Managing Extreme Risks in Tranquil and Volatile Markets Using Conditional Extreme Value Theory
No 2001:18, Working Papers from Lund University, Department of Economics
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 (search for similar items in EconPapers)
JEL-codes: C22 C53 G19 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-fmk and nep-ias
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Published in International Review of Financial Analysis, 2004, pages 133-152.
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Journal Article: Managing extreme risks in tranquil and volatile markets using conditional extreme value theory (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:lunewp:2001_018
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