Managing extreme risks in tranquil and volatile markets using conditional extreme value theory
AbstractFinancial 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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Bibliographic InfoArticle provided by Elsevier in its journal International Review of Financial Analysis.
Volume (Year): 13 (2004)
Issue (Month): 2 ()
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Web page: http://www.elsevier.com/locate/inca/620166
Other versions of this item:
- Byström, Hans, 2001. "Managing Extreme Risks in Tranquil and Volatile Markets Using Conditional Extreme Value Theory," Working Papers 2001:18, Lund University, Department of Economics.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G19 - Financial Economics - - General Financial Markets - - - Other
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