基于时变Copula的沪深300股指期现货高频价格相依结构测度

Measuring Dependence Structure between High-frequency Prices of CSI300 Index Futures and Spots Based on Time-varying Copulas

沪深300股指期货上市交易以来,中国股指期现货市场间相互冲击引发风险的概率正逐渐上升。科学测度沪深300股指期现货尤其是极端情况下价格间相依关系,对于准确跟踪和防范跨市场风险具有重要理论和现实价值。在日内高频价格环境下,本文采用已实现双幂波动拟合沪深300股指期现货价格的边缘分布,分别构造相依参数和相关系数时变的Clayton Copula函数、Gumbel Copula函数及其混合Copula函数测度沪深300股指期现货高频价格相依结构。实证结果表明,沪深300股指期现货高频价格呈现出正向相关的动态非对称相依结构,市场价格暴跌阶段沪深300股指期现货高频价格相依性略强于市场价格暴涨阶段,时变混合Copula函数在测度性能上具有明显优越性。

The probability of risk triggered by the impact between the prices of Chinese stock index futures and spots has been enhancing since CSI300 index futures were listed. Measuring the dependence, especially in extreme prices, scientifi- cally between CSI300 index futures and spots is significantly important for tracking cross-market risk. Thus, under the intraday high-frequency data environment, the marginal distributions of CSI300 index futures and spots are fitted with. realized hi-power volatility, and then the Clayton Copula, the Gumbel Copula and their mixture Copula containing timevarying parameters and dependence are constructed. The empirical results indicate that there is a high-positive dynamic asymmetric dependence between CSI300 index futures and spots, while the dependence in the bear markets shows slightly stronger than in the bull market. Moreover, time-varying mixture Copula shows better measurement performance.