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A DARE for VaR

Author

Listed:
  • Benjamin Hamidi
  • Christophe Hurlin
  • Patrick Kouontchou
  • Bertrand Maillet

Abstract

This paper introduces a new class of models for the Value-at-Risk (VaR) and Expected Shortfall (ES), called the Dynamic AutoRegressive Expectiles (DARE) models. Our approach is based on a weighted average of expectile-based VaR and ES models, i.e. the Conditional Autoregressive Expectile (CARE) models introduced by Taylor (2008a) and Kuan et al. (2009). First, we briefly present the main non-parametric, parametric and semi-parametric estimation methods for VaR and ES. Secondly, we detail the DARE approach and show how the expectiles can be used to estimate quantile risk measures. Thirdly, we use various backtesting tests to compare the DARE approach to other traditional methods for computing VaR forecasts on the French stock market. Finally, we evaluate the impact of several conditional weighting functions and determine the optimal weights in order to dynamically select the more relevant global quantile model.

Suggested Citation

  • Benjamin Hamidi & Christophe Hurlin & Patrick Kouontchou & Bertrand Maillet, 2015. "A DARE for VaR," Finance, Presses universitaires de Grenoble, vol. 36(1), pages 7-38.
    • Handle: RePEc:cai:finpug:fina_361_0007
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    Other versions of this item:

    • Benjamin Hamidi & Christophe Hurlin & Patrick Kouontchou & Bertrand Maillet, 2015. "A DARE for VaR," Post-Print hal-01243402, HAL.
    • Benjamin Hamidi & Christophe Hurlin & Patrick Kouontchou & Bertrand Maillet, 2015. "A DARE for VaR," Post-Print hal-02312327, HAL.

    Citations

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    Cited by:

    1. David Happersberger & Harald Lohre & Ingmar Nolte, 2020. "Estimating portfolio risk for tail risk protection strategies," European Financial Management, European Financial Management Association, vol. 26(4), pages 1107-1146, September.
    2. Bonaccolto, Giovanni & Caporin, Massimiliano & Maillet, Bertrand B., 2022. "Dynamic large financial networks via conditional expected shortfalls," European Journal of Operational Research, Elsevier, vol. 298(1), pages 322-336.
    3. Bayer, Sebastian, 2018. "Combining Value-at-Risk forecasts using penalized quantile regressions," Econometrics and Statistics, Elsevier, vol. 8(C), pages 56-77.

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