A Component GARCH Model With Time Varying Weights

CORE Discussion Paper No. 2007/19

32 Pages Posted: 16 Aug 2007

See all articles by Luc Bauwens

Luc Bauwens

Université catholique de Louvain

Giuseppe Storti

University of Salerno - Department of Economics

Date Written: February 16, 2007

Abstract

We present a novel GARCH model that accounts for time varying, state dependent, persistence in the volatility dynamics. The proposed model generalizes the component GARCH model of Ding and Granger (1996). The volatility is modelled as a convex combination of unobserved GARCH components where the combination weights are time varying as a function of appropriately chosen state variables. In order to make inference on the model parameters, we develop a Gibbs sampling algorithm. Adopting a fully Bayesian approach allows to easily obtain medium and long term predictions of relevant risk measures such as value at risk and expected shortfall. Finally we discuss the results of an application to a series of daily returns on the S&P500.

Keywords: GARCH, persistence, volatility components, value-at-risk, expected shortfall

JEL Classification: C11, C15, C22

Suggested Citation

Bauwens, Luc and Storti, Giuseppe, A Component GARCH Model With Time Varying Weights (February 16, 2007). CORE Discussion Paper No. 2007/19, Available at SSRN: https://ssrn.com/abstract=1006754 or http://dx.doi.org/10.2139/ssrn.1006754

Luc Bauwens (Contact Author)

Université catholique de Louvain ( email )

CORE
34 Voie du Roman Pays
B-1348 Louvain-la-Neuve, b-1348
Belgium
32 10 474321 (Phone)
32 10 474301 (Fax)

Giuseppe Storti

University of Salerno - Department of Economics ( email )

Via John Paul II, 132
Fisciano (SA), 84084
Italy

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