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Extreme Returns, Tail Estimation, and Value-at-Risk

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  • Jon Danielsson

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Abstract

Accurate prediction of extreme events are of primary importance in many financial applications. The properties of historical simulation and Risk Metrics techniques for computing Valu-at Risk (VaR) are compared with a method which involves modelling the tails of financial returns explicitly with a tail estimator. The methods are compared using a sample of U.S. stock returns. For predictions of low probability worst outcomes, RiskMetrics type analysis underpredicts while historical simulation overpredicts. However, the estimates obtained from applying the tail estimator are more accurate in the VaR prediction. This implies that capital requirements can be lower by doing VaR with the tail estimator.

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File URL: http://www.lse.ac.uk/fmg/workingPapers/discussionPapers/fmg_pdfs/dp273.pdf
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Bibliographic Info

Paper provided by Financial Markets Group in its series FMG Discussion Papers with number dp273.

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Date of creation: Jul 1997
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Handle: RePEc:fmg:fmgdps:dp273

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Web page: http://www.lse.ac.uk/fmg/

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Cited by:
  1. Straetmans, Stefan, 2000. "Extremal spillovers in financial markets," Serie Research Memoranda 0013, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  2. Peter F. Christoffersen & Francis X. Diebold, 1998. "How Relevant is Volatility Forecasting for Financial Risk Management?," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-080, New York University, Leonard N. Stern School of Business-.
  3. Xiongwei Ju & Neil D. Pearson, 1998. "Using Value-at-Risk to Control Risk Taking: How Wrong Can you Be?," Finance 9810002, EconWPA.
  4. Agata Gemzik-Salwach, 2012. "The Use Of A Value At Risk Measure For The Analysis Of Bank Interest Margins," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 8(4), pages 15-29, February.

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