Representativeness Heuristic

When the similarity of objects is confused with the probability of an outcome

What is Representativeness Heuristic?

Representative bias occurs when the similarity of objects is confused with the probability of an outcome, meaning people incorrectly believe that two common-sounding events are believed to be more closely correlated than they are. This representativeness heuristic is a common information processing error in behavioral finance theory.


Representativeness Heuristic


Representativeness Heuristic Example

Let’s look at an example of information processing errors, commonly referred to as heuristic simplification. So let’s imagine the following scenario:


Consider Laura Smith. She is 31, single, outspoken and very bright. She majored in philosophy at university, and as a student, she was deeply concerned with issues surrounding 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, what you’ve done is you’ve actually been influenced by representative bias.

One of the things you want to think about is that you want to judge things as they are statistically, or logically, rather than as they 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.” As a result, the second option can’t be more probable than the first. However, people will often judge events. Again, investors will judge events often as they appear rather than how likely they really are.

This example is an excerpt from CFI’s Behavioral Finance Course.


Protecting against Representativeness Heuristic

Let’s look at strategies to protect against this heuristic. You may want to consider keeping an investment diary. List down your reasoning and then match it to the outcomes whether they are good or bad.

In financial markets, one example of this representative bias is when investors often automatically assume that good companies make good investments. However, that is not necessarily the case.

Another example is when analysts forecast future results based on historical performance. Just because a company has seen high growth for the past five years doesn’t necessarily mean that it is going to continue for the next five or ten years.


Additional Resources

Thank you for reading this guide to the representativeness heuristic and its place in financial decision making. To learn more, check out CFI’s Behavioral Finance Course.

Additional helpful resources include:

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