An Empirical Study On Noise Trading In Chinese Stock Market

Due to asymmetric information, irrational noise traders account for a large proportion of Chinese stock market investors. Chinese investors are more likely to follow the herd. Traditional financial theories such as CAPM, EMH and MPT cannot explain some abnormal financial phenomena in China’s stock markets, which include investors’ herd behavior, investors’ over-reaction and hypo-reaction, momentum effect and long term reversal effect, etc. With consideration of the reality of China’s stock markets, based on the financial theories concerning noise trading, the paper makes an empirical study of China’s stock markets.First, the theory of noise trading is discussed in the thesis. The origin of the theory of noise trading, as well as the nature and content of the noise traders and noise trading risk and behavioral mechanisms are defined. The paper expounds DSSW model and how noise traders come out and benefit from the stock markets. BSV, DHS and HS theories are applied to account for investors’ over-reaction and hypo-reaction as well as the Momentum effect and long term reversal effect in China’s stock markets.On the basis of analysis of the Chinese stock market noise type of transaction, combined with the development trend of China’s stock market, the author studies the special performance of the Chinese stock market noise trading: significant volatility， high turnover and affected by policies.Then, the author studies the elements of noise trading in Chines stock markets, especially analyzes the noise elements before and after the reform of non-tradable shares, using NCT index based on VRT. In the mean time, this essay compares those stocks which are almost completely circulated with the whole market, leading to the conclusion that the reform of non-tradable shares and complete circulation of stocks efficiently restrain unreasonable factors and noise in the market.Also, the author analyzes the lever effect of noise trading in Chinese stock markets and points out that the noise trading is often affected by policies. Based on Shanghai and Shenzhen300Industry Index, the paper analyzes the volatility of each representative sector index in Shanghai and Shenzhen by using ARMA-GARCH model. The empirical results show that the GARCH (1,1) model can be used to explain the volatility of the industry exist in the continuity clustering. And it tests various trades with the leverage effects and volatility of the impact of asymmetric information through the TARCH (1,1) and EGARCH (1,1) model. The results show that the reverse impact will have higher volatility than the same amount of positive impact.Excessive noise trading is the main reason why China’s stock markets go ups and downs. The author makes an empirical study of positive feedback trading in China’s stock markets by selection of Shanghai Composite Index and Shenzhen Component Index, the small board index, CSI300Index, five samples of closed-end fund index, the asymmetric GARCH-M model.The results show that our existence of noise traders use positive feedback trading strategy to the two cities daily gain and noise trader behavior; blue chip companies listed on the control of noise and containment of positive feedback trading has a positive effect; small plates of positive feedback trading is the most obvious, followed by closed-end funds, then the Shenzhen Component Index on the Shanghai Composite Index, and finally the CSI300Index; that should develop more suitable for long-term investment in index funds to stabilize the market and innovative closed-end funds issue.Based on BAPM model, the author studies exceeding noise trading by using listed companies which were given administrative penalties as samples. Selection of2007-2009years by the China Securities Regulatory Commission administrative penalties listed companies from January2007to December2009, the rate of return analysis of samples, whichever corresponds to the same industry, matching empirical studies have concluded that, The noise trader risk（NTR） with the stock excess return is the greater the likelihood of a significant negative correlation was significantly higher the investors investing in such stocks suffered losses.The original ideas of the paper are as follows.First, NCT norms are established on the basis of VRT. The paper analyzes the distinctiveness of the noise trading in China’s stock markets and makes an empirical study.The author makes an empirical study of the lever effect caused by noise trading in Chinese stock markets on the basis of ARMA-GARCH.Secondly, the thesis makes an empirical study of five representative share indexes on the basis of volatility by positive feedback trading theories and asymmetric GARCH-M Model.Finally, the author based on BAPM model studies exceeding noise trading by using listed companies which were given administrative penalties as samples.