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A multivariate realized GARCH model

delete2025-05-31
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PRE
AI
I
Ilya Archakov
P
Peter Reinhard Hansen *
A
Asger Lunde
DOI:10.1016/j.jeconom.2025.106040delete
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Abstract

Abstract

En 中文
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.

Journal

Journal of Econometrics cover
Journal of Econometrics
IF:
4
Papers:
5.2K
Citations:
3.0W

Organization

U
university of north carolina
Scholars:
7.4W
Papers: 6.5W
Citations: 93
Y
York University
Scholars:
1.0K
Papers: 593
Citations: 1.5K