Market insights and analysis

How dynamic, risk-managed investment solutions are performing in the current market environment

1st Quarter | 2022

Market insights and analysis

rss

Updates on how dynamic, risk-managed investment solutions are performing in the current market environment.

By David Wismer

Some time ago, I listened to an interview on Bloomberg radio with Thomas Gilovich, a well-known professor of psychology at Cornell University. He has conducted research in social psychology and behavioral economics, with a focus on human biases in decision-making. He is the author of several books, including “How We Know What Isn’t So: The Fallibility of Human Reason in Everyday Life.”

Carl Sagan said of Gilovich’s work that it is “most illuminating” in showing “how people systematically err in understanding numbers, in rejecting unpleasant evidence, and in being influenced by the opinions of others.”

During an interview with Barry Ritholtz, Professor Gilovich touched on a lot of eye-opening topics related to human behavior, both market-related and otherwise. One of the themes of the interview explored why the human mind leads people to ignore some fundamental principles of mean reversion.

Data over time will normally regress to the mean or average, yet people tend to remain “anchored” to what happened most recently. Whether it concerns the financial markets, sports, the weather, or everyday life, Gilovich maintains the following:

• We tend to see more patterns in the world than are there.

• We too often hold on to beliefs that do not fit the observed data.

• We give too much credence to evidence that supports our beliefs and give too little credence to data that does not support our beliefs—confirmation bias is the “mother of all biases.”

Gilovich likes to use easily understood examples from the sports world to communicate some of his points. Three quick examples from the interview explore how overlooking mean-reversion theory can impact some common biases:

#1 “The Sports Illustrated Cover Jinx”: Over the years, people have maintained that appearing on the cover of Sports Illustrated (SI) is bad luck for an athlete. In fact, several pro athletes have turned down a cover for that reason. Gilovich points out that to be considered for a cover in the first place, an athlete usually had to have had an extraordinarily strong performance in his or her last season or last event. Simple mean reversion says that the odds are good that the athlete will not perform up to that standard in the next season or next event. So, while the SI effect might have a basis in observed data, it is not a “jinx,” but more likely reversion to the mean.

#2 “Don’t mention a no-hitter in the dugout”: Every baseball player from Little League on is told it is bad luck to mention a no-hitter in progress within earshot of the pitcher throwing the no-hitter. Gilovich says no-hitters, by definition, are an extremely rare occurrence outside the normal range of most games played. Players tend to remember when no-hitters were “lost” due to some loose lips in the dugout, when in fact the vast majority of no-hitters in progress never make it to fruition. “Bad luck” does not play a role either way, but people are selective in their memory.

#3 “Always give the ball to the player with the ‘hot hand’”: Gilovich, cognitive psychologist Amos Tversky, and statistician Robert Vallone wrote a paper in 1985 that debunked the notion that a “hot” player in sports (specifically basketball) is more likely to remain “hot”—put another way, that a player who has made a high percentage of shots in a game will be more likely to hit his or her next shots. Though somewhat controversial, their data supported the notion that “the hot hand fallacy can lead people to form incorrect assumptions regarding random events.”

What is one explanation for why both fans and coaches believe in the “hot hand theory”? People are more likely to remember a player who performed exceptionally (where he or she made, say, 14 out of 18 shots in a game) than they are the player who made five shots in a row and then reverted to the mean of average performance in that same game. Both random patterns might be achieved several times over thousands of games, but only one type is memorable.

In each of these cases, says Gilovich, individuals have preconceived notions that fly in the face of observed data or the explanation of observed data. He likes to summarize this form of confirmation bias in what he calls a “Freudian slip” from a conversation he once had. Many people, he says, operate from the perspective of “I’ll see it when I believe it.”

***

What does this discussion have to do with the financial market’s behavior?  And investment management theory?

Simply that no matter what one’s emotions or biases are saying about a strong trend in the market, it is a pretty sure thing that eventually that trend will see some mean reversion, or reversal to the trend.

This is just one reason why Flexible Plan Investments (FPI) believes in taking portfolio strategic diversification “to the next level.”

FPI’s investment strategies offer a three-dimensional approach to diversification that aims to increase the odds that a portfolio is correctly positioned to weather market storms—while taking advantage of market opportunities:

1. Diversification by asset class (e.g., stock, bonds, alternatives).

2. Diversification by investment methodology (e.g., momentum, trend following, mean reversion, pattern recognition, and many other approaches).

3. Diversification by time horizon.

Additionally, dynamic strategic diversification can be responsive to different market environments, employing higher portfolio allocations to strategic approaches that tend to perform better in a specific type of environment.

For example, a dynamic, risk-managed approach can seek to do the following:

• Allocate more to trend-following, high-beta, and leveraged strategies in rising, bullish markets.

• Allocate more to inverse strategies, leveraged inverse strategies, or strategies with exposure to defensive asset classes during falling, bearish markets.

• Allocate more to mean-reversion or pattern-recognition strategies during sideways markets, taking advantage of volatility and market swings.

FPI’s president and founder, Jerry Wagner, has written, “Keeping an eye on all key indicators through our quantitative strategies is what our dynamic, risk-managed investing approach is all about. Historically, it has helped us minimize the downside in bear markets, and that goes a long way toward ‘beating the market’—as we define it.”

With FPI’s firm commitment to transparency on strategy performance, I think that is something you can both see and believe in when it comes to portfolio management over full cycles of the financial markets.



Comments are closed.