Modelling expected shortfall using tail entropy

Pele, D. T., Lazar, E. ORCID: https://orcid.org/0000-0002-8761-0754 and Mazurencu-Marinescu-Pele, M. (2019) Modelling expected shortfall using tail entropy. Entropy, 21 (12). 1204. ISSN 1099-4300 doi: 10.3390/e21121204

Abstract/Summary

Given the recent replacement of value-at-risk as the regulatory standard measure of risk with expected shortfall (ES) undertaken by the Basel Committee on Banking Supervision, it is imperative that ES gives correct estimates for the value of expected levels of losses in crisis situations. However, the measurement of ES is affected by a lack of observations in the tail of the distribution. While kernel-based smoothing techniques can be used to partially circumvent this problem, in this paper we propose a simple nonparametric tail measure of risk based on information entropy and compare its backtesting performance with that of other standard ES models.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/87772
Identification Number/DOI	10.3390/e21121204
Refereed	Yes
Divisions	Henley Business School > Finance and Accounting
Publisher	MDPI Publishing
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