Model of Bias-Driven Trend Followers and Interaction with Manipulators

Ke Liu (), Kin Keung Lai (), Jerome Yen () and Qing Zhu ()
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Ke Liu: School of Business Adminstration, North China Electric Power University, Daxing, Beijing, China
Kin Keung Lai: School of Business Adminstration, North China Electric Power University, Daxing, Beijing, China
Jerome Yen: Department of Finance and Economics, Tung Wah College, Kowloon, Hong Kong
Qing Zhu: International Business School of Shaanxi, Normal University, Xi’an City, Shanxi, China

International Journal of Information Technology & Decision Making (IJITDM), 2017, vol. 16, issue 02, 573-590

Abstract: Stock investors are not fully rational in trading and many behavioral biases that affect them. However, most of the literature on behavioral finance has put efforts only to explain empirical phenomena observed in financial markets; little attention has been paid to how individual investors’ trading performance is affected by behavioral biases. As against the common perception that behavioral biases are always detrimental to investment performance, we conjecture that these biases can sometimes yield better trading outcomes. Focusing on representativeness bias, conservatism and disposition effect, we construct a mathematical model in which the representative trend investor follows a Bayesian trading strategy based on an underlying Markov chain, switching beliefs between trending and mean-reversion. By this model, scenario analysis is undertaken to track investor behavior and performance under different patterns of market movements. Simulation results show the effect of biases on investor performance can sometimes be positive. Further, we investigate how manipulators could take advantage of investor biases to profit. The model’s potential for manipulation detection is demonstrated by real data of well-known manipulation cases.

Keywords: Bayesian trading strategy; trading behavior; Markov chain; trend following (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1142/S0219622014500485

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