Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model

Bastian Gribisch and Jan Patrick Hartkopf

Journal of Econometrics, 2023, vol. 235, issue 1, 43-64

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 modern robust and data efficient realized covariance estimators and 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 and translates into a convenient likelihood factorization which facilitates inference using simple Bayesian MCMC procedures. The state-space 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 (search for similar items in EconPapers)
JEL-codes: C32 C51 C58 G17 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:235:y:2023:i:1:p:43-64

DOI: 10.1016/j.jeconom.2022.01.007

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