Quintiles Regression For The Premium Pricing Of Idiosyncratic Risk

According to the classical asset pricing model, investors can construct diversified portfolios to remove the system risk and the idiosyncratic risk is useless in asset pricing. However, Merton (1987) based on the information asymmetry theory put forward that investors always concentrate investment choices based on the information they have, so the idiosyncratic risk can not be diversified. The problem of the pricing of the idiosyncratic risk has become one of the hot spots in finance.But the diversity of the empirical results leads to the debate of this problem. These disputes could be caused by the choice of different inspection tools or by different asset pricing models. This paper will select different pricing models and different inspection tools to research the relationship between idiosyncratic risk and stock returns. Specifically, different asset pricing models can lead to diverse results. Fama-French three factor pricing model clarify a large number of financial vision that can not be explained by traditional asset pricing model and become the reference of the research of the idiosyncratic risk. However, different asset pricing models can lead to diverse results, so I calculate the idiosyncratic volatility by Fama-French three factor pricing model and Carhart four factor pricing model and compare the two results. What is more, the mean regression model can not comprehensive test the idiosyncratic risk premium. So I will try to use quantile regression method to research the relationship between idiosyncratic risk and stock returns.This article selects A-share market as the research object to check out whether the Puzzle of the idiosyncratic risk exists. Following are the main conclusions. Firstly, taking the momentum factor into consideration have little effect on the estimation of the idiosyncratic volatility. This suggests that momentum factor have little effect on idiosyncratic risk. Secondly, along with the fractile changes the regression coefficient of idiosyncratic volatility to cross-sectional returns change a lot, in the low site the relationship between idiosyncratic risk and stock returns are not significantly or significantly negative; in high site at the1%significant level the relationship between idiosyncratic risk and stock returns are significantly positive. In addition, the company size, Book-to-Market ratio, turnover rate, fluidity, reversal effects do not affect the positive relationship between idiosyncratic risk and stock returns. Fourthly, operation of the margin business has no effects on the pricing of the idiosyncratic risk and the positive relationship between idiosyncratic risk and cross-sectional returns.