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Financial Crisis, VaR Forecasts and the Performance of Time Varying EVT-Copulas

In: Operations Research Proceedings 2012

Author

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  • Theo Berger

    (University of Bremen)

Abstract

We investigate Value-at-Risk (VaR) estimates based on extreme value theory (EVT) models combined with time varying parametric copulas against competing parametric approaches accounting for dynamic conditional correlations feasible to higher order portfolios. Tails of the return distributions are modeled via Generalized Pareto Distribution (GPD) applied to GARCH filtered residuals to capture excess returns, linked via constant and time varying copulas. Drawing on this EVT-GARCH-Copula, we evaluate portfolios consisting of German Stocks, market indices and FX-rates. However, the empirical results support the dynamic EVT-GARCH-Copula approach, as 99 % VaR forecasts clearly outperform parametric estimates stemming from competing dependency approaches.

Suggested Citation

  • Theo Berger, 2014. "Financial Crisis, VaR Forecasts and the Performance of Time Varying EVT-Copulas," Operations Research Proceedings, in: Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), Operations Research Proceedings 2012, edition 127, pages 35-40, Springer.
  • Handle: RePEc:spr:oprchp:978-3-319-00795-3_6
    DOI: 10.1007/978-3-319-00795-3_6
    as

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