中国股市异象的时变特征及影响因素研究

中国股市存在诸多市场异象，而其时变性却常被忽视。本文从动态视角出发，基于条件CAPM，研究了中国股市异象的时变特征及影响其变化的经济因素。研究结果表明，即使在条件CAPM下，各类市场异象仍然存在，并且表现出显著的时变性。在样本期内，中国股票市场异象发生了风格转换，以账面市值比异象、市盈率异象为代表的价值型异象正在逐渐减弱甚至消失，而规模、特质波动率、换手率以及市场风险异象正逐渐显现并仍有增强的趋势。同时，规模、账面市值比、市盈率等"基本面类"异象主要受宏观经济因素的影响，反映了更多经济风险的信息；而特质波动率、换手率以及市场风险等"市场类"异象主要受市场因素的影响，此类异象更可能是市场无效的表现。此外，研究还发现，条件β未能捕捉到各多空组合收益率蕴含的经济风险，这是条件CAPM无法解释各市场异象的原因之一。

Study on Characteristics and Influence Factors of Time-varying Anomalies in China's Stock Market

Recent years, the issue of asset pricing and quantitative investment has received great attention in China's stock market.Similar to the result of the developed countries, many empirical researches indicate that anomalies which refers that CAPM always have little power to explain the cross section of average returns on assets sorted by many kinds of stocks' characters are found in China's stock market.Furthermore, some studies find that the anomalies may be time varying, which implies that the anomaliesare prominent only in some special periods, while in the other periods the anomalies are often weakened or vanished. In fact, the time variation of the anomalies should be a very significant issue in both academy and practicesectors, because the ignoring of the time variation would have a negative impact on both pricing efficiency of the factor pricing model and the market timing ability of the invest strategy based on the anomalies.Motivated by the above discussion, using the China's A shares' data from January 1995 to April 2017, the time varying characteristics of several kinds of anomalies based on the conditional CAPM are investigated in this paper, which could capture the dynamic information of the risk-adjusted return and market risk. To avoid the bias of state variable selection, the nonparametric method proposed by Ang and Kristensen is chosen to estimate the dynamic model. First, the long-term existence of the anomalies is tested based on the conditional CAPM. The result indicates that the anomalies are still existent, which implies that the conditional CAPM is not significantly helpful to explain the anomalies. Second, the anomalies' time variation is tested by the Hausman Test and graph thedynamictendency of the anomalies. In the result, it is found that the time variation of the anomalies is statistically significant, and from the long term, the China's stock market anomalies have experienced a type transformation, which result in that the significant level of B/M and P/E anomalies are gradually weakened and even disappeared, while the significant level of the other anomalies are gradually emerging and still have a tendency to strengthen. Third, with the regression analysis, the drivers of the anomalies are discussed, which can be separated into fundamental-type and market-type, including size, B/M, P/E effect and IVOL, turnover,market risk effect respectively. It is concluded that for the fundamental-type anomaliesthe main drivers are the macroeconomic factors, which means this type of anomalies reflect the information of macroeconomic risk, while for the market-type anomaliesthe main drivers are the market factors, which means this type of anomalies reflect the market's inefficiency. Finally, the drivers of the conditional β are also analyzed based on the conditional CAPM.Contrary to theory expectation, the result provides the evidence that the conditional β seems more likely to be associated with market factors rather than macroeconomic factors. This implies that the conditional β can't fully reflect the information about economic risk, which may be one of the reasons for the CAPM's failure to explain the anomalies.This study enriches the literatures on China's stock market anomalies from dynamic perspective. The conclusion tells us that time variation shouldn't be ignored when constructing pricing factors in factor pricing model based on anomalies. Moreover, it is useful to promote the market timing ability of the invest strategy based on the China's stock market anomalies.