Journal of Computational Finance
ISSN:
1460-1559 (print)
1755-2850 (online)
Editor-in-chief: Christoph Reisinger
Optimizing the Omega ratio using linear programming
Michalis Kapsos, Steve Zymler, Nicos Christofides and Berç Rustem
Abstract
ABSTRACT
The Omega ratio is a recent performance measure. It captures both the downside and upside potentials of the constructed portfolio, while remaining consistent with utility maximization. In this paper, a new approach to compute the maximum Omega ratio as a linear program is derived. While the Omega ratio is considered to be a nonconvex function, the authors show an exact formulation in terms of a convex optimization problem and transform it as a linear program. The convex reformulation for the Omega ratio maximization is a direct analog of the mean-variance framework and the Sharpe ratio maximization.
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