COMMENTAR Y
10 Fallacies When Selecting CTAs Superficial aspects can be misleading SEB GLOBAL QUANT TEAM
Summary I
n this article we are taking the perspective of an institutional investor who wants to invest in one or several commodity trading advisor funds (CTAs). Meetings we have had with investors over the last decade indicate that they do an initial quantitative screening, but then – after
having met with the different CTA managers – put a lower weight on the hard facts (realised track record) and a higher weight on soft factors (all other kinds of information) when they make their final investment decision. This kind of behaviour either signals a belief that soft factors can forecast the future returns of the different CTA managers, and/or that investors make their investment decisions on the basis of emotions rather than objective facts.
We have scrutinised the following 10 fallacies in this article:
1. The Pitch Book Fallacy 2. The Slick Presenter Fallacy 3. The Big Team Fallacy 4. The Title Fallacy 5. The Long Experience Fallacy 6. The Brand Fallacy 7. The Technology Fallacy 8. The Trading Fallacy 9. The Transparency Fallacy 10. The Performance Fallacy
The research we carried out on 23 of the largest CTAs in the world resulted in the conclusion that neither team size nor experience is able to predict the risk-adjusted returns of different CTAs. After detailed discussions, we also drew the conclusion that none of the other soft factors are likely to contain any predictive power either: pitch books, communication skills of presenters, the number of people with PhD titles, the manager’s brand, the technological appearance, the trading set-up or the degree of transparency provided. Finally, when it comes to performance figures, investors need to watch out for at least seven different pitfalls when managers present their past performance.
An objective like-for-like analysis of past performance may be the only remaining factor that potentially possesses some power to predict future performance. Investors may therefore want to spend more time analysing, understanding and adjusting track records, as well as classifying CTAs into sub-categories and running client portfolio simulations to find out which CTAs generate the largest improvement in the risk-adjusted returns for the client.
Hans-Olov Bornemann Portfolio manager and head of Global Quant Team
How we did the research We started by looking at the constituents of three major CTA indices: BarclayHedge’s BTOP50, the NewEdge CTA index and the Dow Jones Credit Suisse Managed Futures index. From this aggregated group of funds, we excluded funds:
a) That tend to make qualitative (as opposed to quantitative) investment decisions;
b) That do not offer public access to their performance data on Bloomberg;
c) That did not exist prior to October 2006 or that had closed down by August 2013; d) That are copies of other funds.
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We chose to use the launch date of our own fund, SEB Asset Selection (3 October 2006), as the start date for the research. The end date of August 2013 was chosen as we easily could use data from another study we had done with that end date. Following this methodology, we ended up with the following 23 CTA funds: Altis, Aspect, Boronia, Brummer & Partners Lynx, Campbell, Cantab, Eckhardt, Estlander, FTC, FX Concepts, Graham, IKOS, Lyxor Epsilon, Man AHL, Millburn, Nuwave, Ortus, Rivoli, Transtrend, SEB Asset Selection, SMN Diversified, Superfund and Winton.
Of course, it would have been great to have had at least 30 funds in the study, but rather than tweaking
the rules or changing the methodology, we have chosen to stay with the above 23 funds.
When it comes to return data, we have derived them from each fund’s NAV per share series on Bloomberg (in dollars or euro). Sharpe1 ratios take the currency-specific and period-specific risk-free rate into account. The number of years since inception and the number of relevant researchers per fund have been taken from publicly available sources in 2013. In some cases we have had to estimate these numbers. We stopped short of trying to classify each firm’s employees with regard to their respective academic titles.
As regards the qualitative factors, we have chosen to discuss those fallacies from a behavioural finance perspective rather than making subjective assessments. Hopefully, those discussions can help fund selectors to avoid some of the pitfalls.
1. The Pitch Book Fallacy It is time to get going with the first fallacy, the Pitch Book Fallacy. It is widely known that corporate finance people at the major investment banks are the masters of the universe when it comes to pitch book production. However, anybody who has met a larger CTA firm would probably agree that their pitch books are pretty good-looking too.
Most people would probably agree that neither the structure, lay-out nor the touch and feel of a pitch book has anything to do with an investment team’s ability to generate excess returns. Anybody with an aesthetic sense and some basic knowledge of a presentation programme could come up with a very professional-looking presentation. Some managers believe it is worth the extra time and effort, others think that clients ignore the packaging.
The contents of presentations are, however, deemed to be relevant for judging a team’s future alpha generation capabilities – that is why presentation materials are always used in meetings between clients and managers. At this point, let us make a distinction between hard contents and soft contents and define hard contents to be numbers and graphs directly or indirectly related to the fund’s track record. In a corresponding way, we define soft contents to be the pages that describe the team’s history, organisation, philosophy, processes and so on.
Let us discuss the soft contents first. Some investors believe that the soft contents give a more accurate forecast of a fund’s future performance than the historical track record does. The only problem with this hypothesis is that most of the larger CTAs have investment processes and trading processes that are very similar to each other. Yet there is a fairly substantial dispersion in the funds’ returns on a
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