Paper of the year: Bakhodir Ergashev, Stefan Mittnik and Evan Sekeris
Scarcity of applicable data is a perennial problem for modelling op risk losses. Bayesian estimation is a far from universally accepted technique – but Bakhodir Ergashev, Stefan Mittnik and Evan Sekeris describe a way to make it work in this year’s Paper of the Year
Paper: A Bayesian Approach to Extreme Value Estimation in Operational Risk Modelling
Scarcity of data is the ever-present bugbear of everyone who deals with operational risk – in particular the shortage of relevant data points in the tails of loss distributions, which are not only crucial for planning responses to extreme and business-threatening events, but also important in operational risk modelling and capital calculations.
The tail is critical: observed operational risk losses fall into a
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