中国股票市场的时变杠杆效应研究——基于随机Copula模型的实证分析

构建随机Copula模型研究了中国股票市场在极端市场条件下的时变杠杆效应.为了解决金融市场中波动率不可直接观测的问题,采用已实现波动率测度作为隐波动率的代理变量,进而运用基于有效重要性抽样的极大似然(EIS-ML)方法估计了随机Copula模型的参数.基于沪深股市数据的实证研究表明:中国股票市场的杠杆效应具有非对称特征,即股市低收益率伴随高波动率,但股市高收益率不一定伴随低波动率;中国股票市场的杠杆效应存在显著的时变性,沪深股市杠杆效应表现出类似的变化趋势;随机Copula模型相比其它Copula模型(静态Copula模型和时变Copula模型)具有更好的数据拟合效果.

Time-varying leverage effects in Chinese stock markets: Empirical analysis based on stochastic Copula models

This paper constructs stochastic Copula models to study the time-varying leverage effects in Chinese stock markets at the extremes.It is well-known that volatility can not be directly observed in the financial markets.To overcome this problem,realized volatility is used to measure the latent volatility.Then the efficient importance sampling-based maximum likelihood (EIS-ML) estimation is adopted to estimate the parameters of the stochastic Copula models.The empirical results from data of Shanghai and Shenzhen stock markets demonstrate that the leverage effects in Chinese stock markets exhibit asymmetric features.Specifically,extremely low stock market returns tend to be associated with extremely large volatilities,but extremely high stock market returns are not related to small volatilities.Moreover,the leverage effects in Chinese stock markets are found to be changing over time and exhibit similar variation trends in Shanghai and Shenzhen stock markets.The stochastic Copula models are shown to outperform other Copula models,including the static Copula models and time-varying Copula models.