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2010 | 11 | 1 | 81-89

Article title

Expected shortfall and Harell-Davis estimators of value-at-risk

Content

Title variants

Languages of publication

EN

Abstracts

EN
The most widely used estimator for the Value-at-Risk is the corresponding order statistic. It relies on a single historic observation date, therefore it can exhibit high variability and provides little information about the distribution of losses around the tail. In this paper we purpose to replace this estimator of VaR by an appropriately chosen estimator of the Expected Shortfall. We also consider the Harrel-Davis estimator of VaR and give some comparative analysis among these estimators.

Year

Volume

11

Issue

1

Pages

81-89

Physical description

Dates

published
2010

Contributors

  • Collegium Mazovia in Siedlce
author
  • Collegium Mazovia in Siedlce; University of Natural Sciences and Humanities in Siedlce, Institute of Mathematics and Physics

References

  • Acherbi C., Tasche D., (2002). On the coherence of expected shortfall. J. Bank. Finance, 26:1487-1503.
  • Artzner P., Delbaen F., Eber J.M., Heath D. (1999). Coherent measures of risk. Math. Finance, 9:203-228.
  • Dowd K., Blake D., (2006). After VaR: The theory, estimation, and insurance applications of quantile-based risk measure. J. Risk Insur., vol.73, No.2, 193-229.
  • Harrell, F.E., Davis, C.E. (1982). A new distribution-free quantile estimator, Biometrika, 69(3): 635-640.
  • Mausserr H., (2001). Calculating quantile-based risk analytics with L-estimators. Algo Research Quarterly, vol.4, No.4, 33-47.
  • Rockafeller R., Uryasev S., (2000). Optimization of conditional value-at-risk. J. Risk, 2: 21-41.
  • Wirch J., Hardy M., (1999). A synthesis of risk measures for capital adequacy. Insur. Math. Econ. 25:337-348.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-a00ce69e-40eb-45af-ad79-5667f8de11cf
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