中国股市非流动性对市场超额收益的预测研究——基于ARFIMA模型

The predictive power of aggregate illiquidity for stock returns-based on ARFIMA model

从非流动性的内涵出发,计算沪深300指数的七个非流动性指标,并通过主成分分析法对七个非流动性测度进行降维,获得市场综合非流动性指标。使用ARFIMA模型拟合各变量的长记忆性及残差相关性,构建蒙特卡洛模拟衡量因长记忆性及残差相关性对预测回归的影响程度,使用Bootstrap抽样法调整偏差及筛选具有稳健预测能力的非流动性测度。结果表明:非流动性测度能够对超额收益进行短、中及长期预测,prin和fht指标有较高的预测拟合优度,非流动性因子是因子定价理论的重要因子,且大多非流动性指标对市场超额收益的短期预测能力来源于市场波动,而中长期预测能力由与波动无关的非流动性因素主导。

From the concept of illiquidity,we calculate seven illiquidity proxies by using samples from Shanghai and shenzhen stock exchange(csi)300,and use principal component analysis(pca)to obtain the comprehensive illiquidity proxy(prin).We use ARFIMA model to fit the long memory and residual correlation of various variables,monte carlo simulation is constructed to measure the influence of long memory and residual correlation on prediction regression,and Bootstrap sampling method is used to adjust the deviation and screen the illiquidity measure with robust prediction ability.The results show that:the illiquidity measure can predict the short,medium and long term excess returns,R 2 measures of fht and prin are high,which reflects that the important role of illiquidity factor in liquidity risk pricing;The short-term forecasting ability of most illiquidity indexes to the market excess returns comes from the market volatility,while the medium-term and long-term forecasting ability is dominated by the illiquidity factors which have nothing to do with the volatility.