This post was originally published on August 22, 2007. It has been republished from a previous version of the site.
The Omega Measure is a popular fund evaluation tool, allowing traditional economic decision theory to guide asset allocators. Assets can be compared either at specific return thresholds or across a whole range of desired of returns. Though typically used to evaluate fund-of-fund managers’ performance, I have here applied the Omega ratio to the ETF and CEF market at various specific thresholds.
Details:
As the Omega measure at a given return threshold is calculated on the Omega function, defined to be homeomorphic to cumulative return density functions, I have used the intuitive upper / lower partial moment method of calculation. The thresholds used are no return (0), the average SPY return, the average IWM return, and twice the average IWM return. I have weighted each return threshold thusly: 10% for 0 return, 50% for SPY return, 30% for IWM return, 10% for double IWM return. To be fair, I have used only ETFs and CEFs that have traded at least 250 periods, and thus only 250 periods for each.
Symbol | K=0 | K=SPY | K=IWM | K=2*IWM | Score |
PMH | 1.81 | 1.72 | 1.3 | 0.95 | 1.7 |
IAH | 1.45 | 1.43 | 1.32 | 1.2 | 1.52 |
MXE | 1.37 | 1.36 | 1.32 | 1.27 | 1.48 |
ITA | 1.41 | 1.39 | 1.28 | 1.16 | 1.47 |
SHY | 1.98 | 1.67 | 0.71 | 0.27 | 1.47 |
PPA | 1.4 | 1.38 | 1.26 | 1.13 | 1.46 |
ASG | 1.39 | 1.37 | 1.25 | 1.12 | 1.45 |
IXP | 1.38 | 1.36 | 1.25 | 1.13 | 1.44 |
TTH | 1.36 | 1.34 | 1.23 | 1.11 | 1.42 |
USA | 1.37 | 1.34 | 1.2 | 1.06 | 1.41 |
PGJ | 1.32 | 1.31 | 1.25 | 1.18 | 1.41 |
FXI | 1.31 | 1.3 | 1.25 | 1.19 | 1.41 |
GGT | 1.35 | 1.33 | 1.22 | 1.09 | 1.41 |
APB | 1.31 | 1.3 | 1.24 | 1.17 | 1.4 |
CII | 1.36 | 1.33 | 1.2 | 1.05 | 1.4 |
IHI | 1.35 | 1.32 | 1.19 | 1.05 | 1.39 |
GAB | 1.34 | 1.31 | 1.19 | 1.06 | 1.39 |
VOX | 1.32 | 1.3 | 1.19 | 1.07 | 1.38 |
WMH | 1.31 | 1.29 | 1.2 | 1.09 | 1.38 |
EWG | 1.31 | 1.29 | 1.2 | 1.1 | 1.38 |
Here’s a guide to maximizing the Omega Ratio for a portfolio of investments. It uses Excel, but the principles can be applied to better optimizers (i.e. those offered by NAG etc).