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Forecasting extreme risk using regime-switching GARCH models: a case from an energy commodity

Yang Xiao (Business School, Chengdu University of Technology, Chengdu, China)

International Journal of Emerging Markets

ISSN: 1746-8809

Article publication date: 23 July 2020

Abstract

Purpose

The purpose of this paper is to investigate regime-switching and single-regime GARCH models for the extreme risk forecast of the developed and the emerging crude oil markets.

Design/methodology/approach

The regime-switching GARCH-type models and their single-regime counterparts are used in risk forecast of crude oil.

Findings

The author finds that the regime-switching GARCH-type models are suitable for the developed and the emerging crude oil markets in that they effectively measure the extreme risk of crude oil in different cases. Meanwhile, the model with switching regimes captures dynamic structures in financial markets, and these models are just only better than the corresponding single-regime in terms of long position risk forecast, instead of short position. That is, it just outperforms the single-regime on the downside risk forecast.

Originality/value

This study comprehensively compares risk forecast of crude oil in different situations through the competitive models. The obtained findings have strong implications to investors and policymakers for selecting a suitable model to forecast extreme risk of crude oil when they are faced with portfolio selection, asset allocation and risk management.

Keywords

Acknowledgements

The author would like to acknowledge the Editor, Ziaul Haque Munim, for his helpful guidance and thank for the insightful comments of the three anonymous reviewers. The author wishes to thank David Ardia and Keven Bluteau for their help. This work is supported by the Technology Project of CDUT (2018KJC0354).

Citation

Xiao, Y. (2020), "Forecasting extreme risk using regime-switching GARCH models: a case from an energy commodity", International Journal of Emerging Markets, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJOEM-11-2019-0974

Publisher

:

Emerald Publishing Limited

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