Working Papers,
Lund University, Department of Economics

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.

Keywords: Value-at-Risk; conditional extreme value theory; GARCH; backtesting

JEL-codes: C22; C53; G19

23 pages, October 15, 2001

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Published as

Hans Byström, (2004), 'Managing Extreme Risks in Tranquil and Volatile Markets Using Conditional Extreme Value Theory', International Review of Financial Analysis, vol 13, no 2, pages 133-152

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