Crisis, Value at Risk, and Conditional Extreme Value Theory via Garch-Jump Model : WestminsterResearch

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Title	Crisis, Value at Risk, and Conditional Extreme Value Theory via Garch-Jump Model
Type	Journal article
Authors	Ze-To, S.
Abstract	This study develops a new conditional extreme value theory-based model (EVT) combined with the GARCH-Jump model to forecast extreme risks. This paper utilizes the GARCH-Jump model to asymmetrically feed back the past realization of jump innovation to the future volatility of the return distribution and uses the EVT to model the tail distribution of the GARCH-Jump-processed residuals. The model is compared to the GARCH-t model and the conditional EVT-GARCH model to evaluate its performance in estimating extreme losses in three major market crashes and crises. The results show that the conditional EVT-GARCH-Jump model outperforms the GARCH and GARCH-t models in depicting the non-normality and in providing accurate VaR forecasts in the in-sample and out-sample tests. The EVT-GARCH-Jump model, which can measure the volatility of extreme price movement in capital markets due to unexpected events, enhances the EVT-based model for measuring the tail risk.
Keywords	value-at-risk
	extreme value theory
Journal	Review of Futures Markets
Journal citation	18 (4), pp. 319-345
ISSN	0898-011X
Year	2010
Publisher	Chicago Board of Trade
Published	2010

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Crisis, Value at Risk, and Conditional Extreme Value Theory via Garch-Jump Model

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