摘要
ince Amihud(2002),researchers have realized that liquidity may be able to capture the predictable variation of stock return.However,it is still unclear why liquidity has predictability.With daily trading data of Shanghai and Shenzhen Security Exchanges from Jan 2,1996 to Dec 31,2004,this paper utilizes a rolling analysis to construct an illiquidity measure similar to Amihud(2002).under the 5-by-5 portfolio space of Fama and French,departure from stochastic discount factor framework,we apply a first-stage GMM to empirically test the conditional CAPM with market liquidity serving as an instrument.The empirical results indicate that,market liquidity indeed can predict the stock return,and this predictability sources from its capability of capturing time-variation of stock return.Our study at least partially bridge an academic gap.
Since Amihud(2002), researchers have realized that liquidity may be able to capture the predictable variation of stock return. However, it is still unclear why liquidity has predictability. With daily trading data of Shanghai and Shenzhen Security Exchanges from Jan 2,1996 to Dec 31,2004,this paper utilizes a rolling analysis to construct an illiquidity measure similar to Amihud (2002). under the 5-by-5 portfolio space of Fama and French, departure from stochastic discount factor framework, we apply a first-stage GMM to empirically test the conditional CAPM with market liquidity serving as an instrument. The empirical results indicate that, market liquidity indeed can predict the stock return, and this predictability sources from its capability of capturing time-variation of stock return. Our study at least partially bridge an academic gap.
出处
《统计研究》
CSSCI
北大核心
2006年第8期66-71,共6页
Statistical Research