Modeling Realized Covariance Measures with Heterogeneous Liquidity: A Generalized Matrix-Variate Wishart State-Space Model

53 Pages Posted: 7 Oct 2020

See all articles by Bastian Gribisch

Bastian Gribisch

University of Cologne - Department of Econometrics and Statistics

Jan P. Hartkopf

University of Cologne - Cologne Graduate School in Management, Economics and Social Sciences

Date Written: August 17, 2020

Abstract

We propose to generalize the Wishart state-space model for realized covariance matrices of asset returns in order to capture complex measurement error structures induced by heterogeneous liquidity across assets. Our model assumes that the latent covariance matrix of the assets is observed through their realized covariance matrix with a Riesz measurement density, which generalizes the Wishart to monotone missing data. The Riesz alleviates the Wishart-implied attenuation of measurement errors for less liquid assets and translates into a convenient likelihood factorization which facilitates inference using simple Bayesian MCMC procedures. The statespace approach allows for a flexible description of the covariance dynamics implied by the data and an empirical application shows that the model performs very well in- and out-of-sample.

Keywords: Realized covariance, State-space model, Riesz distribution, Bayesian inference

JEL Classification: C32, C51, C58, G17

Suggested Citation

Gribisch, Bastian and Hartkopf, Jan P., Modeling Realized Covariance Measures with Heterogeneous Liquidity: A Generalized Matrix-Variate Wishart State-Space Model (August 17, 2020). Available at SSRN: https://ssrn.com/abstract=3676140 or http://dx.doi.org/10.2139/ssrn.3676140

Bastian Gribisch (Contact Author)

University of Cologne - Department of Econometrics and Statistics ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

Jan P. Hartkopf

University of Cologne - Cologne Graduate School in Management, Economics and Social Sciences ( email )

Albertus-Magnus-Platz
Cologne, 50931
Germany

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