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Total Posts: 367
Joined: May 2012
Posted: 2015-11-04 18:35

has any of you found any real advantage in using Omega Ratios vs. Sharpe?

I know the theory. I am just asking if any of you did find it useful in real life, including when you had an analyst or a prospect looking at your numbers.

The only thing that counts: Can you make money?


Total Posts: 346
Joined: Mar 2005
Posted: 2016-09-26 00:27
I have used it in the past (more Sortino actually) for a specific, niche portfolio proposition. At the end of the day they seemed to go for the team over the risk picture and parameters. Chug Beer

Salut toi, je vais au Social Club avec des amis ce soir, c'est au 142 rue Montmartre. J'ai mis ta robe préférée. Viens me trouver.


Total Posts: 367
Joined: May 2012
Posted: 2016-09-26 10:37
Thanks, I was looking for alternatives to the constraints of the Sharpe Ratio, however FWIW we may have to live with Sharpe in the end... not many care about Omega Ratio, it appears...

The only thing that counts: can you make money?


Total Posts: 996
Joined: May 2004
Posted: 2016-09-26 11:36
Keep it simple and stick to Sharpe, unless you are doing something extremely non linear (OTM options, etc...) for which Sharpe is obviously misleading.

We all know there is some amount of skewness/kurtosis in the returns of any strategy, and learn to take Sharpe ratios with a grain of salt. Just like Black-Scholes + experience is better than fancy models in many cases, Sharpe + experience is better than fancy ratios. Know your weapon.

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Total Posts: 367
Joined: May 2012
Posted: 2016-09-26 11:42
I agree, NeroTulip.

Just had in my mind a meeting with a very successful manager, years ago, and his fixation that a Sharpe above 2 could turn a small amount of money into a fortune, so the only way for him to measure a strategy was the Sharpe Ratio. He would not care about anything else.

The only thing that counts: can you make money?


Total Posts: 89
Joined: Apr 2005
Posted: 2017-06-12 12:30
I have found both empirical Omega and Sortino subject to over-fitting if your data set allows for extremely low or no downside in the in sample period - a distributional / copula approach seems to work better especially out of sample

see Good Bad , Ugly of Risk Stats and SFA Score as a RAPM
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