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Forecasting Value-at-Risk and Expected Shortfall using Fractionally Integrated Models of Conditional Volatility: International Evidence
Company: International Review of Financial Analysis
Company Url: Click here to open
Year Of Publication: 2012
Month Of Publication: June
Resource Link: Click here to open
Pages: 21-33
Download Count: 0
View Count: 1709
Comment Num: 0
Language: English
Source: article
Who Can Read: Free
Date: 6-23-2012
Publisher: Administrator
The present study compares the performance of the long memory FIGARCH model, with that of the short memory GARCH specification, in the forecasting of multi-period Value-at-Risk (VaR) and Expected Shortfall (ES) across 20 stock indices worldwide. The dataset is comprised of daily data covering the period from 1989 to 2009. The research addresses the question of whether or not accounting for long memory in the conditional variance specification improves the accuracy of the VaR and ES forecasts produced, particularly for longer time horizons.
(volume 27)
Degiannakis, Stavros Sign in to follow this author
Floros, C_hristos Sign in to follow this author
Dent, Pamela Sign in to follow this author
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