Risk and investing: how we sabotage ourselves
by Alyssa Hodder
Alyssa Hodder attended a breakfast session hosted by CIBC Mellon where IA CEO Damian Handzy presented how lessons from Behavioral Economics can lead to better Risk Management practices.
You can read the full text here at Benefits Canada
Investing always has its risks, but does the way we’re predisposed to think and act affect our ability to mitigate them?
The answer is an unequivocal yes, according to Dr. Damian Handzy, president and CEO of Investor Analytics, at a breakfast session on risk management hosted by CIBC Mellon.
Using research from behavioural economics and cognitive science, he examined six natural biases that cloud our judgment when it comes to investing and managing risk.
1) Representation bias – Handzy explained that human beings have evolved to believe stories with rich details over those that are more general. Yet from a risk management perspective, the more specific the scenario is, the less likely it is to occur.
The danger is that we may over-specify when creating scenarios to stress test a portfolio. “A lot of our clients are putting in a lot of different stresses,” he said. “The probability that all those things will happen just that way decreases with each specification added to the scenario. So it’s better—it’s more likely—if you break these apart into smaller scenarios but consider all of them.”
2) Default option – We also have a tendency to choose the default when one is available, since it contains the implicit assumption of an endorsement. For example, Handzy pointed out that we usually trust the defaults identified by a manufacturer rather than making our own decisions—partly because it’s easier to do so.
“When it comes to risk, you have to be really careful,” he cautioned. “Because chances are, the defaults that are in a risk system are not there because it’s easier for you, but because it’s easier for the programmer.” In other words, risk systems should not function on auto-pilot. Like any other aspect of risk management, they require close scrutiny.
3) Risk aversion – Another common inclination is to be risk-averse with gains yet risk-taking with losses. For example, when asked to choose between a 100% chance of receiving $25,000 and a 25% chance of receiving $100,000, most people will take the $25,000. But when they have to choose between a 100% chance of having to pay $25,000 or a 75% chance of having to pay $100,000, most people will opt for the 75% chance.
In practice, this behaviour limits upside potential while also allowing for large losses in an investment portfolio. “This is a gut instinct,” Handzy explained. “There are very good evolutionary explanations as to why this is. In an environment where the resources are scarce and you don’t know where your next meal is coming from…you hoard things. You value that which you have over that which you might have.”
4) Patternicity – Handzy also noted that we often find patterns in events, even where—or especially where—none exist. However, he believes we can use this bias effectively in risk management. For example, when examining a series of data points to determine beta (which measures the volatility of an investment or portfolio relative to the market on the whole).
“If many different lines fit the beta, then the beta isn’t really accurate,” he said. “It’s not a good fit. You shouldn’t use it.”
5) Framing bias – Handzy used a medical example to show how the positioning of different options can affect our judgment: when physicians state the risks of a necessary medical procedure in terms of a 1% mortality rate instead of a 99% survival rate, people are more likely to decline the procedure.
Applying this to investment risk, “if you’re looking at a value at risk (VAR) at 95%, that means, by definition, that your portfolio is not supposed to lose more than that number 95% of the time,” he explained. “In other words, 5% of the time, it’s supposed to be worse than that loss.” Yet investors sometimes insist on using a risk measure that can never be exceeded—the absolute worst-case loss. “How do you know if it’s right?” Handzy asked. “If a risk measure is not exceeded, you can’t test it.”
6) The Monty Hall problem – Finally, our instincts can work against us when we make investment decisions. Handzy gave the infamous Monty Hall puzzle as an example.
Suppose you are a contestant on a game show, and you must choose between three closed doors. Behind one of the doors is cash; behind the other two doors are booby prizes. Once you’ve made your initial choice, the host opens one of the remaining doors. A booby prize is behind it. You then have the option to stay with your original choice or choose the remaining closed door. Should you switch?
While you might think it doesn’t make a difference—that your chances are 50/50 either way—that’s not the case, Handzy explained. If you stick with your original choice, the probability of finding the cash is 1/3. But if you make a switch, the probability is 2/3, counterintuitive though this may be.
Handzy’s overall message is that while we may not be able to overcome all of the biases that hinder us, we should at least be aware of them.
“Don’t feel bad that you don’t get probabilities—nobody does,” he said. “But that’s why it’s important that you understand how these tools work—how we misinterpret this information and how we apply that to what we do for a living.”
