A DCC-Type Approach for Realized Covariance Modelling With Score-Driven Dynamics

38 Pages Posted: 8 Jan 2019 Last revised: 3 Mar 2020

See all articles by Danilo Vassallo

Danilo Vassallo

Scuola Normale Superiore

Giuseppe Buccheri

University of Rome Tor Vergata

Fulvio Corsi

University of Pisa - Department of Economics; City University London

Date Written: March 3, 2020

Abstract

We propose a class of score-driven realized covariance models where volatilities and correlations are separately estimated. We can thus combine univariate realized volatility models with a recently introduced class of score-driven realized covariance models based on Wishart and matrix-F distributions. The proposed models are computationally simple to estimate in high dimensions and allow complete flexibility in the choice of the univariate specification. Through a Monte-Carlo study, we show that the two-step maximum likelihood procedure provides accurate parameter estimates in small samples. Empirically, we find that the proposed models outperform joint estimations, with forecasting gains that become more significant as dimension increases.

Keywords: Realized Covariance, Dynamic Dependencies, Covariance forecasting, Score-driven models, Portfolio construction

JEL Classification: C58, D53, D81

Suggested Citation

Vassallo, Danilo and Buccheri, Giuseppe and Corsi, Fulvio, A DCC-Type Approach for Realized Covariance Modelling With Score-Driven Dynamics (March 3, 2020). Available at SSRN: https://ssrn.com/abstract=3305628 or http://dx.doi.org/10.2139/ssrn.3305628

Danilo Vassallo (Contact Author)

Scuola Normale Superiore ( email )

Piazza dei Cavalieri, 7
Pisa, 56126
Italy
+393312732394 (Phone)

Giuseppe Buccheri

University of Rome Tor Vergata ( email )

Via columbia 2
Rome, Rome 00123
Italy
39 06 72595945 (Phone)

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

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