What is Representativeness Heuristic?
Representativeness heuristic bias occurs when the similarity of objects or events confuses people’s thinking regarding the probability of an outcome. People frequently make the mistake of believing that two similar things or events are more closely correlated than they actually are. This representativeness heuristic is a common information processing error in behavioral finance theory.
Representativeness Heuristic Example
Let’s look at an example of information processing errors, commonly referred to as heuristic simplification. Let’s imagine the following scenario:
Consider Laura Smith. She is 31, single, outspoken and very bright. She majored in economics at university and, as a student, she was passionate about the issues of equality and discrimination.
Is it more likely that Laura works at a bank? Or, is it more likely that she works at a bank AND is active in the feminist movement?
Many people when asked this question go for option 2, that Laura works in a bank but is also active in the feminist movement. But that is incorrect. In fact, in giving that answer, they’ve actually been influenced by representativeness heuristic bias.
One of the things you want to think about is that you want to judge things strictly as they are statistically or logically, rather than as they merely appear.
The second option, “Laura works in a bank and is active in the feminist movement” is a subset of the first option, “Laura works in a bank.” Because of that fact, the second option can’t be more probable than the first. (The odds of Laura’s behavior(s) falling into a narrower subset must be statistically lower than the odds of her falling into the larger group of “bank employees”.)
This example is an excerpt from CFI’s Behavioral Finance Course.
Protecting against the Representativeness Heuristic
Let’s look at strategies to protect against this heuristic as an investor. You may want to consider keeping an investment diary. Write down your reasoning and then match it to the outcomes, whether good or bad.
In financial markets, one example of this representative bias is when investors automatically assume that good companies make good investments. However, that is not necessarily the case. A company may be excellent at their own business, but a poor judge of other businesses.
Another example is that of analysts forecasting future results based on historical performance. Just because a company has seen high growth for the past five years doesn’t necessarily mean that trend will continue indefinitely into the future.
Thank you for reading CFI’s guide on Representativeness Heuristic. Additional helpful resources include: