Alternative Viewpoints: Sustainable Hedge Fund Performance
| Mar 31st, 2008 | Filed under: CAIA Alternative Viewpoints Columns, CAPM / Alpha Theory, Guest Posts | By: Alpha Male |
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Every year, pure random chance dictates that exactly half of all investors will outperform the median and half underperform the median. The Holy Grail of alpha generation, of course, is to outperform more than pure random chance should allow. In other words, to produce persistent alpha.
In our monthly column featuring the thoughts of a member of the Chartered Alternative Investment Analyst (CAIA) Association, we feature one academic who may have identified a way to uncover such non-random outperformance. Daniel Capocci, Ph.D., CAIA, is a senior portfolio manager at KBL European Private Bankers, a lecturer at the Luxembourg School of Finance and a Research Associate at the Edhec Risk & Asset Management Center.
Alternative Viewpoints, powered by CAIA
Special to AllAboutAlpha.com by: Dr. Daniel Capocci, CAIA, KBL European Private Bankers
Three fields exist that examine hedge fund performance. The first includes studies that compare the performance of hedge funds with equity and other indices (some authors conclude that hedge funds are able to outperform these indices, whereas others are more cautious in their conclusions).
The second field of hedge fund performance analysis compares the performance of hedge funds with that of mutual funds (where some have found that hedge funds constantly obtain superior performance to mutual funds, although lower and more volatile returns than the reference market indices considered.)
Finally, the third group of hedge fund performance analysis examines the persistence of hedge fund returns. Persistence is particularly important in the case of hedge funds because the hedge fund industry has a higher attrition rate than mutual funds.
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“funds with a limited exposure to the equity market consistently and significantly outperform equity and bond markets”
I don’t think that if I have a fund exploring betas in non equity/bond asset classes, I am creating alpha…
Been trying to “break” our models that have been back & forwarded tested ad nauseam, and thus far am unable to do so. IMHO it’s our risk control & adaptive money management, coupled with a periodic reoptimization followed by daily total rescreening of our 30+ algorithms that has created the robustness of our risk:reward ratio and non-leveraged returns. Just damn sustainable performance!
Saying that, perhaps our log normal return bell curve will begin to skew if we take on too much investment, i.e., in excess of $3B, non-leveraged? Difficult to say, in practice, as it is typically the manager’s goal to accept a larger asset pool if expected lower returns, making up with the larger pool of assets to earn the management & performance incentive fee. So do we stick with $3B as a limit and take our 50% incentive fee above the benchmark, or do we simply accept unlimited client assets at the orthodox 1%/20% and make it up on the volume of assets?
I suppose if I am able to break our adaptive models, then I’ll have my answer.