Skip to main content
Log in

First and Second Order Asymptotics of the Spectral Risk Measure for Portfolio Loss Under Multivariate Regular Variation

  • Published:
Journal of Systems Science and Complexity Aims and scope Submit manuscript

Abstract

In the context of multivariate regular variation, the authors establish the first-order asymptotics of the spectral risk measure of portfolio loss. Furthermore, by the notion of second-order regular variation, the second-order asymptotics of the spectral risk measure of portfolio loss is also presented. In order to illustrate the derived results, a numerical example with Monte Carlo simulation is carried out.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Artzner P, Delbaen F, Eber J M, et al., Thinking coherently, Risk, 1997, 10(11): 68–71.

    Google Scholar 

  2. Acerbi C, Spectral measures of risk: A coherent representation of subjective risk aversion, Journal of Banking & Finance, 2002, 26: 1505–1518.

    Article  Google Scholar 

  3. Acerbi C, Coherent representations of subjective risk aversion, Risk Measures for the 21st Century, Ed. by Szegö G, Wiely, New York, 2004.

    Google Scholar 

  4. Cotter J and Dowd K, Extreme spectral risk measures: An application to futures clearinghouse margin requirements, Journal of Banking & Finance, 2006, 30: 3469–3485.

    Article  Google Scholar 

  5. Dowd K, Cotter J, and Sorwar G, Spectral risk measures: Properties and limitations, Journal of Financial Services Research, 2008, 34(1): 61–75.

    Article  Google Scholar 

  6. Brandtner M, “Spectral risk measures: Properties and limitations”: Comment on dowd, cotter, and sorwar, Journal of Financial Services Research, 2016, 49: 121–131.

    Article  Google Scholar 

  7. Yan Z and Zhang J, Adjusted empirical likelihood for value at risk and expected shortfall, Communications in Statistics — Theory and Methods, 2017, 46(5): 2580–2591.

    Article  MathSciNet  Google Scholar 

  8. Xing G and Gan X, Asymptotic analysis of tail distortion risk measure under the framework of multivariate regular variation, Communications in Statistics — Theory and Methods, 2020, 49(12): 2931–2941.

    Article  MathSciNet  Google Scholar 

  9. Zhu L and Li H, Asymptotic analysis in multivariate tail conditional expectations, North American Actuarial Journal, 2012, 16(3): 350–363.

    Article  MathSciNet  Google Scholar 

  10. de Haan L and Stadtmüller U, Generalized regular variation of second order, Journal of the Australian Mathematical Society, 1996, 61(3): 381–395.

    Article  MathSciNet  Google Scholar 

  11. de Haan L and Ferreira A, Extreme Value Theory, Springer Series in Operations Research and Financial Engineering, Springer, New York, 2006.

    Book  Google Scholar 

  12. Geluk J, de Haan L, Resnick S, et al., Second-order regular variation, convolution and the central limit theorem, Stochastic Processes and Their Applications, 1997, 69(2): 139–159.

    Article  MathSciNet  Google Scholar 

  13. Hua L and Joe H, Second order regular variation and conditional tail expectation of multiple risks, Insurance: Mathmatics and Economics, 2011, 49: 537–546.

    MathSciNet  MATH  Google Scholar 

  14. Basrak B, Davis R A, and Mikosch T, A characterization of multivariate regular variation, Annals of Applied Probability, 2002, 12(3): 908–920.

    Article  MathSciNet  Google Scholar 

  15. Bingham N H, Goldie C M, and Teugels J L, Regular Variation, Volume 27 of Encyclopedia of Mathematics and Its Applications, Cambridge University Press, Cambridge, 1987.

    Google Scholar 

  16. Resnick S I, Extreme Values, Regular Variation, and Point Processes, Volume 4 of Applied Probability, A Series of the Applied Probability Trust, Springer-Verlag, New York, 1987.

    Book  Google Scholar 

  17. Mikosch T, Modeling Dependence and Tails of Financial Time Series, C&H/CRC Monographs on Statistics & Applied Probability, Chapman and Hall/CRC, 2003.

  18. Hult H and Lindskog F, Multivariate extremes, aggregation and dependence in elliptical distributions, Advances in Applied Probability, 2002, 34(3): 587–608.

    Article  MathSciNet  Google Scholar 

  19. Resnick S I, Heavy-Tail Phenomena, Springer Series in Operations Research and Financial Engineering, Springer, New York, 2007.

    Google Scholar 

  20. Mainik G, On asymptotic diversification effects for heavy-tailed risks, Doctor’s degree thesis, University of Freiburg, Freiburg, 2010.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guodong Xing.

Additional information

This research was supported by the Important Natural Science Foundation of Colleges and Universities of Anhui Province under Grant No. KJ2020A0122 and the Scientific Research Start-up Foundation of Hefei Normal University.

This paper was recommended for publication by Editor WANG Shouyang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xing, G., Yang, S. First and Second Order Asymptotics of the Spectral Risk Measure for Portfolio Loss Under Multivariate Regular Variation. J Syst Sci Complex 33, 1533–1544 (2020). https://doi.org/10.1007/s11424-020-8037-z

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11424-020-8037-z

Keywords

Navigation