In a previous Portfolio Minute, we looked at several topics that fall under the category of Behavioral Finance which includes common fallacies like anchoring and herding, among others. In this edition, we will continue this series by looking at a heuristic bias known as “representativeness bias”.
What is a heuristic?
Put simply, heuristics is the use of mental shortcuts that help us make decisions in the face of uncertainty and a lack of sufficient information. They are necessary to help speed up our decision-making process. In 1974, Daniel Kahneman and Amos Tversky identified three different kinds of heuristics:
– Representativeness and,
– Anchoring or adjustment
The representativeness heuristic is most often relied on when making probability judgements, by way of comparison to an existing prototype. In other words, would something or someone with the characteristic “A” almost always also has characteristic “B”, then we will tend to equate having “A” with having “B”.
Consider the following example:
John is an opera fan who enjoys touring art museums when on holiday. Growing up, he enjoyed playing chess with family and friends. Which job is John likely to have (assuming one of the following is true)?
A. John is a musician with a major symphony orchestra
B. John is a farmer
Our instinctive answer would be A because John’s description fits our prototype we hold about classic musicians.
How can this lead to bad decision making?
A representativeness bias
Looking back at our example involving John, answer A may be more intuitive, but B is more likely to be the correct answer simply because there are far more farmers in the world than there are classical musicians, and there is no reason to believe that a farmer cannot enjoy seeing art museums and listening to operas.
Moreover, if we had dug a little deeper to learn more about John, we may have found out that he likes to fix machinery, work with animals, and is an expert on soil samples. With his new information in hand, we could create a more accurate picture of John the human being rather than just John the opera and art lover.
How might Representativeness Bias hurt our investments?
One common example of this bias in action for investors is when we analyze the price chart of mutual funds, stocks, or bonds. Representative bias will lead us to see patterns even when the data is largely random, or too small of a sample size.
For example, let’s take a look at the magnified chart below:
If we exclusively focus on what happened between points 200 and 400 then we would likely think that the price of this security is going up. But if we take a step back and look at a longer period, the series looks like the price has stabilized, and may even be starting to go down. The chart alone does not give us enough data to base a decision on, and smaller “snippets” of the chart could distort the truth even further.
As investors, we tend to look at a limited set of data (mutual fund or stock performance over the last few months or maybe a few years) and conclude that something is likely to go up or down. If it has been going up it will keep going up, or if it is going down the price will continue to fall. This is why every investment comes with the warning label: “past performance is no indication of future results.” We know this is true, but our representative bias keeps trying to make us forget.
So, how do we at CH combat representativeness bias?
One of the best ways to overcome this bias is to take a step back and try to see the bigger picture. At CH we build deep and long-lasting relationships with our mutual fund portfolio managers and their teams. This access allows us to be in constant communication with our partners to better understand why their respective funds are behaving the way they are at any given moment in time. We can take the information they provide to us and combine it with our knowledge, resources, and experience to then judge if the current trends are an aberration, or if they are good predictors of what is likely to happen over the next few years.
Representativeness bias can affect all sorts of decisions in our lives. The heuristics behind them help us make decisions in an efficient and timely manner. At the same time, it is critical to understand how they work to know how to combat their weaknesses and potential biases. Behavioral finance is important and helps us to better understand how our clients think when it comes to investing. For us, at CH we want to use it to provide better service to our clients, and ultimately better long-term performance for their portfolios.
All the best,
Devin Gorgchuck, Wealth Advisor
& Your CH Financial Team