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High volatility, thick tails and extreme value theory in value-at-risk estimation

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  • Gencay, Ramazan
  • Selcuk, Faruk
  • Ulugulyagci, Abdurrahman

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Bibliographic Info

Article provided by Elsevier in its journal Insurance: Mathematics and Economics.

Volume (Year): 33 (2003)
Issue (Month): 2 (October)
Pages: 337-356

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Handle: RePEc:eee:insuma:v:33:y:2003:i:2:p:337-356

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Web page: http://www.elsevier.com/locate/inca/505554

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References

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  1. 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, Elsevier, vol. 7(3-4), pages 271-300, November.
  2. Benoit Mandelbrot, 1963. "New Methods in Statistical Economics," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 71, pages 421.
  3. Loretan, Mico & Phillips, Peter C. B., 1994. "Testing the covariance stationarity of heavy-tailed time series: An overview of the theory with applications to several financial datasets," Journal of Empirical Finance, Elsevier, Elsevier, vol. 1(2), pages 211-248, January.
  4. Danielsson, Jon & Morimoto, Yuji, 2000. "Forecasting Extreme Financial Risk: A Critical Analysis of Practical Methods for the Japanese Market," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, Institute for Monetary and Economic Studies, Bank of Japan, vol. 18(2), pages 25-48, December.
  5. Michel Dacorogna & Höskuldur Ari Hauksson & Thomas Domenig & Ulrich Müller & Gennady Samorodnitsky, 2001. "Multivariate extremes, aggregation and risk estimation," CeNDEF Workshop Papers, January 2001, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance P2, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, Econometric Society, vol. 59(2), pages 347-70, March.
  7. Koedijk, C.G. & Schafgans, M.M.A. & Vries, C.G. de, 1990. "The tail index of exchange rate returns," Open Access publications from Tilburg University, Tilburg University urn:nbn:nl:ui:12-3108722, Tilburg University.
  8. Levich, Richard M., 1985. "Empirical studies of exchange rates: Price behavior, rate determination and market efficiency," Handbook of International Economics, Elsevier, in: R. W. Jones & P. B. Kenen (ed.), Handbook of International Economics, edition 1, volume 2, chapter 19, pages 979-1040 Elsevier.
  9. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, Econometric Society, vol. 50(4), pages 987-1007, July.
  10. Mussa, Michael, 1979. "Empirical regularities in the behavior of exchange rates and theories of the foreign exchange market," Carnegie-Rochester Conference Series on Public Policy, Elsevier, Elsevier, vol. 11(1), pages 9-57, January.
  11. Hols, Martien C A B & de Vries, Casper G, 1991. "The Limiting Distribution of Extremal Exchange Rate Returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 6(3), pages 287-302, July-Sept.
  12. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2001. "Dangers of data mining: The case of calendar effects in stock returns," Journal of Econometrics, Elsevier, Elsevier, vol. 105(1), pages 249-286, November.
  13. Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 36, pages 394.
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Cited by:
  1. 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, Elsevier, vol. 22(2), pages 283-300.
  2. Ana-Maria Gavril, 2009. "Exchange Rate Risk: Heads or Tails," Advances in Economic and Financial Research - DOFIN Working Paper Series, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB 35, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
  3. He, Kaijian & Lai, Kin Keung & Yen, Jerome, 2011. "Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach," Energy Economics, Elsevier, Elsevier, vol. 33(5), pages 903-911, September.
  4. Haque, Mahfuzul & Varela, Oscar & Hassan, M. Kabir, 2007. "Safety-first and extreme value bilateral U.S.-Mexican portfolio optimization around the peso crisis and NAFTA in 1994," The Quarterly Review of Economics and Finance, Elsevier, Elsevier, vol. 47(3), pages 449-469, July.
  5. Sasa Zikovic & Randall Filer, 2009. "Hybrid Historical Simulation VaR and ES: Performance in Developed and Emerging Markets," CESifo Working Paper Series, CESifo Group Munich 2820, CESifo Group Munich.
  6. He, Kaijian & Wang, Lijun & Zou, Yingchao & Lai, Kin Keung, 2014. "Value at risk estimation with entropy-based wavelet analysis in exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 408(C), pages 62-71.
  7. Cifter, Atilla, 2011. "Value-at-risk estimation with wavelet-based extreme value theory: Evidence from emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 390(12), pages 2356-2367.
  8. Kaijian He & Kin Keung Lai & Guocheng Xiang, 2012. "Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach," Energies, MDPI, Open Access Journal, vol. 5(4), pages 1018-1043, April.
  9. Zuoxiang, Peng & Miaomiao, Liu & Nadarajah, Saralees, 2010. "Asymptotic expansions for the location invariant moment-type estimator," Mathematics and Computers in Simulation (MATCOM), Elsevier, Elsevier, vol. 80(5), pages 982-998.
  10. Saša ŽIKOVIÆ & Randall K. FILER, 2013. "Ranking of VaR and ES Models: Performance in Developed and Emerging Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, Charles University Prague, Faculty of Social Sciences, vol. 63(4), pages 327-359, August.
  11. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area 99, Bank of Italy, Economic Research and International Relations Area.
  12. Sofiane Aboura, 2014. "When the U.S. Stock Market Becomes Extreme?," Risks, MDPI, Open Access Journal, MDPI, Open Access Journal, vol. 2(2), pages 211-225, May.
  13. Ozun, Alper & Cifter, Atilla & Yilmazer, Sait, 2007. "Filtered Extreme Value Theory for Value-At-Risk Estimation," MPRA Paper 3302, University Library of Munich, Germany.
  14. Marimoutou, Velayoudoum & Raggad, Bechir & Trabelsi, Abdelwahed, 2009. "Extreme Value Theory and Value at Risk: Application to oil market," Energy Economics, Elsevier, Elsevier, vol. 31(4), pages 519-530, July.
  15. Singh, Abhay K. & Allen, David E. & Robert, Powell J., 2013. "Extreme market risk and extreme value theory," Mathematics and Computers in Simulation (MATCOM), Elsevier, Elsevier, vol. 94(C), pages 310-328.
  16. Mapa, Dennis S. & Suaiso, Oliver Q., 2009. "Measuring market risk using extreme value theory," MPRA Paper 21246, University Library of Munich, Germany.
  17. Vêlayoudom Marimoutou & Bechir Raggad & Abdelwahed Trabelsi, 2006. "Extreme Value Theory and Value at Risk : Application to Oil Market," Working Papers, HAL halshs-00410746, HAL.
  18. Bi, Guang & Giles, David E., 2009. "Modelling the financial risk associated with U.S. movie box office earnings," Mathematics and Computers in Simulation (MATCOM), Elsevier, Elsevier, vol. 79(9), pages 2759-2766.
  19. Dimitrakopoulos, Dimitris N. & Kavussanos, Manolis G. & Spyrou, Spyros I., 2010. "Value at risk models for volatile emerging markets equity portfolios," The Quarterly Review of Economics and Finance, Elsevier, Elsevier, vol. 50(4), pages 515-526, November.
  20. Lin, Jin-Guan & Huang, Chao & Zhuang, Qing-Yun & Zhu, Li-Ping, 2010. "Estimating generalized state density of near-extreme events and its applications in analyzing stock data," Insurance: Mathematics and Economics, Elsevier, Elsevier, vol. 47(1), pages 13-20, August.

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