The Example Rule

The example rule has profound implications for the way we think about risk. Simply put, it suggests that if we can easily recall an example of something, then the perceived risk is greater.



It is easy to see how this rule survived the process of natural selection. Imagine a caveman walking in a forest.   He sees another member of his tribe mauled by a bear. It serves that caveman well to remember the incident, as he stands a better chance of survival if he avoids that part of the forest. Conversely, if he knows of another part of the same forest where he has no example of anyone being attacked, the odds are that this part of the jungle is safer.

Levels of Earthquake Risk - California

Modern day examples include studies of insurance rates in earthquake prone areas such as California. Research shows that demand for (and price of) insurance is greatest immediately after an earthquake. This is because people can easily recall an example and so judge risk to be higher.  Similarly, the price of insurance decreases over time, as the last earthquake becomes a distant memory.




But this is inherently irrational. These people are thinking with their gut. If they thought with their heads, they would realise that statistically speaking, the chance of back-to-back earthquakes occurring is low and it makes sense to wait until the price comes down.  If this market behaved rationally, we would see insurance rates rising when there has been a long interval between earthquakes; surely another one is due soon.




Applying this rationale to my theme, should enough time pass between bubbles such that investors cannot quickly recall an example of the last one and the devastation it caused, their assessment of the risk involved may be greatly impaired.   Combine this effect with that of confirmation bias, traders could conceivably convince themselves that there isn't a bubble in the first place and the result is highly risky behaviour, contributing to the expansion of a financial bubble.