This thesis addresses asset pricing in Chinese A-share stock markets using a dataset consisting of all shares listed in Shanghai and Shenzhen stock exchanges from January 1997 to December 2007. The empirical work is carried out based on two theoretical foundations: the efficient market hypothesis and behavioural finance. It examines and compares the validity of two traditional asset pricing models and two behavioural asset pricing models.
The investigation is initially performed within a traditional asset pricing framework. The three-factor Fama-French model is estimated and then augmented by additional macroeconomic and bond market variables. The results suggest that these traditional asset pricing models fail to explain fully the time-variation of stock returns in Chinese stock markets, leaving non-normally distributed and heteroskedastic residuals, calling for further explanatory variables and suggesting the existence of a structure break. Indeed, the macroeconomic and bond market factors provide little help to the asset pricing model.
Using the Fama-French model as the benchmark, further research is done by investigating investor sentiment as the third dimension beside returns and risks. Investor sentiment helps explain the mis-pricing component of returns in the Fama-French model and the time-variation in the factors themselves. Incorporating investor sentiment into the asset pricing model improves the model performance, lessening the importance of the Fama-French factors, and suggesting that in China, sentiment affects both the way in which investors judge risks as well as portfolio returns directly. The sentiment effect on asset pricing is also examined under a nonlinear Markov-switching framework. The stochastic regime-dependent model reveals that stock returns in China are driven by fundamental factors in bear and low volatility markets but are prone to sentiment and become uncoupled from fundamental risks in bull and high volatility markets.
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.