Publication: Accurate value-at-risk forecasting based on the Normal-GARCH model
Accurate value-at-risk forecasting based on the Normal-GARCH model
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Paolella, M., Hartz, C., & Mittnik, S. (2006). Accurate value-at-risk forecasting based on the Normal-GARCH model. Computational Statistics & Data Analysis, 51(4), 2295–2312. https://doi.org/10.1016/j.csda.2006.09.017
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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 supp
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- Hartz, Christoph
- Mittnik, Stefan
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Paolella, M., Hartz, C., & Mittnik, S. (2006). Accurate value-at-risk forecasting based on the Normal-GARCH model. Computational Statistics & Data Analysis, 51(4), 2295–2312. https://doi.org/10.1016/j.csda.2006.09.017