Idiosyncratic Volatility, Investor Sentiment And Expected Return

Classical financial theory assumes that markets are efficient, investors are rational, and information is complete. It thinks the risk of assets can be divided into systemic risk and non-systematic risk. The systemic risk is composed of the entire market risk factors, which can not be eliminated. But the non-systemic risk is caused by some certain factors of the company or industry, which does not have a comprehensive effect on the overall market, and can be completely dispersed by constructing a diversified portfolio. In other words, since the idiosyncratic risk can be eliminated, then we need not consider this factor when doing asset pricing. However, a growing number of studies have found that due to high transaction costs, limited funds, the investor’s own shortage of analytical ability and other reasons, investors can not construct an effective portfolio to eliminate idiosyncratic risk. And many studies have shown that the relation between idiosyncratic volatility and expected return turn to be negative which is called "Idiosyncratic Volatility Mystery." To explain this phenomenon, many scholars studied on heterogeneous beliefs and short-sale constraints, but did not arrive at an accepted answer. In addition to "Idiosyncratic Volatility Mystery," there are some other anomalies that classical financial theory can not explain, such as the "January Effect", "Scale Effect", "Announcement Effect", "Herd Behavior" and so on. To explain these anomalies, scholars began to study investor psychology and behavior, and explore its impact on asset prices. Thus was born the Behavioral Finance. In the field of behavioral finance, investor sentiment is the main research content. Because investors are not fully rational, and their expectations for the future are biased perception, this bias makes investors sometimes overly optimistic, sometimes overly pessimistic, thus making the stock prices deviate from the true value. Therefore, this paper will verify whether investor sentiment can explain "Idiosyncratic Volatility Mystery".The purpose of this study is to research the correlation between idiosyncratic volatility and expected return, and whether this relation can be explained by investor sentiment. To do this research, we need to answer three questions:First, how to measure the stock idiosyncratic volatility and expected return? In this paper, idiosyncratic volatility is measured by standard deviation of the residuals from the Fama-French three-factor model, and expected return is measured by the original rate of return held a month later. In addition, this paper also uses Fama-French three-factor model to adjust expected return, and regards regression constant term as a proxy indicator of excess returns. Secondly, how to test the relation between idiosyncratic volatility and expected return? This paper uses portfolio analysis and Fama-Macbeth two-step regression analysis. Specifically, sorting stocks according to their idiosyncratic volatility before divide them into five groups. Portfolio 1 contains stocks in the lowest volatility, and Portfolio 5 contains stocks in the highest volatility. And then observe whether expected return of Portfolio 1 and Portfolio 5 have significant difference. Meanwhile, this paper also uses Fama-Macbeth two-step regression to determine the quantitative relationship between idiosyncratic volatility and expected return. Thirdly, how to measure investor sentiment and verify whether this relation can be explained by investor sentiment? This paper selects closed-end fund discount rate, the average monthly turnover of Shanghai and Shenzhen 300 Index, number of new investors, consumer confidence index as basic indexes, and uses principal component analysis to construct a composite sentiment index. Then take investor sentiment as the second grouping indicators, and also use portfolio analysis and Fama-Macbeth two-step regression analysis to do the research. In addition, taking into account the policy and listed company style are a little different between Shanghai Stock Exchange and Shenzhen Stock Exchange, this paper will discuss the two stock markets separately.In this paper, we take China’s main-board market as research sample and sample period ranges from January 1,2006 to June 30,2015. Through empirical research, we find that stock idiosyncratic volatility and expected return was negatively correlated, namely we prove the existence of "idiosyncratic volatility mystery" in China’s main-board market. Thus, traditional financial theories can no longer explain some financial anomalies in real life. Therefore, inventors should not rely on CAPM completely when making investment decisions. Furthermore, from this paper’s conclusion, we can see that high risk do not always bring high yield.The innovation of this paper is:Most of the previous studies were based on heterogeneous beliefs and short-sale constraints to explain "idiosyncratic volatility mystery", but this paper choose a new perspective that is investor sentiment difference to do the research.The shortcomings of this paper are:First, this paper does not use other methods to measure idiosyncratic volatility, so we can not know whether the result will be different when we choose another measurement method. Secondly, the investor sentiment index we conduct reflects overall market sentiment, so this index is a time series. When we use investor sentiment index as a grouping indicator, we just divide full sample into three shorter subsamples and this approach is not so good.