Pompian uses the tests he created to gauge clients’ ability to predict future market action. But he doesn’t go there first. Instead, he asks clients to guess the average weight of an adult sperm whale. Then he asks them to guess the distance to the moon in miles. Lastly, they estimate returns for their own stock portfolios. Each question requires both high and low estimates.
The range of possibilities a client offers is typically too narrow. They might pick a range for the sperm whale’s weight between 10 – 20 tons versus 20 – 100 or say that the moon is between 100,000 to 200,000 miles away instead of 100,000 to 500,000. The range your client picks gives you an idea of the propensity for overconfidence.
Trivia tests also work. You can ask how old Martin Luther King was when he died or ask clients to guess the gestation period of an Asian elephant.
Clients get a good laugh at themselves while educating themselves—and you—that their stated goals are actually based on their behavioral biases.
If you design a portfolio based on these biases, the investment process is off kilter from the very beginning. Then, when the inevitable market or economic crisis hits, things can break down because the goals used to build the portfolio were assumptions, not the client’s real goals.
Generational wealth attitudes mask a client’s real goals in much the same fashion as behavioral biases.
Take a family patriarch in 2008 who wanted to make a large investment in GM stock. GM was making new highs and had just announced it was closing four plants. It was a solid “blue chip” company that the government would never let “go under.”
The family had replaced its original position of GM—stock he had inherited from his father—in the late 1990s with a position in Amazon. The patriarch felt Amazon carried too much risk. He wanted to sell the Amazon stock and restore the GM position.
The value of GM stock in June of 2008 was approximately US$35; by June 2009, the company had filed for bankruptcy protection.
This client had been subject to overconfidence, framing bias, and hindsight. He could only see the “facts” he wanted to see. He ignored danger signals like the condition of GM’s pension plans and the sales records of some of its brands.
Even though the Amazon position had performed well, he still viewed selling GM as a mistake. He couldn’t understand or identify with Amazon’s business model—internet commerce.
If you worked with this client you’d see that his feelings about his father, about America, and WWII are clues to the generational values he hopes to pass on to his children and grandchildren.
You’d discover—among many other things—that he was afraid of running out of money despite his healthy net worth and consistently living below his means.
Educating him about these biases would free the patriarch to look at his investment decisions from a larger view. You can unearth a great deal simply by understanding the different levels of influences on decision making.
Learning how these influences are at work in your clients will help you understand how their real goals get lost in the translation to a traditional investment strategy.
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