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Tail expectile-VaR estimation in the semiparametric Generalized Pareto model

Author

Listed:
  • Abbas, Yasser
  • Daouia, Abdelaati
  • Nemouchi, Boutheina
  • Stupfler, Gilles

Abstract

Expectiles have received increasing attention as coherent and elicitable market risk measure. Their estimation from heavy-tailed data in an extreme value framework has been studied using solely the Weissman extrapolation method. We challenge this dominance by developing the theory of two classes of semiparametric Generalized Pareto estimators that make more efficient use of tail observations by incorporating the location, scale and shape extreme value parameters: the first class relies on asymmetric least squares estimation, while the second is based on extreme quantile estimation. A comparison with simulated and real data shows the superiority of our proposals for real-valued profit-loss distributions.

Suggested Citation

  • Abbas, Yasser & Daouia, Abdelaati & Nemouchi, Boutheina & Stupfler, Gilles, 2025. "Tail expectile-VaR estimation in the semiparametric Generalized Pareto model," TSE Working Papers 25-1607, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:130105
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    References listed on IDEAS

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    More about this item

    Keywords

    Expectile; Extreme risk; Generalized Pareto model; Heavy tails; Semiparametric; extrapolation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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