Why Markets Miss
Are we really suggesting that a company should abandon its stars and focus on its dogs? We don’t rule out the possibility, especially if the dogs can be rehabilitated in line with the company’s core strategy. Superior value creation comes from changes in future performance. What if the markets have inherent biases in predicting performance?
The strategy of loving your dogs may be intuitively difficult to swallow for many, but it is supported by an economic field of study — behavioral finance — that has come into vogue over the last decade. Behavioral finance is founded on the precept, as economist James Montier puts it, that “not only do investors make mistakes, but they do so in a predictable fashion.” Day traders, for example, routinely display overconfidence; they trade with high turnover but low returns. And as Nobel Prize–winning economists Amos Tversky and Daniel Kahneman articulated in their “law of small numbers,” people are likely to overestimate the similarities between a small group they know and the larger population — an error that leads to faulty predictions of the behavior of markets and prices. Irrationality occurs even with highly trained specialists, such as professional investors, or, as Dr. Kahneman puts it, when “people who are explicitly trained to bring [rational] thinking to problems don’t do so, even when they know they should.”
Guided by these types of insights, behavioral economists have developed a robust set of models of market behavior. These models represent an alternative to conventional economic models, which are logically consistent but fail to account for the real behavior of capital markets because they assume that all markets are efficient, all investors are rational, and all relevant information about securities is reflected in their prices. Because behavioral finance explains the gaps between ideal valuations and actual prices, investors have begun to use this theory to exploit these mismatches and thus capture additional value. (See “Derivative Wisdom,” by Rob Norton.)
Although behavioral finance is used by a growing number of fund managers to guide their purchases, another potential application has largely gone unnoticed: its use as a guide to corporate strategy decisions. The same kind of behavioral analysis can help corporate executives better understand and manage their own “portfolios” — the businesses or business units that make up their companies. Executives who understand behavioral finance will capture more shareholder value from businesses that have previously been regarded as unworthy of much attention.
Consider, for example, how behavioral analysis can explain the poor track records of capital markets as predictors of the true value of businesses. Investors don’t make their choices through purely rational processes or with complete information; they allow emotions to affect their decisions, they misinterpret data, and they are shortsighted in estimating the long-term viability of an enterprise. All of this can lead to a misunderstanding of the future potential of a security (or other asset).
These “flaws” are pervasive enough to be systematic in a population of investors. Enough people make decisions with enough irrationality that individual mistakes, however minor, combine to lead to routine mispricing of securities and other capital assets. Investors overvalue “glamour stocks,” those in vogue as evidenced by their high market-to-book value ratios or high price-to-cash-flow ratios. And they undervalue “value stocks” — identified by such measures as low market-to-book value ratios or low price-to-cash-flow ratios — even though a vast amount of research conducted over the past few years has shown conclusively that a portfolio of “value” stocks will consistently outperform their more popular “glamorous” counterparts.
Research shows that this pattern exists both over time and in all major capital markets. While academics continue to investigate the rationale for this dynamic, a consensus has emerged about its relationship to two phenomena. First, investors are people, not rational machines, and therefore display “expectation biases” about future performance. If they can recall that a stock has done well in the past, they are more likely to expect it to do well in the future, and they invest accordingly.