The Mentality of An Average Investor series will talk about the biases and heuristics of average investors. This series will mostly use interesting surveys conducted by readers to show common misconceptions and biases. Most of the material is taken from the behavior finance course taught by Ling Cen at University of Toronto. Although the entire series are written by me, I would like to credit my professor for the valuable life lessons and investment ideas in this series.
Study done by Kahneman and Tversky(1974) shows that:
When people try to determine the probability that an object A belongs to a class M, they often use representative heuristics:
-Rather than using A's own probabilities, people evaluate the probability by the degree to which A reflects the essential characteristics of M and how closely it resembles M. Although, this helps people make quicker decisions, it also generate some severe biases. It includes base rate neglect, and gambler's fallacy or hot hand fallacy. I will try to illustrate these using experiments. Keep in mind these experiments are for illustrative purposes only.
Linda is 31, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues surrounding equality and discrimination. Is it more likely that Linda is:
a) A bank clerk
b) A bank clerk and active in the feminist movement
Essentially, the correct answer should be A, because a bank clerk who is active in feminist movement is also considered as a bank clerk. However, our mind simply associates the description with "feminist movements" and put too much weight on the representativeness and too little weight on the base rate, making option B look like a no-brainer.
Question 1: Which of the following sequences is more likely to occur when a fair coin is tossed?
The answer is that both options are equally likely. However, classical theory suggests that most people think B is more likely because it is more "realistic." Another explanation is that people group random sequences like HTHTTH and HTTHTH all in the same mental category, thus skewing the possibility for any seemingly random sequence.
What is most interesting is that we observe the same representativeness heuristics in the financial market:
Shefrin and Staman's (1995) research shows that most investors think good companies provide stocks with higher returns. The survey specifically indicated investors tend to believe that stocks of big firms and growth firms have a high value. This applies to both institutional investors and retail investors as well, although it is because of different reasons.
Institutional investors like to hold good-looking, and fast growing stocks because of the pressure they face by sponsors to meet the performance of their benchmark portfolio in the short run. This caused them to "indexing" their portfolio with S&P 500 (NYSEARCA:SPY) and overweight on past winners.
Retail investors on the other hand like to own household names that they are familiar with such as Tesla (NASDAQ:TSLA), Apple (NASDAQ:AAPL), Netflix (NASDAQ:NFLX), and Amazon (NASDAQ:AMZN). These companies tend to perform nicely in the bull market and underperform in tumultuous market like today's.
The reason behind this is that investors like chasing the winner. Tesla (NASDAQ:TSLA), Netflix (NASDAQ:NFLX), Apple (NASDAQ:AAPL), and Amazon (NASDAQ:AMZN) were the biggest winners in S&P for the past few years. As we can see in the past month, NFLX, the best performer in 2015, dropped around 20%, while AMZN has dropped 15.9% (the graph does not include the aftermarket loss after missing earnings estimates yesterday), TSLA and AAPL is also down 17.14% and 12% respectively.
Barber and Odean (2008) research showed that retail investors tend to buy stocks with strong past price returns. This is consistent with representative bias. They like to associate the strong historical returns with these companies.
De Bondt and Thaler (1985) also finds that stocks that have been extreme past losers in the preceding 3 years do much better than extreme past winners over the subsequent 3 years.
Not only do retail investors like to chase past winners, they also like to chase past winner funds.
Another interesting thing that De Bondt also finds is that this also extrapolates into long-term earnings forecasts made by professional analysts. Analysts overreact in that they are much more optimistic about recent winners than they are about recent losers. Investors try to extrapolate future earnings growth based on past earnings growths which overestimate the value of the firm if earnings have been consistently growing and underestimate earnings of a value stock.
We are subject to our heuristics and environment when making decisions. And like making decisions, it is hard to dissociate ourselves from our investments whether that is in terms of personality, geography, or belief. We like to associate ourselves with seemingly "good" companies with a lot of growth potentials. However, "good" companies do not always equate to great investments as the earnings are likely to be overestimated and growth prospects are mostly priced in. History shows that over and over again people have fallen into the same investor behavior of chasing the winners and dumping the losers. The recent downfall of technology giants like Apple, Netflix and Amazon is a prime example of this, and I have committed this mistake myself many times in the past as well.
That being said, I believe that studying our human nature and other investors' biases can help us make better investment decisions and avoid pitfalls in our perceptions. In the world of investing, the biggest enemy is likely to be ourselves. I would like to leave you with the quote from Warren Buffett.
It seems to be some perverse human characteristic that likes to make easy things difficult. - Warren Buffett
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Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.
I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.