Using Extreme Value Theory to Estimate Value-at-Risk
نویسندگان
چکیده
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 forecasts are desired. Extreme Value Theory (EVT) is proposed to overcome these problems. The application of EVT is illustrated by an example from the German hog market. It turns out that multi-period VaR forecasts derived by EVT deviate considerably from standard forecasts. We conclude that EVT is an useful complement to traditional VaR methods.
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