Overconfidence Intervals

According to many psychologists, overconfidence is the mother of all cognitive biases found in human beings.  An often cited study showed that 93% of American drivers rate themselves as better than the median.  Many people probably remember places that they have traveled, not by their experience, but with memories of how awful the driving was.

Other studies have shown that when people are asked to place 90% confidence intervals around estimates of specific quantities, hit rates were as low as 50%.  Overconfidence in the financial markets is most evident when markets are at both highs and lows.  In 2000, most investors were confident that technology stocks would make them millionaires, and  in 2009 most investors were confident that markets were going to zero and that the entire world was plunging into another Great Depression.

Today, we are faced with an interesting environment, where roughly half of the participants are very confident we are headed for a market crash, and the other half are convinced that the gains have only just begun with both factions using the current political backdrop as the reason.  One side could be proven right, and we are set up for a large move higher or lower, but both could also be wrong at the same time.  We could see a scenario develop much like the period in 2015-2016, where the U.S. stock markets stayed in a relatively tight range for about 14 months.

Overconfidence can also be found when people are making assumptions for their retirement plan goals, and often times investors are far too aggressive when estimating returns, and far too conservative in their estimates of how much they can afford to save/spend in the future.   If one was developing and implementing a financial plan in March 2009, using long term historic averages probably would have been okay, but now, after nearly ten years of the market going higher, using those same assumptions is likely on the aggressive side.  As shown below from The Behavior Gap, the cost of a mistake is in direct relationship with our level of overconfidence.

So how can we use the knowledge about overconfidence to make ourselves better investors?