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Smooth-Transition Regression Models for Non-Stationary Extremes

Author

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  • Julien Hambuckers
  • Thomas Kneib
Abstract
We introduce a smooth-transition generalized Pareto (GP) regression model to study the time-varying dependence structure between extreme losses and a set of economic factors. In this model, the distribution of the loss size is approximated by a GP distribution, and its parameters are related to explanatory variables through regression functions, which themselves depend on a time-varying predictor of structural changes. We use this approach to study the dynamics in the monthly severity distribution of operational losses at a major European bank. Using the VIX as a transition variable, our analysis reveals that when the uncertainty is high, a high number of losses in a recent past are indicative of less extreme losses in the future, consistent with a self-inhibition hypothesis. On the contrary, in times of low uncertainty, only the growth rate of the economy seems to be a relevant predictor of the likelihood of extreme losses.

Suggested Citation

  • Julien Hambuckers & Thomas Kneib, 2023. "Smooth-Transition Regression Models for Non-Stationary Extremes," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 445-484.
    • Handle: RePEc:oup:jfinec:v:21:y:2023:i:2:p:445-484.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbab005
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    More about this item

    Keywords

    extreme value theory; generalized Pareto distribution; operational risk; VIX;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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