High-Frequency Covariance Matrix Estimation Using Price Durations

57 Pages Posted: 1 May 2018

See all articles by Xiaolu Zhao

Xiaolu Zhao

Donbei University of Finance and Economics

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Stephen J. Taylor

Lancaster University - Department of Accounting and Finance

Date Written: April 14, 2018

Abstract

We propose a price duration based covariance matrix estimator using high frequency transactions data. The effect of the last-tick time-synchronisation methodology, together with effects of important market microstructure components is analysed through a comprehensive Monte Carlo study. To decrease the number of negative eigenvalues produced by the non positive-semi-definite (psd) covariance matrix, we devise an average covariance estimator by taking an average of a wide range of duration based covariance matrix estimators. Empirically, candidate covariance estimators are implemented on 19 stocks from the DJIA. The duration based covariance estimator is shown to provide comparably accurate estimates with smaller variation compared with competing estimators. An out-of-sample GMV portfolio allocation problem is studied. A simple shrinkage technique is introduced to make the sample matrices psd and well-conditioned. Compared to competing high-frequency covariance matrix estimators, the duration based estimator is shown to give more stable portfolio weights and higher Sharpe ratios while maintaining comparably low portfolio variances.

Keywords: Price Durations, Covariance Estimation, High-Frequency Data, Market Microstructure Noise, Minimum Variance Portfolio

JEL Classification: C41, C14, C13, C58

Suggested Citation

Zhao, Xiaolu and Nolte, Ingmar and Taylor, Stephen J., High-Frequency Covariance Matrix Estimation Using Price Durations (April 14, 2018). Available at SSRN: https://ssrn.com/abstract=3162514 or http://dx.doi.org/10.2139/ssrn.3162514

Xiaolu Zhao (Contact Author)

Donbei University of Finance and Economics ( email )

217 Jianshan St,
Shahekou
Dalian, Liaoning
China

Ingmar Nolte

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Stephen J. Taylor

Lancaster University - Department of Accounting and Finance ( email )

The Management School
Lancaster LA1 4YX
United Kingdom
+ 44 15 24 59 36 24 (Phone)
+ 44 15 24 84 73 21 (Fax)

HOME PAGE: http://www.lancs.ac.uk/staff/afasjt

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