PHILADELPHIA (HedgeWorld.com)–NewMarket Capital Partners LLC, a fund of funds manager founded in 2003, has released a report on a new tool for the analysis of performance called the omega ratio.
The report, by Senior Investment Manager Andre Boreas, describes the omega ratio as an answer to a challenge created by traditional mean-variance analysis. Such analysis, which measures return against a manager’s, or an underlying fund’s, unit of risk, fails to distinguish between “good risk” and “bad risk”.
What is necessary, then, Mr. Boreas wrote, is “a metric that incorporates all points along the distribution curve while providing some degree of insight into what an investor’s true risk/reward function looks like across that curve.”
The omega ratio, first proposed in 2002 by William F. Shadwick and Connor Keating, is designed to fill precisely this need. It is a ratio of gains to losses across a defined threshold. Because the gains and losses are both defined in positive terms, the ratio itself must be a positive number. If the threshold in a particular case coincides with the mean of the distribution of returns, for example, the gains will equal losses, so the ratio will be 1.
The subjective input in the formulation of this ratio, then, is the threshold itself, giving rise to certain questions. At what point will a given investor consider a return to be so low as to constitute a loss? Less than 0%? Less than the rate one might get from U.S. Treasuries? Somewhere in between those two? The definition of the threshold will depend upon an investor’s risk tolerance. Obviously, a higher choice of threshold (other things constant) will result in a lower omega ratio.
What intrigues Mr. Boreas is the binary nature of the ratio. “Omega ratios greater than one indicate a higher relative probability of achieving returns above the threshold return, while omega ratios below one indicate a greater probability of not achieving returns above the threshold return.”
He concludes that there are a number of benefits to the use of the omega ratio as a risk return measure. For example, it compares returns from manager to manager (or between a manager and an index), is easy to interpret, and may be tailored according to risk tolerance.
Perhaps most important, Mr. Boreas contends, is what sets this ratio apart from the Sharpe ratio and other measures: that use of the omega ratio “rewards managers with positive fat tails, penalizes those with negative fat tails, and thus is able to convey the preference between volatility on the positive side versus on the negative side.”
Contact Bob Keane with questions or comments at firstname.lastname@example.org.