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| Author: | Sun, W. Rachev, S. Fabozzi, F.J. |
| Title: | A new approach for using Lévy processes for determining high-frequency value-at-risk predictions |
| Journal: | European Financial Management
2009 : MAR, VOL. 15:2, p. 340-361 |
| Index terms: | financial management financial risk value-at-risk |
| Language: | eng |
| Abstract: | This article introduces a new approach for using Lévy processes to compute value-at-risk (VaR) using high-frequency data. The approach is a parametric model that uses an ARMA(1,1)-GARCH(1,1) model where the tail events are modeled using fractional Lévy stable distribution. High-frequency data is used for the German DAX index and the VaR estimates from this approach are compared to those of a standard nonparametric estimation method that captures the empirical distribution function, and with models where tail events are modeled using Gaussian distribution and fractional Gaussian noise. |
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