One of the most important issues in finance is to correctly measure the risk profile of a portfolio, which is fundamental to take optimal decisions on the capital allocation. In this paper, we deal with the evaluation of portfolio’s Conditional Value-at-Risk (CVaR) using a modified Gaussian Copula, where the correlation coefficient is replaced by a generalization of it, obtained as the correlation parameter ofabivariateGeneralizedErrorDistribution(G.E.D.).Wepresentanalgorithmwith the aim of verifying the performance of the G.E.D. method over the classical RiskMetrics one, resulting in higher performance of the G.E.D. method.

A Generalized Error Distribution-based method for Conditional Value-at-Risk evaluation

Giacalone M.;
2018

Abstract

One of the most important issues in finance is to correctly measure the risk profile of a portfolio, which is fundamental to take optimal decisions on the capital allocation. In this paper, we deal with the evaluation of portfolio’s Conditional Value-at-Risk (CVaR) using a modified Gaussian Copula, where the correlation coefficient is replaced by a generalization of it, obtained as the correlation parameter ofabivariateGeneralizedErrorDistribution(G.E.D.).Wepresentanalgorithmwith the aim of verifying the performance of the G.E.D. method over the classical RiskMetrics one, resulting in higher performance of the G.E.D. method.
2018
Cerqueti, R.; Giacalone, M.; Panarello, D.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/483145
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