Wong,et al.  Prospect Performance Evaluation: Making a Case for a Non-Asymptotic UMPU Test , 2011 .

[16]  Wing-Keung Wong,et al.  Preferences over location-scale family , 2008 .

[17]  Wing-Keung Wong,et al.  Estimation of Cost of Capital and its Reliability , 2010 .

[18]  Hua Li,et al.  Test Statistics for Prospect and Markowitz Stochastic Dominances with Applications , 2007 .

[19]  Ephraim Clark,et al.  Investors’ Preference Towards Risk: Evidence from the Taiwan Stock and Stock Index Futures Markets , 2014 .

[20]  A. Tversky,et al.  BELIEF IN THE LAW OF SMALL NUMBERS , 1971, Pediatrics.

[21]  E. Fung,et al.  A pseudo-Bayesian model for stock returns in financial crises , 2011 .

[22]  H. Lean,et al.  Stochastic dominance and behavior towards risk: The market for Internet stocks , 2008 .

[23]  Howard E. Thompson,et al.  On the unavoidability of ‘unscientific’ judgment in estimating the cost of capital , 1991 .

[24]  J. Stein,et al.  A Unified Theory of Underreaction, Momentum Trading and Overreaction in Asset Markets , 1997 .

[25]  Kuldeep Kumar,et al.  Invisible walls: Do psychological barriers really exist in stock index levels? , 2016 .

[26]  J. B. Heaton,et al.  Competing Theories of Financial Anomalies , 2001 .

[27]  Wing-Keung Wong,et al.  Is gold different for risk-averse and risk-seeking investors? An empirical analysis of the Shanghai Gold Exchange , 2015 .

[28]  Kenneth A. Froot,et al.  Herd on the Street: Informational Inefficiencies in a Market with Short-Term Speculation , 1990 .

[29]  Yangru Wu,et al.  Random walk versus breaking trend in stock prices: Evidence from emerging markets , 2003 .

[30]  K. Lam,et al.  A New Pseudo-Bayesian Model with Implications to Financial Anomalies and Investors’ Behaviors , 2010 .

[31]  Wing-Keung Wong,et al.  On the estimation of cost of capital and its reliability , 2004 .

[32]  S. Solomon,et al.  A microscopic model of the stock market: Cycles, booms, and crashes , 1994 .

[33]  Michael McAleer,et al.  Mapping the Presidential Election Cycle in US stock markets , 2009, Math. Comput. Simul..

[34]  P. Slovic Psychological Study of Human Judgment: Implications for Investment Decision-Making , 1972 .

[35]  Wing-Keung Wong,et al.  Technical Analysis And Financial Asset Forecasting: From Simple Tools To Advanced Techniques , 2014 .

[36]  Wing-Keung Wong,et al.  A note on convex stochastic dominance , 1999 .

[37]  Ward Edwards,et al.  Judgment under uncertainty: Conservatism in human information processing , 1982 .

[38]  Markus K. Brunnermeier Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical Analysis, and Herding , 2001 .

[39]  Wing-Keung Wong,et al.  International momentum strategies: a stochastic dominance approach , 2005 .

[40]  Zvi Wiener,et al.  Stochastic Dominance and Prospect Dominance with Subjective Weighting Functions , 1998 .

[41]  Taisheng Liu,et al.  A New Pseudo-Bayesian Model with Implications for Financial Anomalies and Investors’ Behavior , 2012 .

[42]  Wing-Keung Wong,et al.  REVISITING “DIVIDEND YIELD PLUS GROWTH” AND ITS APPLICATION , 1996 .

[43]  Michael McAleer,et al.  Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China , 2012 .

[44]  Wing-Keung Wong,et al.  ENHANCEMENT OF THE APPLICABILITY OF MARKOWITZ'S PORTFOLIO OPTIMIZATION BY UTILIZING RANDOM MATRIX THEORY , 2009 .

[45]  Kent D. Daniel,et al.  Presentation Slides for 'Investor Psychology and Security Market Under and Overreactions' , 1998 .

[46]  Wing-Keung Wong,et al.  The performance of commodity trading advisors: A mean-variance-ratio test approach , 2013 .

[47]  Wing-Keung Wong,et al.  Stochastic dominance and mean-variance measures of profit and loss for business planning and investment , 2007, Eur. J. Oper. Res..

[48]  Songsak Sriboonchitta,et al.  Stochastic Dominance and Applications to Finance, Risk and Economics , 2017 .

[49]  Wing-Keung Wong,et al.  Gains from diversification on convex combinations: A majorization and stochastic dominance approach , 2010, Eur. J. Oper. Res..

[50]  A. Tversky,et al.  On the psychology of prediction , 1973 .

[51]  Benjamin M. Friedman,et al.  Optimal expectations and the extreme information assumptions of ‘rational expectations’ macromodels , 1979 .

[52]  Wing-Keung Wong,et al.  Stochastic Dominance and Risk Measure: A Decision-Theoretic Foundation for VAR and C-Var , 2006, Eur. J. Oper. Res..