Unbiased covariance estimation with interpolated data
Unbiased covariance estimation with interpolated data
复制标题
使用插值数据进行无偏协方差估计
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
R. Renò
中科院分区：
文献类型：
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作者：
T. Kanatani;R. Renò
我们研究协方差估计，当被迫使用均匀间隔的数据，已经被以前的插值操作。我们提出了一种无偏协方差估计，它被设计用来纠正由于插值而产生的两种偏差：非同步交易和零回报偏差。我们展示了这些源如何使通常的已实现协方差估计有偏，而传统的超前-滞后修正并不能完全纠正这些偏差。在极高频情况下，所提出的估计量与Hayashi和Yoshida（2005）的无偏估计量是一致的。我们用模拟和实际数据说明了该方法的潜在优势
We study covariance estimation when compelled to use evenly spaced data which have already been manipulated by previous-tick interpolation. We propose an un- biased covariance estimator, which is designed to correct for the two biases arising because of the interpolation: non-synchronous trading and zero-return bias. We show how these sources make usual realized covariance estimators biased, and that the traditional lead-lag modification does not correct these biases completely. The proposed estimator is also proved to be consistent with the Hayashi and Yoshida (2005)’s unbiased estimator under extremely high frequency situation. We illustrate the potential advantages of the method with both simulated and actual data