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Interval Estimation for the Value-at-Risk Based on GARCH Models with Heavy Tailed Innovations
Year Of Publication: 2005
Month Of Publication: June
Pages: 28
Download Count: 710
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Comment Num: 0
Language: EN
Source: working paper
Who Can Read: Free
Date: 11-7-2005
Publisher: Administrator
Summary
ARCH and GARCH models are widely used to model financial market volatilities inmany risk management applications. Based on a GARCH model with heavy-tailed innovations,an estimator, which corresponds to the extremal quantile of the conditionaldistribution of a GARCH process, of the conditional Value-at-Risk (VaR) is constructed.We characterize the limiting distribution of the conditional VaR estimator of the GARCHprocess with heavy-tailed innovations. We also propose two methods, the normal approximationmethod and the data tilting method, for constructing confidence intervals for theconditional VaR estimator and assess their accuracies by simulation studies. Finally, weapply the proposed approach to an energy market data set.
This document is published in Journal of Econometrics (volume 137, number 2), April 2007, 556-576.
http://dx.doi.org/10.1016/j.jeconom.2005.08.008
Author(s)
Chan, Ngai Hang Sign in to follow this author
Deng, Shi-Jie Sign in to follow this author
Peng, Liang Sign in to follow this author
Xia, Zhendong Sign in to follow this author
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