Optimizing expected shortfall under an ℓ1 constraint—an analytic approach
Gábor Papp,
Imre Kondor and
Fabio Caccioli
LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library
Abstract:
Expected Shortfall (ES), the average loss above a high quantile, is the current financial regulatory market risk measure. Its estimation and optimization are highly unstable against sample fluctuations and become impossible above a critical ratio r=N/T, where N is the number of different assets in the portfolio, and T is the length of the available time series. The critical ratio depends on the confidence level α, which means we have a line of critical points on the α−r plane. The large fluctuations in the estimation of ES can be attenuated by the application of regularizers. In this paper, we calculate ES analytically under an ℓ1 regularizer by the method of replicas borrowed from the statistical physics of random systems. The ban on short selling, i.e., a constraint rendering all the portfolio weights non-negative, is a special case of an asymmetric ℓ1 regularizer. Results are presented for the out-of-sample and the in-sample estimator of the regularized ES, the estimation error, the distribution of the optimal portfolio weights, and the density of the assets eliminated from the portfolio by the regularizer. It is shown that the no-short constraint acts as a high volatility cutoff, in the sense that it sets the weights of the high volatility elements to zero with higher probability than those of the low volatility items. This cutoff renormalizes the aspect ratio r=N/T, thereby extending the range of the feasibility of optimization. We find that there is a nontrivial mapping between the regularized and unregularized problems, corresponding to a renormalization of the order parameters.
Keywords: portfolio optimization; regularization; renormalization (search for similar items in EconPapers)
JEL-codes: F3 G3 J1 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2021-05-01
New Economics Papers: this item is included in nep-cwa, nep-isf, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations:
Published in Entropy, 1, May, 2021, 23(5). ISSN: 1099-4300
Downloads: (external link)
http://eprints.lse.ac.uk/111051/ Open access version. (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:111051
Access Statistics for this paper
More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().