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Spectral Risk Measures: Properties and Limitations

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Author Info

  • Kevin Dowd

    ()

  • John Cotter

    ()

  • Ghulam Sorwar

    ()

Abstract

Spectral risk measures (SRMs) are risk measures that take account of user riskaversion, but to date there has been little guidance on the choice of utility function underlying them. This paper addresses this issue by examining alternative approaches based on exponential and power utility functions. A number of problems are identified with both types of spectral risk measure. The general lesson is that users of spectral risk measures must be careful to select utility functions that fit the features of the particular problems they are dealing with, and should be especially careful when using power SRMs.

(This abstract was borrowed from another version of this item.)

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File URL: http://hdl.handle.net/10.1007/s10693-008-0035-6
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Bibliographic Info

Article provided by Springer in its journal Journal of Financial Services Research.

Volume (Year): 34 (2008)
Issue (Month): 1 (August)
Pages: 61-75

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Handle: RePEc:kap:jfsres:v:34:y:2008:i:1:p:61-75

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Web page: http://www.springerlink.com/link.asp?id=102934

Related research

Keywords: Coherent risk measures; Spectral risk measures; Exponential utility; Power utility; G15;

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  1. Cotter, John & Dowd, Kevin, 2006. "Extreme spectral risk measures: An application to futures clearinghouse margin requirements," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3469-3485, December.
  2. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
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Cited by:
  1. 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.
  2. Marcin Fałdziński & Magdalena Osińska & Tomasz Zdanowicz, 2012. "Detecting Risk Transfer in Financial Markets using Different Risk Measures," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(1), pages 45-64, March.

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