Unbiased covariance estimation with interpolated data
AbstractWe 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
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Bibliographic InfoPaper provided by Department of Economics, University of Siena in its series Department of Economics University of Siena with number 502.
Date of creation: Apr 2007
Date of revision:
Realized covariance; Previous tick interpolation; Epps effect; Nonsynchronous trading; Bias-correction;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-28 (All new papers)
- NEP-ECM-2007-04-28 (Econometrics)
- NEP-MST-2007-04-28 (Market Microstructure)
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