In this paper, we show some results regarding the evaluation of Value-at- Risk (VaR) of some portfolios using a Gaussian Copula, modified by introducing the Generalized Correlation Coefficient, and assuming a Generalized Error Distribution (G.E.D.) for the single returns in the portfolios. In the literature, various authors considered the Copula function approach to evaluate market risk. In our proposal we consider a Lpmin algorithm to estimate p, the shape parameter of the distribution. Finally, we compare the classical RiskMetrics method with our G.E.D. method based on a modified Gaussian Copula.

A G.E.D method for market risk evaluation using a modified Gaussian Copula

GIACALONE, Massimiliano;
2017

Abstract

In this paper, we show some results regarding the evaluation of Value-at- Risk (VaR) of some portfolios using a Gaussian Copula, modified by introducing the Generalized Correlation Coefficient, and assuming a Generalized Error Distribution (G.E.D.) for the single returns in the portfolios. In the literature, various authors considered the Copula function approach to evaluate market risk. In our proposal we consider a Lpmin algorithm to estimate p, the shape parameter of the distribution. Finally, we compare the classical RiskMetrics method with our G.E.D. method based on a modified Gaussian Copula.
2017
Giacalone, Massimiliano; Panarello, D.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/483138
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