考虑共同跳跃的波动建模:基于高频数据视角

针对共同跳跃研究的不足,文章沿袭已有理论框架,采用常用的日内跳跃检验方法,构建了共同跳跃(协)方差和连续样本路径(协)方差,并扩展HAR-RV-CJ模型,将(协)方差、共同跳跃置于统一波动模型框架内。通过对上证综指和深圳成指高频数据的实证分析,结果显示两指数共同跳跃占其各自的跳跃比例较大,且基本上都是同方向的跳跃;共同跳跃(协)方差和连续样本路径(协)方差对已实现(协)方差的影响都是显著的,考虑共同跳跃影响有助于提高(协)方差建模的准确性。此研究有助于投资者优化投资策略和为监管部门提供监管基础。

Volatility Modeling in Consideration of the Co-jumps: Based on the Perspective of High-frequency Data

In consideration of the insufficience of the existing researches on co-jumps, co-jumps (co)variance and continuous sample path (co)variance are established using the common intraday jump test and the HAR-RV-CJ model is extended by taking (co)variance and co-jumps together into account, according to the existing theoretical framework. By virtue of high frequency data from Shanghai composite index and Shenzhen component index, the empirical analyses show that the number of the co-jumps of two indexes has a large proportion to their own jumps, most of the co-jumps are the same direction, co-jumps (co)variance and continuous sample path (co)variance both have significant effects on the (co)variance and considering co-jumps makes the extended model more accurate. This study makes contribution to the investment strategy optimization for investor and also provides regulatory basis for the regulatory authorities.