Can Liquidity Risk Improve The Explanatory Power Of The CAPM Model?

When it comes to liquidity in the financial field,we know that it plays an important role in the process of financial resource allocation,so it is recognized as an important factor affecting the excess stock return.Therefore,the study refers to liquidity and its risk in stock pricing has become an important research direction.Existing asset pricing,however,the article research the liquidity factor,whether as a factor to join his three factors or five factor model,examine whether the improved model based on the original pricing power,still based on Acharya and Pedersen LCAPM model proposed by(2004),the relationship between liquidity risk and stock returns,are merely involves the systemic level factors,research the liquidity of the literature on the idiosyncratic factors that are relatively few.Therefore,this paper not only discusses the applicability of LCAPM model in China’s stock market,but also introduces idiosyncratic factors to study the relationship between liquidity risk and stock return rate from multiple perspectives.In order to better applicability problem research model,this paper use the Amihud illiquidity ratio for the period from 2006 to 2019,the Shanghai a-share market liquidity has carried on the whole,found that Chinese stock market liquidity level significantly increased after 2009,in addition the liquidity ratios can vivid reflect this period of the 2008 financial crisis,the stock market crash of 2015 big events,such as performance as an index of sudden surge in the figure,so after that using Amihud illiquidity ratio as a measure of liquidity has good applicability.Then,we verify that the time series of monthly Amihud illiquidity ratio of Shanghai A-shares has a significant second-order autocorrelation,which has a good guiding role for the national management to control the liquidity.Finally,through the introduction of dummy variables,the paper studies whether there is a monthly effect on China’s liquidity.Through model regression,it is found that the liquidity of China’s stock market in March is significantly higher than that in other months,which means that for many investors in the market,they can get better returns if they operate in March.After having a good understanding of market liquidity,this paper begins to study the impact of liquidity risk on stock return rate.In order to reduce the noise impact of a single stock on the empirical data,this paper adopts the form of building a portfolio based on illiquidity index,and divides Shanghai A-shares into 25 groups.Then,based on LCAPM model,the paper studies the effect of liquidity systemic risk on stock pricing.The results show that the pricing effect of systemic risk factor β in Shanghai A-share market is very significant when considering the restrictive conditions in the model,but the market risk factor β1 loses its significance when the restrictive conditions are removed.But overall,the applicability of the model has improved.After studying the system factors,this paper will introduce the idiosyncratic factors into the model to comprehensively study the effect of the system and non-system liquidity risk on the pricing of Shanghai A-share stocks.The results show that the goodness of fit of the model is significantly improved after the introduction of idiosyncratic factors.Except for the trait fluctuation IVOL factor,all the models show high significance.In order to test the robustness of the empirical results,this paper uses a portfolio with value-weighted different from the previous equal-weighted portfolio,and the systematic and idiosyncratic risks of liquidity still have a significant impact on the stock return rate.Finally,the concept of investor holding period is introduced.In reality,the investor’s holding time of the portfolio is not consistent with the monthly return range measured by our measure.Therefore,when the model term K is multiple of the investor’s holding time,the excess return on stocks excluding liquidity cost will be expressed as E(ri,t-kci,t-rf,t).After changing the null assumption of the model,k=1,the empirical results show that the fitting degree of the model is better than before,the significance of the factor is further improved,and the IVOL shows a certain significance.Full text,through empirical research demonstrates that the stock’s own liquidity risk also affects the excess return,has a certain contribution.It can help the government management departments,institutions or individual investors to fully understand how the different types of liquidity risk in the Chinese market affect stock returns,so as to guide them to make the right regulatory policy and investment decisions.