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Varying the VaR for unconditional and conditional environments

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  • Cotter, John

Abstract

Accurate forecasting of risk is the key to successful risk management techniques. Using the largest stock index futures from twelve European bourses, this paper presents VaR measures based on their unconditional and conditional distributions for single and multi-period settings. These measures underpinned by extreme value theory are statistically robust explicitly allowing for fat-tailed densities. Conditional tail estimates are obtained by adjusting the unconditional extreme value procedure with GARCH filtered returns. The conditional modelling results in iid returns allowing for the use of a simple and efficient multi-period extreme value scaling law. The paper examines the properties of these distinct conditional and unconditional trading models. The paper finds that the biases inherent in unconditional single and multi-period estimates assuming normality extend to the conditional setting.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of International Money and Finance.

Volume (Year): 26 (2007)
Issue (Month): 8 (December)
Pages: 1338-1354

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Handle: RePEc:eee:jimfin:v:26:y:2007:i:8:p:1338-1354

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Web page: http://www.elsevier.com/locate/inca/30443

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  1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," NBER Working Papers 7488, National Bureau of Economic Research, Inc.
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Cited by:
  1. Karmakar, Madhusudan, 2013. "Estimation of tail-related risk measures in the Indian stock market: An extreme value approach," Review of Financial Economics, Elsevier, vol. 22(3), pages 79-85.
  2. Kevin Dowd & John Cotter, 2011. "Intra-Day Seasonality in Foreign Market Transactions," Working Papers 200746, Geary Institute, University College Dublin.
  3. Christian Francq & Jean-Michel Zakoïan, 2013. "Estimating the Marginal Law of a Time Series With Applications to Heavy-Tailed Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 412-425, October.
  4. Cotter, John & Dowd, Kevin, 2007. "The tail risks of FX return distributions: a comparison of the returns associated with limit orders and market orders," MPRA Paper 3493, University Library of Munich, Germany.
  5. 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.
  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.
  7. John Cotter & Kevin Dowd, 2011. "Spectral Risk Measures with an Application to Futures Clearinghouse Variation Margin Requirements," Working Papers 200616, Geary Institute, University College Dublin.
  8. John Cotter & Kevin Dowd & Wyn Morgan, 2011. "Extreme Measures of Agricultural Financial Risk," Papers 1103.5962, arXiv.org.

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