<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>34</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Prass, Taiane Schaedler</style></author><author><style face="normal" font="default" size="100%">Lopes, Sílvia Regina Costa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Risk Measure Estimation on Fiegarch Processes</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We consider the Fractionally Integrated Exponential Generalized Autoregressive Conditional Heteroskedasticity process, denoted by FIEGARCH(p,d,q), introduced by Bollerslev and Mikkelsen (1996). We present a simulated study regarding the estimation of the risk measure VaRp on FIEGARCH processes. We consider the distribution function of the portfolio log-returns (univariate case) and the multivariate distribution function of the risk-factor changes (multivariate case). We also compare the performance of the risk measures VaRp, ESp and MaxLoss for a portfolio composed by stocks of four Brazilian companies.&lt;/p&gt;
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