This study investigates the simplicity and adequacy of tail-based risk measures—value-at-risk(VaR)and expected shortfall(ES)—when applied to tail targeting of the extreme value(EV)model.We implement Lévy-VaR an...This study investigates the simplicity and adequacy of tail-based risk measures—value-at-risk(VaR)and expected shortfall(ES)—when applied to tail targeting of the extreme value(EV)model.We implement Lévy-VaR and ES risk measures as full density-based alternatives to the generalized Pareto VaR and the generalized Pareto ES of the tail-targeting EV model.Using data on futures contracts of S&P500,FTSE100,DAX,Hang Seng,and Nikkei 225 during the Global Financial Crisis of 2007-2008,we find that the simplicity of tail-based risk management with a tail-targeting EV model is more attractive.However,the performance of EV risk estimates is not necessarily superior to that of full density-based relatively complex Lévy risk estimates,which may not always give us more robust VaR and ES results,making the model inadequate from a practical perspective.There is randomness in the estimation performances under both approaches for different data ranges and coverage levels.Such mixed results imply that banks,financial institutions,and policymakers should find a way to compromise or trade-off between“simplicity”and user-defined“adequacy”.展开更多
文摘This study investigates the simplicity and adequacy of tail-based risk measures—value-at-risk(VaR)and expected shortfall(ES)—when applied to tail targeting of the extreme value(EV)model.We implement Lévy-VaR and ES risk measures as full density-based alternatives to the generalized Pareto VaR and the generalized Pareto ES of the tail-targeting EV model.Using data on futures contracts of S&P500,FTSE100,DAX,Hang Seng,and Nikkei 225 during the Global Financial Crisis of 2007-2008,we find that the simplicity of tail-based risk management with a tail-targeting EV model is more attractive.However,the performance of EV risk estimates is not necessarily superior to that of full density-based relatively complex Lévy risk estimates,which may not always give us more robust VaR and ES results,making the model inadequate from a practical perspective.There is randomness in the estimation performances under both approaches for different data ranges and coverage levels.Such mixed results imply that banks,financial institutions,and policymakers should find a way to compromise or trade-off between“simplicity”and user-defined“adequacy”.
