Key Points

  • Statistically, it’s sensible to take a wager if the odds are in your favor.
  • Nevertheless, the bias of Loss Aversion notes that individuals will carefully consider the magnitude of potential losses relative to the gains before making such a bet.
  • This notion and many others are based upon the pioneering work of Amos Tversky and Daniel Kahneman, two highly influential researchers in the field of behavioral economics.

It turns out humans are far more concerned with losing money than gaining money. No surprise here. But what’s really interesting is that this bias exists even if the odds are dramatically in one’s favor to profit. Sound strange, right? This post will explore this phenomenon more closely and we will see where the research takes us.

Flip a Coin

Let us make a simple wager. Heads, I win $1000. Tails, you win $1010. It’s a fair coin, and your chances of winning are indeed 50%. In this bet, your expected winnings are $5, and here’s the quick math that shows this:

Win Amount = $1010; Loss Amount = -$1000; Win Probability = 50%; Loss Probability = 50%

Expected Winnings = (Win Amount) x (Win Probability) + (Loss Amount) x (Loss Probability)

Expected Winnings = ($1010 x 50%) + (-$1000 x 50%) = $505 – $500 = $5

Would you take this bet? Unsurprisingly, most people would not. From a statistical standpoint, this bet is sensible because you stand to win more than you stand to lose. If you were to place many (read: a large number) of these bets, you should come out on top over time. Nevertheless, you decide to pass on my offer. Rightfully so. After all, who really wants to lose $1000?

So how much would someone have to win for that individual to actually take up this bet? If this person cared about expected winnings, than any amount over $1000 would suffice; but if this person cared more about not losing so much money, than it turns out much more than $1000 in winnings will be required. Let’s explore what may be going on here and how all this relates to investing.

Famous Amos and Noble Daniel

It’s impossible to discuss the irrationality of human behavior without peering into the seminal work of Amos Tversky and Daniel Kahneman. These two academics paired up in the 1960s to conduct research that fundamentally challenged the traditional thought process of the day—the prevailing notion that humans beings tend to make rational decisions. Over time, Tversky and Kahneman published a significant amount of research and analysis that dramatically altered this traditional line of thinking and replaced it with a much more nuanced view of human behavior.

 

 

In 2002, Kahneman won the Nobel Memorial Prize in Economic Sciences for his work in developing Prospect Theory, a theory which he helped create with his associate Tversky back in 1992. Unfortunately, Tversky passed away in 1996, so he was not awarded the Nobel prize for his efforts given that the prize is not awarded posthumously.

Nevertheless, according to Kahneman, speaking of his relationship with Tversky, “I feel it is a joint prize. We were twinned for more than a decade.”[2] As it turned out, Prospect Theory ended up having numerous applications across the sciences, including economics, finance, and investing. As such, this topic is certainly worth investigating in more detail as it relates to this series.

[Prospect Theory] states that people make decisions based on the potential value of losses and gains rather than the final outcome, and that people evaluate these losses and gains using some heuristics.—Wikipedia

Applying this theory to our coin-flip example above can provide us with some added color on this phenomenon. Rationally, we should care most about the expected outcome, which in the example we noted above is $5. But in reality, we tend to care more about what can lose ($1000 down the tubes) and than what we can stand to gain ($1010 in the bank). Tversky and Kahneman first identified this behavioral bias and they called it Loss Aversion.

In cognitive psychology and decision theory, Loss Aversion refers to people’s tendency to prefer avoiding losses to acquiring equivalent gains: it is better to not lose $5 than to find $5.—Wikipedia

According to the experiments of these two individuals, their research suggests that individuals tend to place more than a 200% weight on losses over equally probable gains[1]. For example, in our coin flip example above, an individual would want to win over $2000 just for the chance of not losing $1000. In the next post of this series, we’ll tie Loss Aversion to investing and show how this behavioral bias can lead to unintended consequences. Unfortunately, these consequences can end up costing you dearly when it comes to making sound investment decisions.

And of course, there exist many more behavioral biases that have emanated from the work of Tversky and Kahneman so we’ll be sure to take some time to dig into more of their work over the course of this series.

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