The ability to reason is a fundamental characteristic of human beings. Virtually every activity — conscious or not — involves reasoning. We reason whenever we solve problems, explain events, balance chequebooks, predict elections, interpret works of art or even go marlin fishing.

We all know faulty logic and bad decisions when we see them. Yet, recognizing bad decisions and understanding them are two very different things, especially since many activities do not necessarily involve conscious effort. It seems we don’t take the time to ask ourselves what exactly constitutes a rational decision and to what extent our behavior reflects those qualities. However, the observations of risk and probability discussed here show that we really should.

Early normative models of economics and decision-making viewed humans as rational agents, assuming that a reasonable person would do their best to optimize outcomes. These thought models formed the expected utility hypothesis, a theory widely accepted and applied in economic academia. Of course, it was expected that certain axioms of rationality would be violated in practice. However, it wouldn’t be until the late twentieth century that theories of decision-making began to better illustrate reality.

Prospect theory

Prospect theory, created by Daniel Kahneman and Amos Tversky, was perhaps the first theory to document empirical evidence of systematic violations of rational behaviour. Their findings formed the foundation of behavioural economic studies and were unique because they described real-life outcomes.

Following in Kahneman and Tversky’s inquisitiveness, we conducted a study of our own to ascertain a simple, yet powerful bias. We used the following scenario:

“One of your colleagues took off for vacation last Friday. He locked a $20 “Your Shared Lotto Max” ticket in his desk.  Somebody won the jackpot and it remains unclaimed and you know the winning ticket was sold in your province.”

In the first instance, we asked readers how much they would offer to pay for the ticket. Two months later, we asked readers how much they would be willing to sell the ticket for. Utility theory tenants assert that all participants should be willing to pay the same amount they would sell the ticket for. This was not the case. Our respondents were not willing to pay nearly as much as their desired selling price. These results are consistent with a key tenant of prospect theory regarding loss aversion: “In particular, people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. Overweighting low probabilities contribute to the attractiveness of gambling.”[1]

In general, our survey showed that, when contextualized from a seller’s perspective, people were either not willing to sell the ticket or demanded a higher price because the chance (~1/28,633,528) of winning the jackpot could be retained. However, when asked how much they would pay, which would forfeit the possibility of winning, the average price was frequently much lower. Our results underscore an important behavioural bias: loss aversion. We tend not value potential returns nearly as much an equally potential loss.

 

Kahneman, now teaching at Princeton, also demonstrated this to his students using a simple experiment requiring only a $10 bill and a coin. Students were pitted against the professor in a game of heads-or-tails. If the student showed heads, Kahneman would pay them $2. If the coin landed on tails, the student would instead pay Kahneman $1. The exchange of funds took place after every flip for 10 rounds. After the game’s conclusion, students were asked whether they wished to play again under the same conditions. Given the probabilistic payoff is positive, you should play this game every chance you get. Yet in the few instances where the offer to play in the second round was declined, those students very often had lost money the during the first round of the game.

Richard Thaler conducted a similar experiment. Students were told to assume they had just won $30 and were offered a coin-flip upon which they would win or lose $9, and 70% of them opted for the coin-flip. When other students were offered a choice between $30 or a coin-flip in which they would receive either $21 or $39, a much smaller proportion of students, 43%, opted for the coin-flip.

Put otherwise: imagine that you must pick between a 5% chance of winning $10,000 by risking $500 or risk losing $9,500 for a 95% chance of winning $500. Not many would choose risking that much money to win $500, despite identical payoffs. In all above cases, it seems that losing hurts roughly twice as much as an equivalent gain.

The alchemy of behavioural investing

Finding supporting evidence of these theories in a classroom setting is much easier than in the real world (aka markets). Several years ago, we began an extensive study on behavioural economics in an attempt to find ways to isolate and eliminate the impacts our innate biases and emotions made on our investment decisions. We quickly realized that if we could identify clear instances where behavioural dislocations were causing investors to make disadvantageous decisions, en masse, we could profit from those making the mistakes. Our findings led to the development of Purpose Behavioural Opportunities Fund. One of the strategies inside the Fund, emotional cascade, identifies “students” who let their biases get the better of them and opted out of Kahneman’s game.

Prospect theory has taught us that individuals overweight the tails of any distribution, inclining us to want to hold onto lottery tickets in hopes of winning big. Another tenant integral to our investment approach is availability bias, which states that we possess a tendency to refer to examples that are top of mind, rather than what is actually happening. This is what drives retail investors to buy stocks that have positively skewed returns, possess a history of outperformance and appear extraordinarily popular. This positive skew nudges investors to innately believe that there is a greater chance of winning big on well-known, successful stocks than their underperforming peers. A slew of positive news stories further accentuates the availability biases of investors, causing them to place a larger emphasis on newer information while overlooking the cold, hard facts.

Our strategy uses a variety of factors to identify sentiment changes that cause a major stock price reaction, fueled either by fear or greed. On the short side, we have observed emotionally-driven market participants that tend to overpay for securities in the hopes of getting rich. In cases where fears of missing out on current hype is prevalent, there tends to be an overemphasis on timely news and price movements. This herd mentality clouds sound judgment, creating pleasing opportunities for us. In most cases, investors quickly revert to being loss averse when stocks don’t perform as they expected.

We identified such patterns with Grubhub. In July, the company announced that they had signed an exclusive deal with Yum Brands to operate their food delivery services. Investors became enamored with this development while forgetting about the company’s weak competitive advantage and the competitive threats posed by rivals such as Uber. Eventually, the economic reality of the business caught up with investors and reverted performance towards the mean.

On the long side, we took advantage of an opportunity in March following Facebook’s Cambridge Analytica scandal. After being accused of tampering with the 2016 US presidential election, the company’s daily news counts spiked (most of which was extremely negative). Chart investors fled, and the market clearly weighted more judgment on news of the scandal while missing the fact they were expecting to grow sales by roughly 20% for the next five years.

Our team firmly believes that investing lies at the intersection of economics and psychology. We find solace in the fact that, so long as humans continue to participate in the markets, we will always have a job.

 “The intelligent investor is a realist who sells to optimists and buys from pessimists.” – Benjamin Graham

— Craig Basinger, Chris Kerlow, Derek Benedet and Alexander Tjiang are members of Richardson GMP’s Connected Wealth team which manages Purpose Core Equity Income FundPurpose Tactical Asset Allocation Fund and Purpose Behavioural Opportunities Fund

[1] Kahneman, Daniel and Amos Tversky. “Prosepct Theory: An Analysis of Decision under Risk.” 1979.

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