A Random Utility Model for Shareholders Capturing the Disposition Effect

A Random Utility Model for Shareholders Capturing the Disposition Effect

Alfred Ka Chun Ma, Justina Yuen Ki Cheung
Copyright: © 2015 |Pages: 15
DOI: 10.4018/ijabe.2015040101
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This work proposes a random utility model for individual trading decision in the spirit of prospect theory. This model differs from those in the literature in that empirical data of stock price and volume can be incorporated. The paper tests the model with historical data from the NYSE TAQ database. This model provides one more alternative to link prospect theory and the disposition effect. Simulation results show that this model consistently predicts the disposition effect under all circumstances.
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1. Introduction

The disposition effect is one of the most important phenomena observed in the behavioral finance literature. The study of the disposition effect is initiated by Shefrin and Statman (1985) who propose a framework to explain the phenomenon that investors sell winners too early and ride losers too long. Odean (1998) documents the disposition effect in a data set of individual investors from a nationwide brokerage house. He computes the two ratios namely, the proportion of gains realized (PGR) and the proportion of losses realized (PLR) for the data set and finds that the PGR is significantly greater than the PLR. He then concludes that the investors demonstrate a strong preference for realizing winners rather than losers. Grinblatt and Keloharju (2001) document the same phenomenon in a data set of individual investors in Finland. By employing Logit regressions, they find evidence that the investors are reluctant to realize losses. Coval and Shumway (2005) investigate Chicago Board of Trade proprietary traders and find that those trades regularly take more risk than usual in the afternoon in order to recover morning losses. They reinforce that the disposition effect is the strongest behavioral bias they could identify. Ferris et al. (1988) use a proxy for the reference price to show that the abnormal volume can be explained by the level of purchase prices and thus partially support the disposition effect. Kaustia (2004) studies the behavior of investors during the IPO periods. He finds that the turnover is significantly lower when the stock trades below the IPO offer prices while the turnover is significantly higher when the stock trades above the IPO offer prices. His findings supports a market-wide disposition effect during periods of high IPO activities in that investors are reluctant to realize losses during the IPO periods.

While the disposition effect is important per se, it is well connected to other phenomena in finance. Dhar and Zhu (2006) analyze the trading records of more than 50,000 individual investors and study the disposition effect. In addition to the findings that the winners sell stocks sooner than the losers do, they also find that trading frequency is responsible in part for the variation in individual disposition effect. They then conclude that trading frequency tends to reduce the disposition effect. Grinblatt and Han (2005) and later Hur et al. (2010) link the disposition effect to momentum. This momentum is created by the spread between a stock’s fundamental value and its equilibrium price together with price under-reacted to information. The convergence of this spread generates predictability of equilibrium prices. After controlling for a variable acting as proxy for the aggregate unrealized capital gains, past returns have no predictability for the cross-section of returns. In this sense, Frazzini (2006) shows that the disposition effect induces under-reaction to news. By constructing a new measure of reference purchasing prices for individual stocks, he shows that post-announcement price drift is the most severe whenever capital gains and the news event have the same sign. This provides a source of predictability of stock returns and potentially generates monthly alphas of over 200 basis points.

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