Based On The Revised Capm Cross-sectional Study In China's Stock Market

Effective Market Hypothesis(EMH)suggests that an effective market should always reflect all available information sufficiently and correctly. However, many empirical researches found that the real financial markets are not always in that case. We call those phenomena inconsistent with EMH and Capital Asset Pricing Model (CAPM) abnormalities, which illustrate some imperfection on the model specification and limitation of estimation method with those traditional theories. Thus, the research on capital pricing model suitable to real financial markets must be an important subject for the academic and practice fields.In this paper, we focus on the central reasons for the abnormalities, including problems of model specifications and the shortcomings of the traditional regression method. Then we create a Turnover Rate-based Many-Factor Model and introduce the quantile regression into our research on stock cross-sectional returns. The main innovations are as follows:Firstly, we improve the Fama-French Three-Factor Model (Fama and French1993), and put the turnover rate variable into the model. After that we do empirical analysis for all the A shares from Shenzhen stock market of China, the results indicate the turnover rate variable is positively related with cross-sectional returns, and much more significant than other explanatory variables.Secondly, the quantile regression method, suggested by Koenker and Bassett (1978), is introduced into our research on cross-sectional returns, taking the place of traditional average regression method. It is more suitable to the real confuse financial markets. Quantile regression can be used to analyse how the cross-sectional returns be affected by risk factors, not only on average quantile, but also on any quantiles of conditional distribution. It makes the research more comprehensive and integrated.