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Value-at-Risk Analysis of Stock Returns Historical Simulation,Variance Techniques or Tail Index Estimation?

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Author Info

  • R.W.J. van den Goorbergh
  • P.J.G. Vlaar

Abstract

In this paper various Value-at-Risk techniques are applied to the Dutch stock market index AEX and to the Dow Jones Industrial Average. The main conclusion are: (1) Changing volatility over time is the most important characteristic of stock returns when modelling value-at-risk; (2) For low confidence levels, the fat tails of the distribution can best be mod- eled by means of the t-distribution; (3) Tail index estimators are not successful, due to the fact that they can not cope with the volatility clustering phenomenon.

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File URL: http://www.dnb.nl/binaries/sr040_tcm46-146818.pdf
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Bibliographic Info

Paper provided by Netherlands Central Bank in its series DNB Staff Reports (discontinued) with number 40.

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Length: 39 pages
Date of creation: 1999
Date of revision:
Handle: RePEc:dnb:staffs:40

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Keywords: Value-at-Risk; AEX; Dow Jones; Capital Requirements;

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References

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  1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  2. Vlaar, Peter J G & Palm, Franz C, 1993. "The Message in Weekly Exchange Rates in the European Monetary System: Mean Reversion, Conditional Heteroscedasticity, and Jumps," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 351-60, July.
  3. R.W.J. van den Goorbergh, 1999. "Value-at-Risk and least squares tail index estimation," WO Research Memoranda (discontinued) 578, Netherlands Central Bank, Research Department.
  4. Darryll Hendricks, 1996. "Evaluation of value-at-risk models using historical data," Economic Policy Review, Federal Reserve Bank of New York, issue Apr, pages 39-69.
  5. Jon Danielsson & Casper G. de Vries, 1998. "Beyond the Sample: Extreme Quantile and Probability Estimation," FMG Discussion Papers dp298, Financial Markets Group.
  6. M.J.B. Hall, 1996. "The amendment to the capital accord to incorporate market risk," BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 49(197), pages 271-277.
  7. Jeffrey A. Frankel, 1993. "On Exchange Rates," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061546, December.
  8. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
  9. de Haan, Laurens & Resnick, Sidney I. & Rootzén, Holger & de Vries, Casper G., 1989. "Extremal behaviour of solutions to a stochastic difference equation with applications to arch processes," Stochastic Processes and their Applications, Elsevier, vol. 32(2), pages 213-224, August.
  10. Vlaar, Peter J. G., 2000. "Value at risk models for Dutch bond portfolios," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1131-1154, July.
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Citations

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Cited by:
  1. R.W.J. van den Goorbergh, 1999. "Value-at-Risk and least squares tail index estimation," WO Research Memoranda (discontinued) 578, Netherlands Central Bank, Research Department.
  2. PICIU, Gabriela Cornelia, 2013. "Internal Rating – An Active Instrument In The Management Of Banking Risks. Case Study Bcr," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 17(2), pages 21-30.
  3. Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
  4. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
  5. GIOT, Pierre, 2000. "Intraday value-at-risk," CORE Discussion Papers 2000045, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  6. Sinha, Pankaj & Agnihotri, Shalini, 2014. "Sensitivity of Value at Risk estimation to NonNormality of returns and Market capitalization," MPRA Paper 56307, University Library of Munich, Germany, revised 26 May 2014.
  7. virginie terraza & stephane mussard, 2007. "New trading risk indexes: application of the shapley value in finance," Economics Bulletin, AccessEcon, vol. 3(25), pages 1-7.
  8. Timotheos Angelidis & Alexandros Benos, 2006. "Liquidity adjusted value-at-risk based on the components of the bid-ask spread," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 835-851.
  9. Piñeiro, J. & Tamazian, A. & Melikyan, David N., 2006. "Consequences of the Euro introduction on Market Risk: An Econometric Evidence from 1995-2004," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 6(2).
  10. Juan Piñeiro Chousa, & Artur Tamazian, & Davit N. Melikyan,, 2008. "MARKET RISK DYNAMICS AND COMPETITIVENESS AFTER THE EURO: Evidence from EMU Members," William Davidson Institute Working Papers Series wp916, William Davidson Institute at the University of Michigan.
  11. Wielhouwer, J.L. & Bams, D., 2001. "Empirical issues in value at risk," Open Access publications from Tilburg University urn:nbn:nl:ui:12-88468, Tilburg University.
  12. Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
  13. Bank for International Settlements, 2000. "Stress Testing by Large Financial Institutions: Current Practice and Aggregation Issues," CGFS Papers, Bank for International Settlements, number 14, January.

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