Estimation of Integrated Covolatility for Asynchronous Assets in the Presence of Microstructure Noise

Abstract:     
Use of high-frequency return data has led to dramatic improvements in both theoretical and applied finance research. Estimators of covariance among multiple processes have been proposed, such as realized variance and Hayashi-Yoshida estimator. We are introducing a new estimator, random lead-lag estimator (RLLE), which coincides with the Hayashi-Yoshida estimator at very high frequency and with the realized covariance at low frequency. We studied the performance of RLLE both with and without microstructure noise for non-synchronous data and obtained the optimal estimation with good bias-variance trade-off. Our result is conformed by simulation and real data applications in stock and online auction markets.

Number of Pages in PDF File: 22

Keywords: High frequency data, microstructure noise, non-synchronicity, realized covariance estimator, bias-variance trade-off

working papers series