Sunday, November 18th, 2018
the dangers of maximization

In a recent posting,Epsilon Theory | The title is “Getting Out: A Godfather Story.” Ben Hunt wrote, “My goal as an investor is NOT to maximize my investment returns or to maximize my personal wealth.”  Instead, his goal is to “minimize my maximum regret.”

As Hunt explains, that’s not the way of the investment world, with its benchmarks and optimizers and breathless searches for the best stock, the best strategy, the best manager, etc.  He says that the business is based upon the assumptions that we are maximizers and “that we SHOULD BE maximizers” — and sees that at the root of many problems.

I discussed the differences between maximizers and satisficers in three postingsthe research puzzle | This is the first one of the three; click the “next post” link at the bottom to get to the other two. written 2013, based upon ideas in The Paradox of Choice by Barry Schwartz.  Basically, a maximizer is that person who always seeks the very best choice and often spends a lot of time, resources, and emotional energy in pursuit of that goal.  On the other hand, satisficers try to make a good decision that they can live with.  In practice, maximizers often experience disappointment after the fact, because all of that effort to find the “best” can very easily come up short.

Complicating decision making when it comes to financial instruments and strategies is the pull of past performance numbers.  It shouldn’t be surprising that the average individual investor is swayed by them, since they seem to provide the score of the game.  Therefore, the best asset classes and the best mutual funds appear to be those at the top of the performance charts so eagerly supplied by financial publications, firms, and advisors.

Unfortunately, in making decisions on that basis, people face a couple of obstacles.  The first, according to James Picerno,The Capital Spectator | This posting includes some charts that illustrate the concept. is that the behavioral risk in any investment is highest early on, when volatility can give you an impression of it that is different from what your conclusion would be after the passage of time.  He says that an investor “is at high risk in this preliminary period by jumping ship (due to sharp losses) or assuming that the unusually high returns will be the norm.  In either case, behavioral risk is in the red zone.”

The second challenge is that the going-in expectations are often out of whack because the performance on which the selection was made wasn’t representative of its real prospects.  For one thing, performance results are remarkably noisy; extrapolating is dangerous business in any case.  Beyond that, it’s likely that changes in valuation contributed to the performance pattern that was relied upon; a turnabout in the valuation trend leads to performance that doesn’t fit with expectations.Research Affiliates | This paper by Rob Arnott and others gets into that phenomenon in some detail.

For those relying on long-term historical performance for asset classes to set their allocation preferences today, that issue presents itself in spades.  Valuation changes have been the wind at the back of the financial markets over the last few decades.  A reversal of that trend would lead to much different outcomes than are expected.

On a more tactical basis, the relative performance of specific strategies and asset managers often prove disappointing after selection simply because of the unanticipated reversion of valuation effects.  The seeds of subsequent underperformance can be sown during the very outperformance that catches the eye and proves to be irresistible.

Professional investors are not at all immune from the allure of performance.  While the sensitivity to performance varies considerably, chasing it is essentially designed into the evaluation and selection of asset managers by almost all allocators.

In my workshopstjb research | Here is a summary of the training that I provide on these topics. and presentations on due diligence and manager selection, I try to isolate factors that contribute to that problem.  One easy example comes from comparing the assessments of attendees of the time required for statistical significance of performance to the evaluation windows and characterizations that they actually use in practice.  It’s easy to toss around the label of “proven performer” to support your case, but it’s harder to be clear about what that actually means (and to have it comport with notions of statistical significance).  What evidence constitutes “proof”?

As is the situation for all of us, professionals engaged in manager research are prone to having the performance record of an asset manager distort the analysis of it — and that record invariably frames the mindsets of those (investment committees, advisors, and clients) who ultimately act on the research regarding that manager.

Compounding the problem, many firms define their goal as finding the “very best” managers.  (Talk about a bunch of maximizers.)  That goal seems natural, but what comes with it?  Likely, a greater sensitivity to performance in the decision process, as well as increased behavioral risk in response to any performance disappointment after the decision has been made.  After all, can you really sit by patiently when there is some evidence that a manager is not the very best?  Remember the goal!  (“The fallacy of intervention” kicks in.  As Richard Thaler describes it, “When things are going badly, it feels right to make a change.”  Thus begins a new search for the very best.)

It would seem odd for anyone involved in analysis to seek anything but the best.  However, if that orientation leads to increased behavioral errors or problematic situations down the road, maybe it’s not the right framework to use.  Thus Hunt’s argument:  The investment norms of the day can appear to provide the right map to follow, but they might lead to results that are unexpected and unwanted given the impermanence of economic trends, the sociology of markets, and the psychology of individual decision makers.

Maximization always sounds like the answer.  It keeps pulling us back into games that maybe we shouldn’t be playing.