![]() Rocket Science Capital Advisors, LLC.
Registered Investment Advisor
Overconfidence and investing mistakes Generally, overconfident investors confuse a rise in the price one of their stocks with being smart. This is intensified by the tendency for people to make biased errors of causation. They attribute successful outcomes to their own skill and attribute negative outcomes to external factors or bad luck. They are far too willing to believe their judgments will be proven correct and will thus be led to take excessive risk in entering and closing positions, or they will simply trade too much. Here are some specific forms of overconfidence. For your edification, we also provide a simple test for you to evaluate your degree of overconfidence. Excessive trading A rational model of investing must conclude that there should be very little trading. If everyone is rational, and markets are efficient, then the only sensible investment strategy is to simply buy and hold. In contrast to this strategy, the volume of trading on global exchanges is very high. Empirical studies suggest individuals and institutions trade more than can be justified on rational grounds. One of the most important such studies was by Terrence Odean. Odean made an innovation in empirical financial testing when he obtained the rights to study trading activity in a large sample of (anonymous) accounts obtained from a national discount brokerage firm (still unrevealed). Some important results flowed from analyzing this database. First, Odean (1998) [ 1 ] found that the average gross return of stocks that investors in his sample bought, over the year after they bought them, was considerably lower than the average gross return of stocks that they sold, over the year after they sold them. In this sense they traded too much. Next, Barber and Odean (2000) [ 2 ] found that after carefully taking trading costs into account, the average return to investors in their sample was well below the return of standard benchmarks. These investors would have done a lot better if they had traded less. The underperformance was probably due to trading costs and lame security selection. Barber and Odean (2000) showed that the investors in their sample who traded the most earned by far the lowest average returns. Further, drawing on evidence that men are more overconfident than women, Barber and Odean (2001) [ 3 ] predict and confirm that men trade more and earn lower returns on average compared to women. An appealing behavioral explanation of such excessive trading is overconfidence: people probably believe that they have information strong enough to justify a trade, when in fact the information is too weak to warrant any action. Given Odean's evidence, the situation may be even worse: not only do people think that they have information when they don't, but they may even misinterpret valid information. It's often the information we are sure we know that's actually wrong that hurts our investing! Familiarity ("The devil you know vs. the one you don't") Familiarity breeds…comfort. We usually choose familiar gambles over unfamiliar ones having equal risks. Sometimes we even prefer a familiar, riskier bet or investment over a safer unfamiliar one. This shortcut can cause serious investment mistakes. The core idea is that seeking familiar instruments blinds us to rational diversification. For example, most American investors have believed in the future growth of USA stock markets and were quite averse to international investments in foreign markets, e.g., Russia. Yet the apparently very risky Russian markets have substantially out-performed USA markets for the past several years. Familiarity is another bias that can lead to poor portfolio diversification. Taking Excessive Risk and Faulty Diversification [ 4 ] Overconfidence leads investors to attempt to maximize future returns without fully analyzing the risks involved. A large body of evidence suggests that investors inappropriately diversify their portfolio holdings. This means that investors choose securities that are correlated in their returns, thereby eliminating the well-established virtues of diversification achieved through selecting uncorrelated assets. As another example, Benartzi and Thaler (1998) [ 5 ] find that when people diversify, they do so in a "naïve" fashion. The authors provide evidence that in 401(k) plans, many people seem to use the simple strategy of allocating equal portion of their money to each of the available investment vehicles, whatever those vehicles are. Of course, this simple strategy usually leads to the investor acquiring a set of correlated and thus non-diversified assets. We address this theme of how to choose uncorrelated assets directly on this site. Are you overconfident? Test yourself! As we've discussed, overconfidence can lead to poor portfolio diversification. One of the main characteristics of being overconfident is that you don't know it if you are. Your successful stock picking may be severely limited by thinking you know more than you do, or by simply not doing sufficient research. So, since almost everyone would deny being overconfident, take this really simple test and find out if you are. The idea is this: you are given a list of observable and well-known quantities, such as the length of the Amazon river. You are asked to estimate the true value of each quantity. Since you probably don't know the answer, you need to find an approximation, using your basic numeracy, and then select the closest one of the four possible answers. Given the huge range of possibilities covered by the four choices, your final choice will represent your confidence in the way you estimated the answer. Thus, if you are right 90% of the time, you should have 90% of your estimates correct. On the other hand, if you are overconfident, your answers will be mostly wrong. Here's a sample quiz. The only condition is that you don't go out and do the research or analysis, and that you respond quickly based on what's in your head now! Go to "Test for Overconfidence"
[ 1 ] Odean, Terrance (1998), "Do Investors Trade Too Much?," American Economic Review 89, 1279-1298 |