On the Feasibility of Portfolio Optimization under Expected Shortfall
Physics and Society
2008-12-02 v1 Disordered Systems and Neural Networks
Portfolio Management
Abstract
We address the problem of portfolio optimization under the simplest coherent risk measure, i.e. the expected shortfall. As it is well known, one can map this problem into a linear programming setting. For some values of the external parameters, when the available time series is too short, the portfolio optimization is ill posed because it leads to unbounded positions, infinitely short on some assets and infinitely long on some others. As first observed by Kondor and coworkers, this phenomenon is actually a phase transition. We investigate the nature of this transition by means of a replica approach.
Cite
@article{arxiv.physics/0606015,
title = {On the Feasibility of Portfolio Optimization under Expected Shortfall},
author = {Stefano Ciliberti and Imre Kondor and Marc Mezard},
journal= {arXiv preprint arXiv:physics/0606015},
year = {2008}
}
Comments
9 pages, 4 figures