Omega

Abstract

Observing that financial markets have performed in unexpected ways over the past several years, the author draws attention to the question of risk measurement. He suggests that widely used statistical measures of investment risk have significant limitations, and argues that actual performance results often do not meet expectations, because of faulty a priori risk assessment. He introduces ‘Omega,’ a statistical measure developed to capture higher levels of information provided by the historic return track record of investments, and enable investors to evaluate and rank investment opportunities based on their individually defined tolerances for loss. The article provides a practical introduction to the Omega statistic by starting with an overview of the general use and limitations of statistical analysis for investment managers. Omega is contrasted with traditional measures of risk and the author suggests that it incorporates more of the higher moment statistical information available to investment analysts. He concludes with an argument that Omega is at least comparable to, and potentially better than, traditional mean-variance analysis in providing meaningful insight to investors.