Estimating the integrated volatility using high-frequency data with zero durations
Estimating the integrated volatility using high-frequency data with zero durations
复制标题
使用零持续时间的高频数据估计综合波动率
DOI：
10.1016/j.jeconom.2017.12.008
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发表时间：
2018
影响因子：
6.3
通讯作者：
Bing-Yi Jing
中科院分区：
文献类型：
--
作者：
Zhi Liu;Xin-Bing Kong;Bing-Yi Jing
在使用高频数据估计综合波动率时，有充分的证据表明，微观结构噪声的存在是一个重大挑战。最近的文献表明，存在多个观测值，这是数据集中的一个常见特征，带来了额外的困难。在本研究中，我们证明了预平均估计量在多个观测值下仍然是相合的，并建立了估计量的相关渐近分布。我们还表明，基于多个观测值的预平均估计达到了与假设我们知道所有交易的确切交易时间的“理想”估计相同的渐近效率。模拟研究支持的理论结果，我们也说明了估计使用真实的数据分析。
In estimating integrated volatility using high-frequency data, it is well documented that the presence of microstructure noise presents a major challenge. Recent literature has shown that the presence of multiple observations, a common feature in datasets, brings additional difficulty. In this study, we show that the preaveraging estimator is still consistent under multiple observations, and the related asymptotic distribution of the estimator is established. We also show that the preaveraging estimator based on multiple observations achieves the same asymptotic efficiency as the “ideal” estimator that assumes we know the exact trading times of all transactions. Simulation studies support the theoretical results, and we also illustrate the estimator using real data analysis.