VaR and ES for linear portfolios with mixture of generalized Laplace distributions risk factors |
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Authors: | Jules Sadefo Kamdem |
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Institution: | (1) Laboratoire de Math?matique (CNRS UMR 6056) Reims, Universit? d’ Evry Val d’ Essonne (Departement de Mathematiques), BP 1039, Moulin de la Housse, 51687 Reims, France |
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Abstract: | In this paper, we propose an explicit estimation of Value-at-Risk (VaR) and Expected Shortfall (ES) for linear portfolios
when the risk factors change with a convex mixture of generalized Laplace distributions (M-GLD). We introduce the dynamics
Delta-GLD-VaR, Delta-GLD-ES, Delta-MGLD-VaR and Delta-MGLD-ES, by using conditional correlation multivariate GARCH. The generalized
Laplace distribution impose less restrictive assumptions during estimation that should improve the precision of the VaR and
ES through the varying shape and fat tails of the risk factors in relation with the historical sample data. We also suggested
some areas of application to measure price risk in agriculture, risk management and financial portfolio optimization. |
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Keywords: | |
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