From the January 2017 issue of Investment Advisor • Subscribe!

Human Behavior + Computational Ease: Enter the Age of Agility

The most successful managers are free from arbitrary constraints

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It’s widely understood that generating alpha is a zero-sum game even before fees and taxes. It’s widely understood that generating alpha is a zero-sum game even before fees and taxes.

In Finance 101, we learn of the efficient market hypothesis and its assertion that asset prices fully reflect all known information, and its corollary, that trying to beat the market is futile. And yet there are thousands of managed products that attempt to do just that. Most fail, as it’s widely understood that generating alpha is a zero-sum game even before fees and taxes. As a result, we’ve seen the rise of passive investing, the thinking being, “Control what you can control — cost — and let the chips fall where they may.”

Interestingly, over the same time that passive approaches have grown in prominence, so too has our understanding of how we make decisions under the cloud of uncertainty and when staring down the ravenous eyes of risk. This expansion of knowledge can be credited to the work of a collection of disciplines that fall under the “Behavioral Economics” label. The website catalogs well over 100 distinct behavioral flaws, from the widely accepted, like “Loss Aversion” and “Anchoring,” to the lesser known, like “Touchy-Feely Syndrome” (admittedly a new one for us).

We’ve observed that as the asset management business has flourished, and as client needs have become more clearly delineated, the size and structure of investment programs have added to the inefficiencies discovered through cognitive psychology. Take for example the situation where, per investment policy statement, managers are prevented from owning debt that isn’t investment-grade; when a bond is downgraded below BBB, those managers are forced to sell. Or consider the plight of massive equity funds that have to put tens of billions of dollars to work and are terrified of considering smaller and less liquid names, no matter how appetizing the investment story, for fear of being labeled a “style drifter.”

Beating the market requires that one have a non-consensus view and be right more often than wrong. How that is accomplished, we believe, isn’t simply a matter of better financial statement analysis; there are far too many highly educated individuals in our business who spend all of their time poring over balance sheets. The trick is to identify the reason that the market is mispricing the security; and for that to be true, given how compelling the efficient market hypothesis is, there has to be an identifiable inefficiency that makes it so. To have confidence in the idea, we need to understand both the reason for the inefficiency’s existence and why it should reasonably persist. We refer to this as an alpha thesis.

Competition in the asset management industry is fierce, and in this arms race, we’ve witnessed a shift from hiring those trained in financial analysis to those trained in math, statistics and computer programming. If you stop to think about it, all investment approaches rely on models; the difference is that the models (algorithms, heuristics, etc.) employed by discretionary approaches reside in the heads of analysts and portfolio managers, whereas the models employed by systematic managers sit on computers. Both discretionary and systematic methodologies can be fundamentally based or technically based. It’s wrong to think quant = technical and discretionary = fundamental, as is often the way it’s portrayed. So what is the most efficient way to run a model: in your head or on a computer?

In our work, we’ve identified numerous inefficiencies that we try to exploit, from the herding behavior of analysts to the institutional footprints left by the largest investors to the short-term overreactions of the market. Interestingly, while many of the exploitable inefficiencies seem to require exceedingly long time horizons, most of the compelling ideas that we observe require agility to capture the benefits. There doesn’t seem to be a lot of middle ground, and we suspect that for many asset managers, there is a duration mismatch between the life of the inefficiency and the time it takes to analyze and act (not to mention the duration mismatch between long-term investment theses and investor patience levels); a supposition we feel is borne out in our industry’s results.

The managers with the greatest freedom to act — those free from the long-only constraint or other arbitrary limits on their positions — along with the computing power to stay ahead of the crowd will be the winners in this new age.

--- Read Advisors to Boost Use of Managed Futures in 2017, Though Many Have Concerns: Poll on ThinkAdvisor.

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