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:: Volume 4, Issue 1 (9-2010) ::
J. of Stat. Sci. 2010, 4(1): 59-76 Back to browse issues page
The application of extreme value theory in value at risk estimation:The case of liability insurance claims in Iran insurance company
Ghadi Mahdavi, Zahra Majedi
Abstract:   (16919 Views)
The GARCH(1,1) and GARCH(1,1)-t models lead to highly volatile quantile forecasts, while historical simulation, Variance–Covariance, adaptive generalized Pareto distribution and non-adaptive generalized Pareto distribution models provide more stable quantile forecasts. In general, GARCH(1,1)-t, generalized Pareto distribution models and historical simulation are preferable for most quantiles.
Keywords: Value-at-risk, Extreme value theory, GARCH model, Historical simulation, Variance- Covariance
Full-Text [PDF 2123 kb]   (2823 Downloads)    
Type of Study: Applied | Subject: Applied Statistics
Received: 2011/11/28 | Accepted: 2011/11/29
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Mahdavi G, Majedi Z. The application of extreme value theory in value at risk estimation:The case of liability insurance claims in Iran insurance company. J. of Stat. Sci.. 2010; 4 (1) :59-76
URL: http://jss.irstat.ir/article-1-87-en.html


Volume 4, Issue 1 (9-2010) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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