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

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  • Cotter, John
  • Dowd, Kevin

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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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 3503.

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Date of creation: 2007
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Handle: RePEc:pra:mprapa:3503

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  1. Upper, Christian & Werner, Thomas, 2002. "Time variation in the tail behaviour of bunds futures returns," Working Paper Series, European Central Bank 0199, European Central Bank.
  2. Broussard, John Paul, 2001. "Extreme-value and margin setting with and without price limits," The Quarterly Review of Economics and Finance, Elsevier, Elsevier, vol. 41(3), pages 365-385.
  3. Acerbi, Carlo, 2002. "Spectral measures of risk: A coherent representation of subjective risk aversion," Journal of Banking & Finance, Elsevier, Elsevier, vol. 26(7), pages 1505-1518, July.
  4. John Cotter, 2011. "Minimum Capital Requirement Calculations for UK Futures," Working Papers, Geary Institute, University College Dublin 200418, Geary Institute, University College Dublin.
  5. John Cotter & Kevin Dowd, 2011. "Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements," Papers 1103.5653, arXiv.org.
  6. Hsieh, David A., 1993. "Implications of Nonlinear Dynamics for Financial Risk Management," Journal of Financial and Quantitative Analysis, Cambridge University Press, Cambridge University Press, vol. 28(01), pages 41-64, March.
  7. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, Wiley Blackwell, vol. 9(3), pages 203-228.
  8. 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, Elsevier, vol. 12(2), pages 339-352, March.
  9. 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.
  10. Matthew Pritsker, 1997. "Evaluating Value at Risk Methodologies: Accuracy versus Computational Time," Journal of Financial Services Research, Springer, Springer, vol. 12(2), pages 201-242, October.
  11. Christian Gourieroux & Wei Liu, 2006. "Sensitivity Analysis of Distortion Risk Measures," Working Papers, Centre de Recherche en Economie et Statistique 2006-33, Centre de Recherche en Economie et Statistique.
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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, Elsevier, vol. 229(2), pages 487-495.

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