Reference : Understanding the Economic Determinants of the Severity of Operational Losses: A regu...
Scientific journals : Article
Business & economic sciences : Quantitative methods in economics & management
http://hdl.handle.net/2268/218423
Understanding the Economic Determinants of the Severity of Operational Losses: A regularized Generalized Pareto Regression Approach
English
Hambuckers, julien mailto [Université de Liège - ULiège > HEC Liège : UER > Statistique appliquée à la gestion et à l'économie >]
Groll, Andreas [> >]
Kneib, Thomas [> >]
2018
Journal of Applied Econometrics
John Wiley & Sons
33
6
898-935
Yes (verified by ORBi)
International
0883-7252
1099-1255
Hoboken
United States
[en] Generalized Pareto distribution ; operational losses ; model selection ; penalized likelihood ; compound process ; VIX
[en] We investigate a novel database of 10,217 extreme operational losses from the Italian bank UniCredit, covering a period of 10 years and 7 different event types. Our goal is to shed light on the dependence between the severity distribution of these losses and a set of macroeconomic, financial and firm-specific factors. To do so, we use Generalized Pareto regression techniques, where both the scale and shape parameters are assumed to be functions of these explanatory variables. In this complex distributional regression framework, we perform the selection of the relevant covariates with a state-of-the-art penalized-likelihood estimation procedure relying on $L_{1}$-norm penalty terms of the coefficients. A simulation study indicates that this approach efficiently selects covariates of interest and tackles spurious regression issues encountered when dealing with integrated time series. The results of our empirical analysis have important implications in terms of risk management and regulatory policy. In particular, we found that high Italian unemployment rate and low GDP growth rate in the European Union are associated with smaller probabilities of extreme severities, whereas high values of the VIX and high growth rates of housing prices are associated with more extreme losses. Looking at firm-specific factors, low leverage ratio and high deposit growth rate are associated with a higher likelihood of extreme losses. Lastly, we illustrate the impact of different economic scenarios on the requested capital for operational risk. We find important discrepancies across event types and scenarios.
Professionals ; General public
http://hdl.handle.net/2268/218423
10.1002/jae.2638

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