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A robust VaR model under different time periods and weighting schemes

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Author Info

  • Timotheos Angelidis

    ()

  • Alexandros Benos

    ()

  • Stavros Degiannakis

    ()

Abstract

This paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by using non parametric, semi parametric and parametric methods. In order to choose one model among the various forecasting methods, a two-stage backtesting procedure is implemented. In the first stage the unconditional coverage test is used to examine the statistical accuracy of the models. In the second stage a loss function is applied to investigate whether the differences between the models, that calculated accurately the VaR, are statistically significant. Under this framework, the combination of a parametric model with the historical simulation produced robust results across the sample periods, market capitalization schemes, trading positions and confidence levels and therefore there is a risk measure that is reliable. Copyright Springer Science+Business Media, LLC 2007

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File URL: http://hdl.handle.net/10.1007/s11156-006-0010-y
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Bibliographic Info

Article provided by Springer in its journal Review of Quantitative Finance and Accounting.

Volume (Year): 28 (2007)
Issue (Month): 2 (February)
Pages: 187-201

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Handle: RePEc:kap:rqfnac:v:28:y:2007:i:2:p:187-201

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Web page: http://springerlink.metapress.com/link.asp?id=102990

Related research

Keywords: Asymmetric power ARCH; Backtesting; Extreme value theory; Filtered historical simulation; Value-at-risk;

References

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Citations

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Cited by:
  1. Gabrielsen, A. & Zagaglia, Paolo & Kirchner, A. & Liu, Z., 2012. "Forecasting Value-at-Risk with time-varying variance, skewness and kurtosis in an exponential weighted moving average framework," MPRA Paper 39294, University Library of Munich, Germany.
  2. Chee Lim & Patricia Tan, 2007. "Value relevance of value-at-risk disclosure," Review of Quantitative Finance and Accounting, Springer, vol. 29(4), pages 353-370, November.
  3. 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.
  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. Chrétien, Stéphane & Coggins, Frank, 2010. "Performance and conservatism of monthly FHS VaR: An international investigation," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 323-333, December.
  6. Trenca Ioan & Zoicas-Ienciu Adrian, 2010. "The Correlation Between The Market Risk And The Liquidity Risk In The Romanian Banking Sector," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 437-442, July.

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