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Asian Review of Financial Research Vol.33 No.1 pp.61-95 https://www.doi.org/10.37197/ARFR.2020.33.1.3
Impact of Investor Sentiment on the Cross-section of Stock Returns
Hyo-jeong Lee Associate Professor, College of Business, Kwangwoon University
Key Words : Behavioral Finance,Investor sentiment,Sentiment beta,Sensitivity,Cross- sectional Analysis

Abstract

Using an investor sentiment index and an index of sentiment changes for the Korean stock market, this study examines how investor sentiment affects a cross-section of stock returns. I examine whether more speculative and harder-to-arbitrage stocks are more sensitive to sentiment, that is, whether their returns co-move more with sentiment changes. I also test whether the returns on extremely unspeculative stocks are negatively related to changes in sentiment, that is, whether they have negative sentiment betas. According to studies on behavioral finance (Shleifer and Summers, 1990; Lee, Shleifer, and Thaler, 1991), because a mispricing is the result of an irrational demand shock in the presence of a binding arbitrage constraint, shifts in investor sentiment have cross-sectional effects when sentiment-based demands or arbitrage limits vary across stocks. Consistent with these predictions, prior empirical studies (Baker and Wurgler, 2006, 2007; Kumar and Lee, 2006) report that more speculative and harder-to-arbitrage stocks—smaller, newer, more volatile, unprofitable, non-dividend paying, distressed or those with extreme growth potential—are more likely to be affected by shifts in investor sentiment. However, the effect of sentiment on the aggregate market is somewhat less clear. Brown and Cliff (2004) show that sentiment has little predictive power for near-term future stock returns, and Schmeling (2009) insist that the effect of sentiment on aggregate stock returns is observed only in the countries that are culturally more prone to herd-like behavior. To reconcile the cross-sectional results and the aggregate results, Baker and Wurgler (2007) suggest one possible explanation known as “the sentiment seesaw,” in that if sentiment fluctuations induce demand shifts between speculative stocks and safe stocks, that is, “the flights to quality within the stock market” occur, the low (high) sentiment reduces (increases) the prices of speculative stocks and at the same time increases (decreases) the prices of safe stocks, resulting in no effect of sentiment on aggregate market returns. In line with this idea, this study analyzes the effect of broad-waved sentiment on a cross-section of stock returns in terms of sensitivity to sentiment. Using financial parlance, I investigate whether more speculative and harder-to- arbitrage stocks have higher sentiment betas, and whether extremely unspeculative and easier-to-arbitrage stocks have negative sentiment betas. As in practice, the same securities that are most sensitive to speculative demands also tend to be the costliest to arbitrage, I hypothesize that stocks most sensitive to investor sentiment are those of companies that are smaller, more volatile, have less tangible assets, are unprofitable, are distressed, and have the potential for extreme growth. At first, I construct the monthly sentiment index and the monthly index of sentiment changes for the Korean stock market based on principal component analysis using five key sentiment proxies: the volatility premium, KSE share turnover, IPO volume, IPO first-day returns, and the proportion of companies with seasonal equity offering. To increase the reliability of the indices and their comparability with international research, I develop these sentiment indices in line with those of Baker and Wurgler (2006, 2007). Using these indices and the monthly returns of all of the common stocks of the KOSPI market from 2000 to 2017, I analyze the effect of the changes in investor sentiment on a cross-section of stock returns. I start by forming equalweighted decile portfolios based on several firm characteristics such as firm size, MTB, idiosyncratic volatility, total volatility, asset tangibility, profitability, sales growth, and Rand D ratio, and look for patterns in changes in average returns across deciles when the investor sentiment index changes from +1σ to -1σ. I also consider a regression approach that allows controlling for the Fama-French (1993) factors and the Carhart (1997) momentum factor. I regress the returns of each decile portfolio and the returns of various high-minus-low portfolios on the index of sentiment changes, respectively. Consistent with my prediction, I find that the stocks with high MTB ratio, high volatility, low PPE ratio, low profitability, and low sales growth, respond more sensitively to changes in investor sentiment than the stocks with low MTB ratio, low volatility, high PPE ratio, high profitability, and high sales growth. In other words, the more speculative and harder-to-arbitrage stocks have higher sentiment betas. The returns of stocks with extremely low MTB ratios and low volatilities are negatively related to changes in sentiment. That is, most bond-like stocks appear to have slightly negative sentiment betas. These findings are consistent with those of prior studies. As the Korean stock market is an individual-crowded and highly integrated market, it is a good test bed for studying issues related to investor sentiment. Using Korean stock market data, my findings shed light on the effect of investor sentiment on a cross-section of stock returns in theory and can help practitioners establish a profitable investment strategy using investor sentiment.
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