Extreme value theory has hidden risks, research finds
Method for calculating capital based on sparse data can lead to additional model risk
Extreme value theory (EVT) has been hailed as a solution to the problem of calculating capital requirements based on sparse data about tail risks. But academics in Regensburg and Sydney have discovered that the use of EVT may in fact involve more model risk than traditional methods.
Ralf Kellner, a researcher at the University of Regensburg, in Germany, and the lead author of a paper due to be published this year in the Journal of Risk, says the case for EVT neglects “second order” model risk
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