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The Overconfident Investor Moves Markets

Jason Hull

How many of you think that you're a better than average driver? Raise your hands. About two-thirds of you will have raised your hands -- nearly a statistical impossibility, since, if that was true, the remaining third of people who are below average would be so bad that the roads would be impassable due to the multitude of wrecks caused by the exceptionally poor drivers.

It's not a surprise that, in general, we think that we can do things better than the "average" person or, sometimes, anyone else, period. Humans suffer from a psychological bias called self-attribution. When things go well, we attribute results to our own actions. If things don't go our way, then we blame bad luck. Additionally, when things do go our way, success further reinforces our belief that we truly have the Midas touch, minus all of the bad parts about turning our loved ones into gold. Our lives, particularly when we don't really think about what's happening, are a cycle of ego boosting with very few instances of ego deflating, since we're so good at attributing failure to any factor other than ourselves.

Because we so rarely suffer from blows to our ego, over time, we become overconfident about our abilities. We fool ourselves into believing that we're experts in areas where we aren't necessarily skilled, and, furthermore, we look for signals as signs which might not necessarily be true.

An oft-cited paper published in The Journal of Finance, "Investor Psychology and Market Reactions" by Kent Daniel, David Hirshleifer and Avanidhar Subrahmanyam, shows how this overconfidence plays out in the stock market. It creates a counterintuitive situation: markets overreact in times when it should not and underreact in times when it should move more.

Let's look at some examples of how this plays out.

The first example is when there are short-term earnings surprises. If a company reports an upside earnings surprise, then, if the market was rational, the new earnings would quickly be incorporated into the stock price, and the price should stabilize. Instead, what happens is that the overconfident investors see the earnings surprise, say "I knew it!" and buy more, continuing the trend of price drift in the same direction after the earnings announcement.

A second example involves the way markets overreact to news. In general, if there is a major news event about a company, a stock's price will get out of line with its industry peers as measured by the price-to-earnings ratio or the PEG ratio (that's price to earnings, divided by the growth rate forecast by analysts). In a rational market, the price would return quickly to be in line with expectations relative to its industry and peer group even after good news appears. Instead, because of investor overconfidence, investors hold onto their stock purchases and refuse to acknowledge contrary information, such as the P/E ratio being too high for a given stock, even as the stock slowly drifts back towards being in line with its industry comparables. For everyday investors, this is dangerous in two ways: Overconfidence caused the overreaction in the first place, and overconfidence causes underreaction as shares return to a more rational price.

The third example involves growth stocks compared to value stocks. The previously mentioned momentum and earnings drift is more pronounced for growth stocks since they're often harder to value and usually more dependent on intangibles like research investments panning out than value stocks. Thus, it takes a long time for investors to receive feedback on their initial investment theses - how long will it take for a new drug to be approved by the government or for a company to successfully launch a passenger ship into space, for example? When investors receive feedback quickly, they tend to be more realistic in their expectations; when the feedback loop is long, overconfidence takes over in the absence of other information.

Until the stock market is completely run by computers, it is going to exhibit behavioral biases. Whether or not you can take advantage of those biases is another issue altogether. After all, while you may be able to spot a trend such as earnings drift, it's impossible to tell whether or not it will happen for a given stock, the magnitude of the effect if it does occur, or how long the effect will happen before rationality in pricing takes over.

Jason Hull is a candidate for the CFP(R) Board's certification, is a Series 65 securities license holder, and owns Hull Financial Planning.

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