股市危机对中美股票市场溢出效应影响的实证研究

An Empirical Study of the Impact of Stock Market Crisis on the Spillover Effects between China and U.S. Stock Markets

2015年中国股市危机期间,监管层实施了一系列资本市场的监管措施,影响了我国股票市场的定价效率和美国股票市场对我国股票市场的溢出效应。基于结构向量自回归模型(SVAR)、动态Granger因果检验和分位数回归,本文对2015年的股市危机对中美股票市场信息溢出效应的影响进行分析,得出如下结论:美国股票市场在中美股票市场信息传递过程中处于主导地位,股灾后美国股票市场对中国市场的影响得到了显著的增强,尤其是在下跌行情中的影响更大。其中,美国与中国股票市场收益率同期和非同期溢出效应都是单向的,道琼斯指数的日内交易对上证综指的隔夜收益率有很大的影响,分位数回归显示美国股票市场对中国股票市场隔夜收益率的影响呈"V"型特征,美国市场的微小波动都会引起中国市场的巨大波动,尤其是股灾后在下跌行情中来自美国市场的负冲击对中国市场的影响变得更大。我国监管当局和投资者不能忽视美国股票市场与国内市场的联动关系,管理当局应采取措施优化市场投资者结构,壮大机构投资者队伍,推动资本市场对外开放,提高我国股票市场的定价效率。

During the 2015 stock market crisis, China＇s regulators have implemented a series of regulatory measures for the capital markets, which affect the pricing efficiency of China＇s stock markets, and the spillover effects of U. S. stock markets on China stock markets. Based on SVAR model, Dynamic Granger Causality Test and quantile regression, the paper analyzes the influence of the 2015 stock market crisis on information spillover effects between China and U. S. stock markets. Empirical conclusions are as follows： the U.S. stock markets dominates in the process of information transmission between China and U. S. stock markets, and the spillover effects of U. S. stock markets on China stock mar- kets tend to enhance significantly after the 2015 stock market crisis, especially in the down market. Among them, the contemporaneous and asynchronous spillovers effects are both of a one-way interaction, China stock market overnight re- turn influenced by U.S. stock markets daytime return is reflected as a V curve by using quantile regression model, and the impact of the negative impact from the stock markets in U.S. on that in China in a bear market has become greater after the 2015 stock market crisis. Our regulatory authorities and investors cannot ignore the linkage between the U. S. stock markets and the domestic markets. The policy makers should optimize the structure of the market investors, promote the openness of the capital market, and improve the pricing efficiency of China stock markets.