股票市场波动丛聚性及杠杆效应的实证研究

Empirical Study on Volatility Clustering and Leverage Effect in Stock Market

本文选取1997年1月1日至2018年9月21日上证综指和标准普尔500指数日收益率序列,通过建立ARCH(1,1)模型对中美股票市场波动丛聚性进行实证分析,结果显示GARCH(1,1)模型能很好地刻画中美股票市场的波动丛聚性特征。建立非对称GARCH模型来刻画中美股票市场的杠杆效应,实证结果表明,中美股票市场都存在杠杆效应,即利空消息比利好消息对股市的冲击更大,并且美股市场杠杆效应明显强于中国股票市场。本文对中美股票市场波动丛聚性及杠杆效应进行比较分析,提出了完善交易制度、加强应对系统性金融危机的能力及减少政府干预等政策建议。

GARCH(1,1) model, of which result worked well, was established to describe volatility clustering of the Shanghai Composite and S&P 500 indices, using the dataset from January 1, 1997 to September 21, 2018. Furthermore, the asymmetric GARCH Models were used to characterize the leverage effect in both China and the U.S. stock market. The empirical results show that there is leverage effect in both market, that is, bad news has a greater impact on the stock market than good news, and the leverage effect of U.S. stock market is significantly stronger than that in China. Finally, the paper made a comparative analysis of volatility clustering and leverage effect between China and U.S. stock market, and put forward some suggestions, such as perfecting the transaction institutions,strengthening the ability to deal with financial crisis and reducing intervention of the government.