Unbiased covariance estimation with interpolated data

Taro Kanatani () and Roberto Renò

Department of Economics University of Siena from Department of Economics, University of Siena

Abstract: 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

Keywords: Realized covariance; Previous tick interpolation; Epps effect; Nonsynchronous trading; Bias-correction (search for similar items in EconPapers)
JEL-codes: C14 C32 C63 (search for similar items in EconPapers)
Date: 2007-04
New Economics Papers: this item is included in nep-ecm and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:usi:wpaper:502

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