Risk Measure Estimation On Fiegarch Processes

Taiane S. Prass and S\'ilvia R. C. Lopes

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Abstract: 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 $VaR_p$ 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 $VaR_p$, $ES_p$ and MaxLoss for a portfolio composed by stocks of four Brazilian companies.

Date: 2013-05
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-rmg
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