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

Gelly Mitrodima and Jaideep Oberoi

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

Keywords: value-at-risk; expected shortfall; CAViaR-type models; component models; long range dependence (search for similar items in EconPapers)
JEL-codes: C50 G11 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2024-01-01
New Economics Papers: this item is included in nep-ecm
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Published in Journal of the Royal Statistical Society. Series C: Applied Statistics, 1, January, 2024, 73(1), pp. 1 - 27. ISSN: 0035-9254

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:120880

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