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Efficient Computation of Value at Risk with Heavy-Tailed Risk Factors
Year Of Publication: 2009
Month Of Publication: July
Pages: 24
Download Count: 22
View Count: 1898
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 5-31-2010
Publisher: Administrator
Summary
The probabilities considered in value-at-risk (VaR) are typically of moderate deviations. However, the variance reduction techniques developed in the literature for VaR computation are based on large deviations methods. Modeling heavy-tailed risk factors
using multivariate t distributions, we develop a new moderate-deviations method for VaR computation. We show that the proposed method solves the corresponding optimization problem exactly, while previous methods produce approximations to the exact solution. Thus, the proposed method consistently outperforms existing methods derived from large deviations theory under various settings. The results are confirmed by a simulation study.
This document is published as "Efficient Simulation of Value at Risk with Heavy-Tailed Risk Factors" in Operations Research (volume 59, number 6) November 2011, 1395-1406.
http://dx.doi.org/10.1287/opre.1110.0993
Author(s)
Fuh, Cheng-Der Sign in to follow this author
Hu, Inchi Sign in to follow this author
Wang, Ren-Her Sign in to follow this author
Hsu, Ya-Hui Sign in to follow this author
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