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Estimating financial risk measures for futures positions: A nonparametric approach

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  • John Cotter
  • Kevin Dowd

Abstract

This study presents nonparametric estimates of spectral risk measures (SRM) applied to long and short positions in five prominent equity futures contracts. It also compares these to estimates of two popular alternative measures, the Value‐at‐Risk and Expected Shortfall. The SRMs 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 SRMs and their precision levels are of comparable orders of magnitude as those of more conventional risk measures. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:689–703, 2010

Suggested Citation

  • John Cotter & Kevin Dowd, 2010. "Estimating financial risk measures for futures positions: A nonparametric approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(7), pages 689-703, July.
  • Handle: RePEc:wly:jfutmk:v:30:y:2010:i:7:p:689-703
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    Cited by:

    1. Lima Miquelluti, Daniel & Ozaki, Vitor & Miquelluti, David J., 2020. "An application of geographically weighted quantile LASSO to weather index insurance design," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304288, Agricultural and Applied Economics Association.
    2. Mitra, Sovan, 2017. "Efficient option risk measurement with reduced model risk," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 163-174.
    3. Wächter, 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.
    4. Mario Brandtner, 2016. "Spektrale Risikomaße: Konzeption, betriebswirtschaftliche Anwendungen und Fallstricke," Management Review Quarterly, Springer, vol. 66(2), pages 75-115, April.
    5. Brandtner, Mario & Kürsten, Wolfgang, 2014. "Decision making with Conditional Value-at-Risk and spectral risk measures: The problem of comparative risk aversion," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100615, Verein für Socialpolitik / German Economic Association.
    6. Mario Brandtner, 2016. "“Spectral Risk Measures: Properties and Limitations”: Comment on Dowd, Cotter, and Sorwar," Journal of Financial Services Research, Springer;Western Finance Association, vol. 49(1), pages 121-131, February.
    7. Mozumder, Sharif & Choudhry, Taufiq & Dempsey, Michael, 2018. "Spectral measures of risk for international futures markets: A comparison of extreme value and Lévy models," Global Finance Journal, Elsevier, vol. 37(C), pages 248-261.
    8. Brandtner, Mario & Kürsten, Wolfgang, 2015. "Decision making with Expected Shortfall and spectral risk measures: The problem of comparative risk aversion," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 268-280.

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    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G00 - Financial Economics - - General - - - General

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