I have a friend — we’ll call her Ai — who has made some disastrous investment decisions. You see, Ai worked for a long time in the high tech sector, where Ai was exposed to a large number of tech companies and the people that ran them. Each new start-up Ai worked with was run by people who were smart, experienced and convinced that they were sitting on a gold mine. Many of these tech gurus were highly successful investors who spent considerable portions of their strategy meetings bragging about their past successes. And so when opportunities arose to get in early and stake my claim to some of their projects, Ai leapt.
And Ai lost money big-time.
Ai was not alone.
Last time, I described the self-enhancement bias and how it impacts what we know about the consumer experiences of our friends and acquaintances. I revealed that I once bought a Slap Chop that entirely failed to chop, yet I kept that to myself. I didn’t want anyone to know that I’d been such a fool. It’s likely that I wasn’t the first or last such fool among my circle of friends and acquaintances, but as of yet, it has never come up in conversation. More suckers throw down good money to get a chopper that doesn’t chop and which can’t withstand a decent slap.
But all that is probably no big deal in the long run. A few not-so-great purchases now and then isn’t normally disastrous. However, there is an arena in which the self-enhancement bias operates in a way that likely does cause people to make bad, even disastrous financial choices, and that is in the area of personal investing.
First, it is widely understood among researchers (but not among individual investors) that frequency of trading is directly linked to trading profitability: the more a person trades, the less money that person makes. Aside from catching the occasional wave when a company’s stock does incredibly well for a period of time, the best individual investment strategy is widely held by the experts to be that of buying shares in mutual funds that are indexed to the performance of the market as a whole, and simply holding them. The historical performance of the stock market as a whole is one of relatively steady (at least in the big picture) increases. In their study of the Taiwanese stock market trades from 1995 to 1998, researchers Barber, Lee, Liu and Odean found that individual investors using an active trading strategy lost the equivalent of 2.2% of Taiwan’s gross domestic product and 2.8% of total personal income — more than was spent in Taiwan during that time on clothing and footwear. In contrast, the professional traders gained 1.5% from their trading during the same period.
So, what drives people to trade? Well, good news about our friends’ trades turns out to be a key driver. For example, members of trading clubs who regularly meet (either in person or virtually) to discuss their trading experiences, tend to trade more frequently and lose more money compared to the market and to people who are passive traders (those who buy a mutual fund and sit on it). Here, it seems that the relative ease of trading, plus the influence of friends who enthusiastically describe their successes tends to drive increased trading, which in turn results in lower returns. As with Ai, when people hear about the success of others, they erroneously believe they can experience the same.
It also appears to be the case that the greater variance there is in a potential outcome, the more likely is the conversation to be biased. If the subject is flat screen TVs, the variance is probably not that big. One 47” flat-screen TV is likely to be very much like another. Some might be better than others, but the differences are relatively small. In such a case, people are not as inclined to bias their communication. One could always say, sure the colors aren’t as brilliant as yours, but I like how it looks on the wall, etc. In the case of stock trading, if all investors did more or less than same, there would be little bias. However, when there are some big losers and some big winners — and there always are, information flow strongly favors the big winners. The big losers tend to keep their mouths shut. As a result, we hear only about the big winners.
Hearing about others’ success tends to make us overconfident. It is a general human bias to attribute other people’s success to luck and our own to skill. In the case of investing, this may lead many people to think, If she can do it, I can certainly do it. And since you were probably just getting part of the story, your confidence is doubly unjustified.
Next, and very importantly, a very strong bias among individual investors is to believe that past performance is related to future performance. Despite the disclaimers in every stock prospective, we tend to believe that a stock can be hot (see here for a discussion of why we tend to see hot streaks where there are none). However, in general the fact that a stock or mutual fund has gone up two years in a row is unrelated to how it will do in year three. So, if you base your trades on the the successes your friends are claiming, you are probably jumping in too late anyway. If you have professional-level information about the stock or the fund, then you may be in the position to make a well-educated guess about its future performance. If your education in the matter consists of reading the Wall Street Journal every day and reading up on the company’s competition, you are probably are not qualified.
A grain of salt, please
So, where does that leave us? The research suggests that you should probably take the stories your friends and acquaintances tell about their investing success with a grain of salt or two. They probably aren’t — ok, maybe they aren’t — lying about their success. But they are probably not telling you the whole story. And, it’s probably too late to get a piece of their successful action anyway.
This blog post was written by Kerry Cunningham. Follow @kerryfc
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The article referenced above is: Barber, B., Y.-T. Lee, Y.-J. Liu, and T. Odean (2009). Just how much do individual investors lose by trading? Review of Financial Studies 22 (2), 609–632.