Herding Behavior Based On The Empirical Research Of Chinese Stock Market

Traditional finance theory is based on efficient market hypothesis, whileempirical research in these years found that there is seriously irrational behavior instock markets. Behavioral finance becomes a hot topic, and herding behavior is atypical case. Herding behavior in stock markets is the phenomenon that market tradersare influenced by others, ignore their own information, make similar decisions, whichis reflected in asset price. This paper investigates the herding behavior in Chinesestock market and draws some conclusion.Firstly, the concept of herding behavior would be described in this article, thenintroduce the theory model and empirical model of herding behavior. Secondly, thispaper adds to the growing literature on herding by examining herding at the intradaylevel using set of a new methodologies based on bootstrapped runs tests. In summingup, we find strong evidence of herding by investors in stocks experiencing extremeprice movements. The stocks on decline are associated with stronger herding. Weconjecture that sell-offs are aggravated by imitative behavior. Thirdly, we analyze therelationship between the herding behavior and the other factors of the stock market.Large capitalization stocks, which are more efficiently priced, fail to exhibit anysignificant level of herding. Herding is present in smaller stocks probably due tolesser and noisier information. The dispersion of opinion among investors about theinterpretation of pieces of information does not have much of an impact on herding.Analysts’ recommendations do not contribute to herding, and may in some instancesspeed up the incorporation of new information into stock prices. Fourthly, we analyzein this study cause of herding in a stock market. Information cascades have often beenconsidered as a primary choice. However, we propose alternative explanations in thisstudy, we suggest including an alternative theory based on search cost of investors.Search cost effect is stronger at market open, while information cascade effect isstronger at market close. Therefore our study suggests that herding should be related both to intrinsic search cost structure of investors as well as information relatedfactors. Moreover, this paper sets out to analyze the impact of herding on the volatilityof the Chinese stock market. Different volatility measures are employed. The resultsconfirm that herding has a direct linear impact on volatility for all of the volatilitymeasures. The conclusion and prospect of the study of herding behavior are placed atthe end of the article.