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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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Bibliographic Info

Article provided by Elsevier in its journal International Review of Financial Analysis.

Volume (Year): 13 (2004)
Issue (Month): 2 ()
Pages: 133-152

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Handle: RePEc:eee:finana:v:13:y:2004:i:2:p:133-152

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Web page: http://www.elsevier.com/locate/inca/620166

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References

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  1. Francis X. Diebold & Til Schuermann & John D. Stroughair, 1998. "Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-081, New York University, Leonard N. Stern School of Business-.
  2. Evis Këllezi & Manfred Gilli, 2000. "Extreme Value Theory for Tail-Related Risk Measures," FAME Research Paper Series rp18, International Center for Financial Asset Management and Engineering.
  3. Poon, Ser-Huang & Taylor, Stephen J., 1992. "Stock returns and volatility: An empirical study of the UK stock market," Journal of Banking & Finance, Elsevier, vol. 16(1), pages 37-59, February.
  4. Baillie, R.T. & Degennaro, R.P., 1988. "Stock Returns And Volatility," Papers 8803, Michigan State - Econometrics and Economic Theory.
  5. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
  6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  7. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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Cited by:
  1. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
  2. Brännäs, Kurt & Quoreshi, Shahiduzzaman & Simonsen, Ola, 2002. "Extreme-Value Characteristics in Daily Time Series of Swedish Stock Returns," UmeÃ¥ Economic Studies 597, Umeå University, Department of Economics.
  3. Chia-Lin Chang & Lydia González-Serrano & Juan-Ángel Jiménez-Martín, 2012. "Currency Hedging Strategies Using Dynamic Multivariate GARCH," Documentos del Instituto Complutense de Análisis Económico 2012-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, revised Feb 2012.
  4. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
  5. Fong Chan, Kam & Gray, Philip, 2006. "Using extreme value theory to measure value-at-risk for daily electricity spot prices," International Journal of Forecasting, Elsevier, vol. 22(2), pages 283-300.
  6. Marimoutou, Velayoudoum & Raggad, Bechir & Trabelsi, Abdelwahed, 2009. "Extreme Value Theory and Value at Risk: Application to oil market," Energy Economics, Elsevier, vol. 31(4), pages 519-530, July.
  7. Stavros Degiannakis & Christos Floros & Alexandra Livada, 2012. "Evaluating value-at-risk models before and after the financial crisis of 2008: International evidence," Managerial Finance, Emerald Group Publishing, vol. 38(3), pages 436-452, March.
  8. Paulo Araújo Santos & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "GFC-Robust Risk Management Under the Basel Accord Using Extreme Value Methodologies," Working Papers in Economics 11/28, University of Canterbury, Department of Economics and Finance.

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