A detailed comparison of value at risk estimates

Pilar Abad and Sonia Benito

Mathematics and Computers in Simulation (MATCOM), 2013, vol. 94, issue C, 258-276

Abstract: This work investigates the performance of different models of value at risk. We include several methods (parametric, historical simulation, Monte Carlo, and extreme value theory) and some models to compute the conditional variance. We analyze several international stock indexes and examine two types of periods: stable and volatile periods. To choose the best model, we employ a two-stage selection approach. The result indicates that the best model is a parametric model with conditional variance estimated by an asymmetric GARCH model under Student's t-distribution of returns. This paper shows that parametric models can obtain successful VaR measures if conditional variance is estimated properly.

Keywords: Value at risk; Parametric model; Extreme value theory model; GARCH model; Risk management (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:94:y:2013:i:c:p:258-276

DOI: 10.1016/j.matcom.2012.05.011

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