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Estimating financial risk measures for futures positions: a non-parametric approach

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  • john cotter
  • kevin dowd

Abstract

This paper presents non-parametric estimates of spectral risk measures applied to long and short positions in 5 prominent equity futures contracts. It also compares these to estimates of two popular alternative measures, the Value-at-Risk (VaR) and Expected Shortfall (ES). The spectral risk measures are conditioned on the coefficient of absolute risk aversion, and the latter two are conditioned on the confidence level. Our findings indicate that all risk measures increase dramatically and their estimators deteriorate in precision when their respective conditioning parameter increases. Results also suggest that estimates of spectral risk measures and their precision levels are of comparable orders of magnitude as those of more conventional risk measures. Running head: financial risk measures for futures positions

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File URL: http://arxiv.org/pdf/1103.5666
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Paper provided by arXiv.org in its series Papers with number 1103.5666.

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Date of creation: Mar 2011
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Handle: RePEc:arx:papers:1103.5666

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  1. Hsieh, David A., 1993. "Implications of Nonlinear Dynamics for Financial Risk Management," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(01), pages 41-64, March.
  2. John Cotter, 2011. "Minimum Capital Requirement Calculations for UK Futures," Working Papers 200418, Geary Institute, University College Dublin.
  3. Cotter, JOhn & Dowd, Kevin, 2006. "Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements," MPRA Paper 3505, University Library of Munich, Germany.
  4. Christian Gourieroux & Wei Liu, 2006. "Sensitivity Analysis of Distortion Risk Measures," Working Papers 2006-33, Centre de Recherche en Economie et Statistique.
  5. Acerbi, Carlo, 2002. "Spectral measures of risk: A coherent representation of subjective risk aversion," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1505-1518, July.
  6. Brooks, C. & Clare, A.D. & Dalle Molle, J.W. & Persand, G., 2005. "A comparison of extreme value theory approaches for determining value at risk," Journal of Empirical Finance, Elsevier, vol. 12(2), pages 339-352, March.
  7. Upper, Christian & Werner, Thomas, 2002. "Time variation in the tail behaviour of bunds futures returns," Working Paper Series 0199, European Central Bank.
  8. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
  9. Matthew Pritsker, 1997. "Evaluating Value at Risk Methodologies: Accuracy versus Computational Time," Journal of Financial Services Research, Springer, vol. 12(2), pages 201-242, October.
  10. Broussard, John Paul, 2001. "Extreme-value and margin setting with and without price limits," The Quarterly Review of Economics and Finance, Elsevier, vol. 41(3), pages 365-385.
  11. Song Xi Chen, 2005. "Nonparametric Inference of Value-at-Risk for Dependent Financial Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(2), pages 227-255.
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Cited by:
  1. W├Ąchter, Hans Peter & Mazzoni, Thomas, 2013. "Consistent modeling of risk averse behavior with spectral risk measures," European Journal of Operational Research, Elsevier, vol. 229(2), pages 487-495.

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