全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Expected Shortfall Semi-Scale T-Distribution M-Estimator

DOI: 10.4236/jmf.2023.134029, PP. 483-500

Keywords: Risk, Expected Shortfall, Semi-Scale, MLE, M-Estimator, Influence Function

Full-Text   Cite this paper   Add to My Lib

Abstract:

The influence function of parametric t-distribution expected shortfall (ES) estimators has an approximately symmetric shape, for which large positive returns indicate large losses. We avoid this risk estimator’s unacceptable feature by introducing an ES semi-scale M-estimator for t-distributions, for which the usual t-distribution scale parameter is replaced by a semi-scale parameter. We derive the influence function of the ES semi-scale M-estimator, and show that its influence function has large values only for large negative returns as one expects, and only very small typically negative values for positive returns. The computation of an ES semi-scale M-estimator is shown to be a simple modification of a parametric t-distribution ES maximum-likelihood estimator (MLE), in which the scale MLE is replaced by a semi-scale estimator. We also derive the asymptotic variance expression for the ES semi-scale M-estimator, and show that its standard error is not very much larger than that of the t-distribution ES maximum-likelihood estimator.

References

[1]  JPMorgan/Reuters (1996) RiskMetrics—Technical Document. 4th Edition.
https://www.msci.com/documents/10199/5915b101-4206-4ba0-aee2-3449d5c7e95a
[2]  Artzner, P., Delbaen, F., Eber, J.M. and Heather, D. (1999) Coherent Measures of Risk. Mathematical Finance, 9, 203-228. https://doi.org/10.1111/1467-9965.00068
[3]  McNeil, A.J., Frey, R. and Embrechts, P. (2015) Quantitative Risk Management. Princeton University Press, Princeton.
[4]  Rockafellar, R.T. and Uryasev, S. (2000) Optimization of Conditional Value-at-Risk. Journal of Risk, 2, 21-41. https://doi.org/10.21314/JOR.2000.038
[5]  Fischer, T. (2003) Risk Capital Allocation by Coherent Risk Measures Based on One-Sided Moments. Insurance: Mathematics and Economics, 32, 135-146.
https://doi.org/10.1016/S0167-6687(02)00209-3
[6]  Martin, R.D. and Zhang, S. (2019) Non-Parametric versus Parametric Expected Shortfall. Journal of Risk, 21, 1-41. https://doi.org/10.21314/JOR.2019.416
[7]  Jorion, P. (2007) Value-at-Risk. 3rd Edition, McGraw-Hill, New York.
[8]  Hampel, F.R. (1974) The Influence Curve and Its Role in Robust Estimation. Journal of American Statistical Association, 69, 383-393.
https://doi.org/10.1080/01621459.1974.10482962
[9]  Zhang, S. (2016) Two Equivalent Parametric Expected Shortfall Formulas for T-Distributions. https://ssrn.com/abstract = 2883935
[10]  Hampel, F.R., Ronchetti, E.M., Rousseeuw, P.J., and Stahel, W.A. (1986) Robust Statistics: The Approach Based on Influence Functions. John Wiley & Sons, Inc., New York.
[11]  Zhang, S., Martin, R.D. and Chritidis, A.A. (2021) Influence Functions for Risk and Performance Estimators. Journal of Mathematical Finance, 1, 1-33.
https://doi.org/10.4236/jmf.2021.111002
[12]  Lucas, A. (1997) Robustness of the Student-t Based M-Estimator. Communications in Statists-Theory and Methods, 26, 1165-1182.
https://doi.org/10.1080/03610929708831974
[13]  Azzalini, A. (2023). http://azzalini.stat.unipd.it/SN/

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133