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Robustness and sensitivity of risk evaluations

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Academic year: 2019

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Fig ur e3 .1 : L e f t : s imula t e d R N- de ns it ye mpir ic a l dis t r ibut io n f unc t io ns o f t he o ut put unde r t he ba s e line ( da s he d bla c k ) a ndt he s t r e s s e d ( s o lid g r e y ) mo de l unde r pr o ble m (o f t hes o lut io n
Fig ur e 3 .2 : E mpir ic a l dis t r ibut io n f unc t io ns o f t he input f a c t o r s unde r t he ba s e liner e dt he a x is o n t he
Fig ur e 3 .3 : L e f t : s imula t e d R N- de ns it yo f t he s o lut io n. R ig ht : s imula t e d e mpir ic a l( s o lid g r e y )dis t r ibut io n f unc t io ns o f t he o ut put unde r t he ba s e line ( da s he d bla c k ) a nd t he s t r e s s e di
Fig ur e 3 .4 : E mpir ic a l dis t r ibut io n f unc t io ns o f t he input f a c t o r s unde r t he ba s e line1 0 %
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Outline

Robustness regions of convex risk measures Comparison to robustness regions of Value-at-Risk VaR constraints Definition of sensitivity measures A Stochastic comparisons

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