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Managing extreme risks in tranquil and volatile markets using conditional extreme value theory

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  • Bystrom, Hans N. E.

Abstract

Financial risk management typically deals with low probability events in the tails of asset price distributions. In order to capture the behavior of these tails, one should therefore rely on models that explicitly focus on the tails. Extreme value theory (EVT) based models do exactly that, and in this paper we apply both unconditional and conditional EVT models to the management of extreme market risks in stock markets. We find conditional EVT models to give particularly accurate Value-at-Risk measures, and a comparison with traditional (GARCH) approaches to calculate Value-at-Risk demonstrates EVT as being the superior approach both for standard and more extreme Value-at-Risk quantiles.
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Suggested Citation

  • Bystrom, Hans N. E., 2004. "Managing extreme risks in tranquil and volatile markets using conditional extreme value theory," International Review of Financial Analysis, Elsevier, vol. 13(2), pages 133-152.
    • Handle: RePEc:eee:finana:v:13:y:2004:i:2:p:133-152
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G19 - Financial Economics - - General Financial Markets - - - Other

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