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fuzzy random variables sign in to follow this
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Fuzzy Value-at-Risk and Expected Shortfall for Portfolios with Heavy-Tailed Returns
Company: Economic Modelling
Company Url: Click here to open
Year Of Publication: 2014
Month Of Publication: April
Resource Link: Click here to open
Pages: 247-256
Download Count: 0
View Count: 796
Comment Num: 0
Language: English
Source: article
Who Can Read: Free
Date: 4-5-2014
Publisher: Administrator
Summary
This paper is concerned with linear portfolio value-at-risk (VaR) and expected shortfall (ES) computation when the portfolio risk factors are leptokurtic, imprecise and/or vague. Following Yoshida (2009), the risk factors are modeled as fuzzy random variables in order to handle both their random variability and their vagueness. We discuss and extend the Yoshida model to some non-Gaussian distributions and provide associated ES. Secondly, assuming that the risk factors' degree of imprecision changes over time, original fuzzy portfolio VaR and ES models are introduced. For a given subjectivity level fixed by the investor, these models allow the computation of a pessimistic and an optimistic estimation of the value-at-risk and of the expected shortfall. Finally, some empirical examples carried out on three portfolios constituted by some chosen French stocks, show the effectiveness of the proposed methods.
(volume 39)
Author(s)
Moussa, A. Mbairadjim Sign in to follow this author
Sadefo-Kamdem, Jules Sign in to follow this author
Terraza, Michel Sign in to follow this author
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