Advances in Risk Management - download pdf or read online
By Greg N. Gregoriou (eds.)
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The visual inspection of MEF is sometimes tricky as no (or several) “break(s)” can be observed. Several authors have suggested methods to identify the optimal threshold (see, for example, Drees and Kaufmann, 1998; Dupuis, 1999; Matthys and Beirlant, 2003) but no single approach has become widely accepted. A possible solution is proposed in Chapelle, Crama, Hübner and Peters (2005) with an algorithmic procedure that builds on ideas from Huisman, Koedijk, Kool and Palm (2001) and shares some similarities with a procedure used by Longin and Solnik (2001) in a different context.
Severity distribution The severity distribution models the economic impact of operational risk loss events. Consequently, any strictly positive continuous distribution can be used to model operational losses. However, operational risk databases are often characterized by a large bulk of “high frequency/low impact” losses and a few “low frequency/high impact” losses. Leptokurtic distributions are thus most appropriate to model the severity distribution. Candidate distributions include log-normal, log-logistic, Pareto or Weibull distributions.
However, the expected value of the portfolio across multiple scenarios is not computed by the regulator. Instead, the worst outcome across the scenarios deﬁnes the risk of a coherent risk measure. It is important to emphasize that coherent risk measures do not account for diversiﬁcation. Although ADEH have a subadditivity axiom that parallels a property implied by our risk measure, their deﬁnition of risk applies A M I Y A T O S H P U R N A N A N D A M E T A L. 25 to terminal portfolio values. Thus, the portfolio weights of the underlying assets cannot be altered to exploit the beneﬁts of diversiﬁcation.
Advances in Risk Management by Greg N. Gregoriou (eds.)