A Generalized Error Distribution-BasedMethod for Conditional Value-at-Risk Evaluation

Roy Cerqueti

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

A Generalized Error Distribution-BasedMethod for Conditional Value-at-Risk Evaluation

Roy Cerqueti

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

3 Citations (Scopus)

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 Risk- Metrics one, resulting in higher performance of the G.E.D. method.

Original language	English
Title of host publication	Mathematical and StatisticalMethods for Actuarial Sciences and Finance,
Publisher	Springer
DOIs	https://doi.org/10.1007/978-3-319-89824-7_38
Publication status	Published - 2018
Externally published	Yes

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A Generalized Error Distribution-BasedMethod for Conditional Value-at-Risk Evaluation

Abstract

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