To seek alpha, analyze managers, not funds

This WSJ article on identifying and analyzing mutual funds is interesting because of what’s not there. The article describes a new study by Fama and French, the prolific finance authors who continue to study the efficient market hypothesis and the effects of pretending it doesn’t exist.

In short, the study tracked yet another big collection of mutual funds over a span of some 22 years, then doing “10,000 simulations.” (That sounds to me like a NYT-ish description of what might have been a Monte Carlo simulation, but I can’t fathom why the WSJ wouldn’t just say that. After all, if a lawyer with an English degree knows what it is, don’t most Journal readers?) I had to sleuth around for the paper, since the article doesn’t say where or when it was published. Why? Perhaps it’s because the paper doesn’t appear to have been published, per se, but is available on SSRN: Luck Versus Skill in the Cross Section of Mutual Fund Returns.

What the abstract doesn’t say, and the journal article does, is whether the high-performers can be distinguished as being good rather than lucky. Clearly the EMH requires us to conclude that the top-performing funds are lucky rather than good. I know that I have recently seen references to articles tracking the movement of funds from the top-tier of performers over time.

Where TSC has become involved in this type of analysis, we’ve chosen instead to focus on the massive amount of data that is in fact sitting on the books of financial advisors. In working with a high-net-worth family, we sought to track not just overall performance of their investment portfolio as a whole, but the effects of each major component: stocks, bonds, and cash. But we wanted to go further. We knew that the “relationship manager” at the high-end wealth management arm of a global bank wasn’t making the individual stock picks. Rather, there were a wide range  of analysts and traders involved in making decisions for the family, ranging from individual trades to funds to allocations across whole market segments.

What TSC’s proprietary process, tools, and knowledge allowed us to do was create an analysis, decision, and guidance framework by breaking down the overall performance into its component parts and using that information to provide guidance to the investing activity.

That’s why, for us, the article leaves us wishing for more: managing performance at the “fund” level is like talking about Brazil world cup teams as if the players don’t matter: who’s gonna tell that to Pele? Or Ronaldo? Or Ronaldinho? Not me, especially after seeing this, this, and this. Even (especially?) on a great team, individuals matter.

Imagine a mutual fund model where you could package together individual traders or analysts? The new crowdsourced investment sites let you track individuals and will someday almost certainly offer the opportunity for you to follow their trades. But that’s working backwards: large funds already track every single trade because of compliance reasons as well as the simple expedients of getting everything executed. There’s no reason that a wealth management firm couldn’t implement this tracking, or at least provide the data, for its high-net-worth clients.

TSC is looking for family offices, investors, or even CFOs managing cash investments for a pilot project to implement our proprietary systems in your live environment to create a robust reporting and risk management tool. Please contact us for details.


  1. Rick Colosimo on April 28, 2010 at 8:48 pm

    Here’s a brief article about the DOD looking for ways to use algorithms to identify quality intelligence analysts.

    The comparison is this: is ability to properly analyze a US equity issue more consistent than an intelligence estimate? Probably.