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高频波动率矩阵估计的比较分析——基于有噪非同步的金融数据

, PP. 19-29

Keywords: 波动率矩阵,高频数据,微观结构噪声,非同步交易

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Abstract:

?基于高频数据的波动率矩阵估计可有效解决传统低频估计面临的种种瓶颈问题。然而,由于受非同步和微观结构噪声等的影响,传统的高频波动率矩阵估计会产生艾普斯效应,并偏离其理论值。本文主要考虑非同步逐笔高频数据的三种同步化方法和五种传统已实现波动率矩阵的纠偏降噪方法,并从数值模拟和沪深股市的实证分析两个角度对两类方法分别展开了全面深入的比较研究。结果表明:更新时间同步化法最大程度地保留了数据信息,传统未纠偏的已实现波动率矩阵具有艾普斯效应,其偏差较大,多变量已实现核估计、双频已实现波动率矩阵估计、调整的已实现波动率矩阵估计的纠偏降噪效果较好,事先平均HY估计和HY估计相对表现较差。研究结果可为相关领域工作者进一步的研究与应用提供方法上的参考与指导。

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