Asian Review of Financial Research Vol.31 No.1 pp.1-38
Investor Sentiment and Firm Characteristics: Domestic Evidence
Key Words : Behavioral Finance,Firm Characteristic,Four-Factor Risk Factor,Investment Sentiment Index,Momentum Effect,Stock Return
This study suggests an investment sentiment index that exploits daily information on individual firm characteristics and individual investors' trading behavior in the Korean stock market. We empirically examine the explanatory power of our sentiment indicator for the cross-sectional returns of individual stocks and portfolios after controlling for appropriate market risk factors. While previous studies use a single variable or multiple market-wide variables to measure investor sentiment, we efficiently measure sentiment by extracting common factors from various individual firm characteristic variables and trades by domestic individual investors, who are normally regarded as noisy and behaviorally biased. By extending methodologies suggested by Ryu, Kim, and Yang (2017), Yang, Ryu, and Ryu (2017), and Yang and Zhou (2015, 2016), we construct a composite sentiment indicator based on principal component analysis using five key variables: the relative strength index, psychological line index, adjusted turnover rate, logarithm of trading volume, and individual investor buy-sell imbalance. We analyze how the sentiment effect varies depending on firm and stock characteristics by constructing several portfolio groups classified according to firm size, stock price, book-to-market ratio, excess return, volatility of past returns, individual trading ratio, and foreign investors' holding for individual companies. We categorize the portfolios into five quintile groups based on each criterion and generate an investor sentiment index for each portfolio group. Our sample data comprise a daily stock trading dataset for all available manufacturing companies listed on the KOSPI stock market from 2000 to 2015. This sample mitigates possible industry effects and biases and enables us to investigate the uncontaminated results for sentiment effects by maintaining homogeneity among the sample firms. To ensure consistency and clarity, we exclude companies facing trading suspension and/or administrative issues. We extend the literature on investor sentiment and contribute to research by constructing a composite sentiment indicator that includes information on various stock and firm characteristics. We use buy-sell order imbalance information on individual investors, as their investment strategies and trading patterns are likely to be affected by psychology, sentiment, and mood. Our sentiment indicator exhibits more robust explanatory power than existing sentiment measures do, as it successfully explains the cross-sectional asset returns after controlling for the four risk factors. Our empirical analyses using this sentiment indicator provide several important findings and implications. We find that our investor sentiment indicator may explain cross-sectional stock and portfolio returns, even after controlling for Fama and French factors (market factor, size factor, and book-to-market factor) and the additional momentum factor suggested by Carhart (1997). It is particularly interesting that the sentiment indicator maintains its explanatory powers after considering and controlling for the momentum effect, consisting of representative time-series stock price patterns driven by investor psychology and behavioral biases. This result indicates that the sentiment indicator may be an important factor in explaining asset price movements. The analyses considering firm and stock characteristics show that the sentiment effect varies significantly according to stock and firm characteristics, being more prominent for smaller firms as well as stocks that are lower priced, have higher book-to-market ratios, have greater excess returns, and are more volatile. The sentiment effect also increases for stocks exhibiting greater individual investor participations, while its effect is lower when stocks are mostly owned by foreign investors, who are mostly professional institutional investors. These results tend to suggest that domestic individual investors are uninformed and noisy traders, while foreign institutional investors are better informed and more sophisticated. Considering that our sentiment indicator captures firm and stock characteristics reflecting individual stock trading on a daily basis, our methodology can be easily applied to analyze sentiment issues in various industry sectors at a relatively high-frequency level. The sentiment indicator can also be used to examine the transmission and spillover effect of market sentiment and behavior across financial markets and countries.