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

Cotter, John and Dowd, Kevin (2007): Estimating financial risk measures for futures positions: a non-parametric approach. Unpublished.

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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.

Item Type:MPRA Paper
Institution:University College Dublin
Language:English
Subjects:G - Financial Economics > G1 - General Financial Markets > G10 - General
G - Financial Economics > G0 - General > G00 - General
ID Code:3503
Deposited By:John Cotter
Deposited On:12. Jun 2007
Last Modified:07. Nov 2007 03:14
References:

Acerbi, C., 2002, Spectral measures of risk: a coherent representation of subjective risk aversion, Journal of Banking and Finance, 26, 1505-1518. Acerbi, C., 2004, Coherent representations of subjective risk-aversion, Pp. 147-207 in G. Szego (Ed,) Risk Measures for the 21st Century, (Wiley: New York). Artzner, P., F. Delbaen, J.-M. Eber, and D. Heath, 1999, Coherent measures of risk, Mathematical Finance, 9, 203-228. Broussard, J. P. 2001. Extreme-value and margin setting with and without price limits, Quarterly Review of Economics and Finance, 41, 365-385. Brooks, C., A. D. Clare, J. W. Dalle Molle and G. Persand, 2005, A comparison of extreme value theory approaches for determining value at risk, Journal of Empirical Finance, 12, 339-352. Butler, J. S., and B. Schachter, 1998, Estimating Value at Risk with a precision measure by combining kernel estimation with historical simulation, Review of Derivatives Research, 1, 371-390. Chen, S. X., and C. Y. Tang, 2005, Nonparametric inference of value at risk for dependent financial returns, Journal of Financial Econometrics, 3, 227-255. Cotter J., 2004, Minimum Capital Requirement Calculations for UK Futures, Journal of Futures Markets, 24, 193-220. Cotter, J., and K. Dowd, 2006, Extreme quantile-based risk measures: an application to futures clearinghouse margin requirements, Journal of Banking and Finance, 30, 3469-3485. 19 Davison, A. C., and D. V. Hinkley, 1997, Bootstrap Methods and their Applications. Cambridge: Cambridge University Press. Dowd, K., 2001, Estimating VaR with order statistics, Journal of Derivatives, 8, 23- 30. Efron, B., and R. J. Tibshirani, 1993, An Introduction to the Bootstrap, (Chapman and Hall, New York). Giannopoulos, K., and R. Tunaru, 2004, Coherent risk measures under filtered historical simulation, Journal of Banking and Finance, 29, 979-996. Gourieroux, C., and W. Liu, 2006, Sensitivity analysis of distortion risk measures, mimeo, University of Toronto. Grootveld, H., and W. G. Hallerbach, 2004, Upgrading value-at-risk from diagnostic metric to decision variable: a wise thing to do? Pp, 33-50 in G, Szegö (Ed,) Risk Measures for the 21st Century, (Wiley: New York). Hsieh D.A., 1993. Implications of Nonlinear Dynamics for Financial Risk Management, Journal of Financial and Quantitative Analysis, 28, 41-64. London Clearing House, 2002, Market Protection, London: LCH. Longin, F., 2001, Beyond the VaR, Journal of Derivatives, 8, 36-48. Pritzker, M., 1997, Evaluating value at risk methodologies: accuracy versus computational time, Journal of Financial Services Research, 12, 201-242. Werner, T., and C. Upper, 2004, Time variation in the tail behavior of Bund futures returns, Journal of Futures Markets, 24, 387-398. Yamai, Y., and T. Yoshiba, 2002, Comparative analyses of expected shortfall and value-at-risk: their estimation error, decomposition, and optimization, Monetary and Economic Studies, January, 87-122.

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