A Generalized Error Distribution-Based Method for Conditional Value-at-Risk Evaluation

Roy Cerqueti (), Massimiliano Giacalone () and Demetrio Panarello
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Roy Cerqueti: University of Macerata, Department of Economics and Law
Massimiliano Giacalone: University of Naples ‘Federico II’, Department of Economics and Statistics

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2018, pp 209-212 from Springer

Abstract: 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 of a bivariate Generalized Error Distribution (G.E.D.). We present an algorithm with 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.

Keywords: Portfolio theory; Gaussian Copula; Generalized Correlation Coefficient (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-89824-7_38

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DOI: 10.1007/978-3-319-89824-7_38

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