GARCH模型、重尾与中国股市收益

Michael Day, Mark Diamond
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摘要

中国股市的独特之处在于,它更多地受到散户散户而非机构投资者的影响。因此,为了经济和政治的稳定,有效地管理中国股市的风险显得尤为重要。我们通过GARCH模型研究了其波动性动力学,该模型具有三种重尾分布,即Student 's t分布、NIG分布和NRIG分布。研究结果表明,三种分布的估计参数均具有统计显著性,NIG分布在拟合中国股市指数收益方面的实证表现最好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GARCH Model, Heavy Tails and the Chinese Stock Market Returns
The Chinese stock market is unique in which it is moved more by individual retail investors than institutional investors. Therefore, for economic and political stability it is more important to efficiently manage the risk of the Chinese stock market. We investigate its volatility dynamics through the GARCH model with three types of heavy-tailed distributions, the Student’s t, the NIG and the NRIG distributions. Our results show that estimated parameters for all the three types of distributions are statistical significant and the NIG distribution has the best empirical performance in fitting the Chinese stock market index returns.
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