managing supply risk using value at risk method based on extreme value theory

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Using Extreme Value Theory to Estimate Value-at-Risk

Martin Odening and Jan Hinrichs Abstract: This article examines problems that may occur when conventional Value-at-Risk (VaR) estimators are used to quantify market risks in an agricultural context. For example, standard VaR methods, such as variance-covariance method or historical simulation, can fail when the return distribution is fat tailed. This problem is aggravated when long-term VaR for...

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Value at Risk Estimation Using Extreme Value Theory

A common assumption in quantitative financial risk modelling is the distributional assumption of normality in the asset’s return series, which makes modelling easy but proves to be inefficient if the data exhibit extreme tails. When dealing with extreme financial events like the Global Financial Crisis of 2007-2008 while quantifying extreme market risk, Extreme Value Theory (EVT) proves to be a...

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جلد ۱۷، شماره ۶۶، صفحات ۱۶۱-۱۹۴

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