使用线性规划优化Omega比率

IF 0.8 4区经济学 Q4 BUSINESS, FINANCE

Journal of Computational Finance Pub Date : 2014-06-01 DOI:10.21314/JCF.2014.283

Michalis Kapsos, Steve Zymler, Nicos Christofides, B. Rustem

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引用次数: 38

摘要

欧米茄比率是最近的一项绩效衡量指标。它捕获了构建的投资组合的下行和上行潜力，同时与效用最大化保持一致。本文给出了一种用线性规划计算最大欧米茄比的新方法。虽然Omega比率被认为是一个非凸函数，但我们给出了一个关于凸优化问题的精确公式，并将其转换为一个线性程序。欧米茄比率最大化的凸重构是对均值-方差框架和夏普比率最大化的直接模拟。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimizing the Omega ratio using linear programming

The Omega Ratio is a recent performance measure. It captures both, the downside and upside potential 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 non-convex function, we 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 analogue to mean-variance framework and the Sharpe Ratio maximization.

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来源期刊

Journal of Computational Finance BUSINESS, FINANCE-

CiteScore

0.90

自引率

0.00%

发文量

期刊介绍： The Journal of Computational Finance is an international peer-reviewed journal dedicated to advancing knowledge in the area of financial mathematics. The journal is focused on the measurement, management and analysis of financial risk, and provides detailed insight into numerical and computational techniques in the pricing, hedging and risk management of financial instruments. The journal welcomes papers dealing with innovative computational techniques in the following areas: Numerical solutions of pricing equations: finite differences, finite elements, and spectral techniques in one and multiple dimensions. Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi-Monte Carlo methodologies; new strategies for market factors simulation. Optimization techniques in hedging and risk management. Fundamental numerical analysis relevant to finance: effect of boundary treatments on accuracy; new discretization of time-series analysis. Developments in free-boundary problems in finance: alternative ways and numerical implications in American option pricing.