A Multivariate Realized GARCH Model

Ilya Archakov, Peter Hansen and Asger Lunde

Papers from arXiv.org

Abstract: We propose a novel class of multivariate GARCH models that incorporate realized measures of volatility and correlations. The key innovation is an unconstrained vector parametrization of the conditional correlation matrix, which enables the use of factor models for correlations. This approach elegantly addresses the main challenge faced by multivariate GARCH models in high-dimensional settings. As an illustration, we explore block correlation matrices that naturally simplify to linear factor models for the conditional correlations. The model is applied to the returns of nine assets, and its in-sample and out-of-sample performance compares favorably against several popular benchmarks.

Date: 2020-12, Revised 2025-02
New Economics Papers: this item is included in nep-ecm and nep-ets
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