Author: Ron Dembo
In 1979, American IT company Electronic Data Systems were worth about $1 billion. Their head, Ross Perot, wanted to invest in a small computer company to supply software. After searching around, they discovered the young Bellevue software company Microsoft, but when Bill Gates asked for $40–60 million, they flat out rejected him.
In 2020, Microsoft’s net income was $44.28 billion, and Gates was the second richest man in the world (behind Amazon’s Jeff Bezos).
Perot later said, “I consider it one of the biggest business mistakes I’ve ever made… I should have just said, ‘Now Bill, you set the price, and I’ll take it.’”
Regret Matters for Risk Management
But why did Perot think it was the biggest mistake of his life? To us it seems obvious — each of us can instinctively understand that fear of missing out (FOMO). But for a while it was hard for economists to wrap their heads around — to quantify it and understand the impact it had on investment decisions. After all, from a numerical perspective, it wasn’t so bad: Perot didn’t lose any money from the decision, nor did he end up in poverty (he died worth a cool $4.1 billion).
Think about the difference between risk and regret this way, as Harvard professor David Bell does. Imagine that you have been playing the lottery every week for several years, and you always pick the same combination of numbers. But then one week, just to mix things up, you decide to change the combination you pick. You are still exposed to the same risk; your action has not changed the odds you face. But you would experience enormous regret if your old numbers were to come up on the very week you switched.
Regret in Advance
This psychological trick that our minds play on us is central to the way we learn from experience. It became interesting to economists once they realized that regret isn’t just something that we can feel after the outcome of a decision is revealed to us, such as seeing our old lottery numbers come up on screen. It can actually influence the way we make decisions in advance. We frequently anticipate the regret we might feel if we make the wrong choice, and we consider this anticipation when we come to make a decision.
This theory of “anticipated regret” can make us act irrationally or in a biased fashion. It can both dissuade us from taking a decision that, from a probabilistic perspective, might be in our favour, and it can motivate us to take a decision that rationally might be a bad one.
A classic example of this is a bubble in the stock market. In an extended bull market, when financial asset prices are on the rise and many people anticipate that they will continue to rise, the fear of missing out can drive prospective investors to ignore warning signs about an impending crash and dive into the market. This enthusiasm can push asset prices much higher than their true value as indicated by their underlying fundamentals. When the bubbles ultimately burst, the reverse happens and people begin panic selling for fear of being left in the market when it bottoms out.
Should We Incorporate Regret into the Decision-Making Process?
There are plenty of ways for investors to eliminate (or at least reduce the influence of) regret by automating the investment process. For example, formula investing follows strict rules for investment decisions, and algorithms can be used to automate the execution of trades and their management.
But should we eliminate regret from the investment process? After all, it is a combination of the outcome of a decision and the way in which we personally relate to that outcome that in many instances really defines whether an investment decision can be consider a “good” one or a “bad” one.
To recognize regret is to acknowledge that we care about the consequences of our decisions; to admit it into our risk thinking process is to be able to mitigate the worst of its influence.
The fear of losing more money than we can afford, for example, may guide us towards more conservative positions than a traditional risk management technique such as mean variance (weighing risk, expressed as variance, against expected return) and Value at Risk (a statistic that measures how much a set of investments might lose during a given time period under normal market conditions). Vice versa, taking into account regret, or the fear of missing out, when choosing an investment option might be a useful prompt to take the leap of faith required to capture a large upside.
How to Utilize Regret to Our Advantage
We can account for regret in the decision-making process by insuring (or hedging) ourselves against those particular outcomes that cause the maximum regret. Often they are the extremes — the double-digit standard deviation events that might be almost impossibly improbable but which, if they occurred, would cause not just loss, but immense regret as well.
We may never rid ourselves of regret completely. In many situations, the potential for regret may exist no matter which scenario happens to occur. But by applying this psychological component of risk thinking to our more structured probabilistic generation of scenario trees, it is possible to truly know the bets we are taking. For our emotional response to a bet that’s won, lost, or simply missed out upon should be as much of a guide in the formal process of risk thinking as calculating the likelihood of each scenario and eliminating the ones with the highest negative numerical impact.
Sometimes hedging against the biggest regrets is cheap, other times not. But sometimes it’s worth paying whatever it takes to ensure peace of mind, even if it means walking away from a deal completely.
 Integrating regret into the decision-making process can be done quantitatively, as is outlined in Ron Dembo and Andrew Freeman. Seeing Tomorrow: Rewriting the Rules of Risk (Wiley, 2001), pp. 72–108. Put briefly, compute the difference in the horizon values between the portfolio and the benchmark under each scenario; the downside is zero whenever this number is positive, in which case we should feel happy about our portfolio; regret is the absolute value of the difference when this value is negative plus the psychological effect of the loss; average regret is the probability-weighted sum of the regrets under each scenario.