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

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Roy Cerqueti

    (University of Macerata, Department of Economics and Law)

  • Massimiliano Giacalone

    (University of Naples ‘Federico II’, Department of Economics and Statistics)

  • Demetrio Panarello

    (Parthenope University of Naples, Department of Economic and Legal Studies)

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.

Suggested Citation

  • Roy Cerqueti & Massimiliano Giacalone & Demetrio Panarello, 2018. "A Generalized Error Distribution-Based Method for Conditional Value-at-Risk Evaluation," Springer Books, in: Marco Corazza & María Durbán & Aurea Grané & Cira Perna & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 209-212, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-89824-7_38
    DOI: 10.1007/978-3-319-89824-7_38
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