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CAViaR models for Value-at-Risk and Expected Shortfall with long range dependency features

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  • Mitrodima, Gelly
  • Oberoi, Jaideep

Abstract

We consider alternative specifications of conditional autoregressive quantile models to estimate Value-at-Risk and Expected Shortfall. The proposed specifications include a slow moving component in the quantile process, along with aggregate returns from heterogeneous horizons as regressors. Using data for 10 stock indices, we evaluate the performance of the models and find that the proposed features are useful in capturing tail dynamics better.

Suggested Citation

  • Mitrodima, Gelly & Oberoi, Jaideep, 2024. "CAViaR models for Value-at-Risk and Expected Shortfall with long range dependency features," LSE Research Online Documents on Economics 120880, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:120880
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    File URL: http://eprints.lse.ac.uk/120880/
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    References listed on IDEAS

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    More about this item

    Keywords

    value-at-risk; expected shortfall; CAViaR-type models; component models; long range dependence;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    NEP fields

    This paper has been announced in the following NEP Reports:

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