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Accurate value-at-risk forecasting based on the Normal-GARCH model


Paolella, Marc; Hartz, Christoph; Mittnik, Stefan (2006). Accurate value-at-risk forecasting based on the Normal-GARCH model. Computational Statistics & Data Analysis, 51(4):2295-2312.

Abstract

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.

Abstract

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.

Citations

27 citations in Web of Science®
40 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Banking and Finance
Dewey Decimal Classification:330 Economics
Language:English
Date:2006
Deposited On:30 Jul 2014 11:56
Last Modified:05 Apr 2016 18:00
Publisher:Elsevier
ISSN:0167-9473
Publisher DOI:https://doi.org/10.1016/j.csda.2006.09.017
Official URL:http://www.sciencedirect.com/science/article/pii/S0167947306003367
Other Identification Number:merlin-id:4466

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