A Bayesian High-Frequency Estimator of the Multivariate Covariance of Noisy and Asynchronous Returns

46 Pages Posted: 20 Feb 2012 Last revised: 21 May 2014

See all articles by Stefano Peluso

Stefano Peluso

University of Lugano and Swiss Finance Institute

Fulvio Corsi

University of Pisa - Department of Economics; City University London

Antonietta Mira

Università della Svizzera italiana - InterDisciplinary Institute of Data Science

Date Written: April 5, 2014

Abstract

A multivariate positive definite estimator of the integrated covariance matrix of noisy and asynchronously observed asset returns is proposed. We adopt a Bayesian Dynamic Linear Model where microstructure noise is interpreted as measurement error, and asynchronous trading as missing observations in an otherwise synchronous series. Missing observations are treated as any other parameter, as typical in a Bayesian framework. An augmented Gibbs algorithm is used since all full conditionals are available and its convergence and robustness are discussed. A realistic simulation study compares our estimator with existing alternatives, under different liquidity and microstructure noise conditions. The results suggest that our estimator is superior in terms of RMSE particularly under severe conditions, such as portfolios of assets with heterogeneous liquidity and high level of microstructure noise. The application to the empirical dataset of ten tick-by-tick stock price series confirms the simulation results.

Keywords: asinchronicity, data augmentation, Gibbs sampler, missing observations, realized covariance

Suggested Citation

Peluso, Stefano and Corsi, Fulvio and Mira, Antonietta, A Bayesian High-Frequency Estimator of the Multivariate Covariance of Noisy and Asynchronous Returns (April 5, 2014). Available at SSRN: https://ssrn.com/abstract=2003492 or http://dx.doi.org/10.2139/ssrn.2003492

Stefano Peluso (Contact Author)

University of Lugano and Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Fulvio Corsi

University of Pisa - Department of Economics ( email )

via Ridolfi 10
I-56100 Pisa, PI 56100
Italy

HOME PAGE: http://people.unipi.it/fulvio_corsi/

City University London ( email )

Northampton Square
London, EC1V OHB
United Kingdom

Antonietta Mira

Università della Svizzera italiana - InterDisciplinary Institute of Data Science ( email )

Via Giuseppe Buffi 13
CH-6900 Lugano, CH-6904
Switzerland

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