NBER Reporter: Summer 2002

Behavioral Finance

    The NBER's Working Group on Behavioral Finance met in Chicago on April 20. NBER Research Associates Robert J. Shiller, Yale University, and Richard H. Thaler, University of Chicago, organized this program:

    Christopher K. Polk and Paola Sapienza, Northwestern University, "The Real Effects of Investor Sentiment"

    Discussant: Jeremy C. Stein, NBER and Harvard University

    Nicholas C. Barberis, NBER and University of Chicago, Andrei Shleifer, NBER and Harvard University, and Jeffrey Wurgler, New York University, "Comovement"

    Discussant: Robert J. Shiller

    Sendhil Mullainathan, NBER and MIT, "Thinking Through Categories"

    Discussant: Jesus Santos, NBER and University of Chicago

    Tim Loughran, University of Notre Dame, and Jay R. Ritter, University of Florida, "Why has IPO Underpricing Increased Over Time?"

    Discussant: Ivo Welch, NBER and Yale University

    Amiyatosh K. Purnanandam and Bhaskaran Swaminathan, Cornell University, "Are IPOs Underpriced?"

    Discussant: Alon Brav, Duke University

    Mark Grinblatt, NBER and University of California, Los Angeles, and Bing Han, University of California, Los Angeles, "The Disposition Effect and Momentum"

    Discussant: Harrison Hong, Stanford University

    Do inefficiencies in the capital markets have real consequences? Or, are they simply wealth transfers from noise traders to arbitrageurs? Polk and Sapienza study firm business investment and find a positive relationship between investment and each of their three measures of mispricing (after controlling for investment opportunities and financial slack.) Consistent with their predictions, they find that firms with higher research and development intensity (suggesting less transparency and longer periods of information asymmetry) have investment that is more sensitive to mispricing.

    Barberis, Shleifer, and Wurgler distinguish three views of comovement among different traded securities. The traditional "fundamentals" view explains the comovement of securities through positive correlations in the rational determinants of their values, such as cash flows or discount rates. "Category-based" comovement occurs when investors classify different securities into the same asset class and then shift resources in and out of this class in correlated ways. "Habitat-based" comovement arises when a group of investors restricts its trading to a given set of securities, and then moves in and out of that set in tandem. The authors model each type of comovement, and then assess them empirically using data on stock inclusions into and deletions from the S&P 500 index. Index changes are noteworthy because they change a stock's category and investor clientele (habitat), but do not change its fundamentals. The authors find that when a stock is added to the index, its beta and R-squared with respect to the index increase, while its beta with respect to stocks outside the index falls. The converse happens when a stock is deleted. These results broadly support the category and habitat views of comovement, but not the fundamentals view. More generally, these non-traditional views may help to explain other instances of comovement in the data.

    Mullainathan presents a model of human inference in which people use coarse categories to make inferences. "Coarseness" means that, rather than updating continuously as suggested by the Bayesian ideal, people update or change categories only when they see enough data to suggest that an alternative category fits the data better. This simple model of inference generates a set of predictions about behavior. Mullainathan applies this framework to produce a simple model of financial markets which produces straightforward and testable predictions about the predictability of returns, comovement, and volume.

    In the 1980s, the average first-day return on initial public offerings (IPOs) was 7 percent. The average first-day return doubled to almost 15 percent during 1990-8, before jumping to 65 percent during the internet bubble years of 1999-2000. Part of the increase can be attributed to changes in the composition of the companies going public. Loughran and Ritter attribute much of the increase in underpricing, though, to previously latent agency problems between underwriters and issuing firms. They argue that the increase in valuations over time has caused issuers to be more complacent about leaving money on the table.

    Purnanandam and Swaminathan study the valuation of initial public offerings (IPOs) using comparable firm multiples. In a sample of more than 2000 IPOs from 1980 to 1997, the median IPO is overvalued at the offer by about 50 percent relative to its industry peers, they find. In the cross-section, overvalued IPOs earn 5 percent to 7 percent higher first day returns than undervalued IPOs, but earn 20 percent to 50 percent lower returns over the next five years. Overvalued IPOs temporarily exhibit higher sales growth rates but persistently earn lower profit margins and return on assets than undervalued IPOs over the next five years. This suggests that any projected growth opportunities implicit in the initial valuation fail to materialize subsequently. These results are not consistent with asymmetric information models of IPO pricing and rather support behavioral theories based on investor overconfidence.

    Prior research shows that many investors have a lower propensity to sell stocks on which they have a capital loss. This behavioral phenomenon, known as "the disposition effect," has implications for equilibrium prices. Grinblatt and Han investigate the temporal pattern of stock prices in an equilibrium that aggregates the demand functions of both rational and disposition investors. The disposition effect creates a spread between a stock's fundamental value -- the stock price that would exist in the absence of a disposition effect -- and its market price. Even when a stock's fundamental value follows a random walk, and thus is unpredictable, its equilibrium price will tend to underreact to information. Spread convergence, arising from the random evolution of fundamental values and updating of the reference prices, generates predictable equilibrium prices. This convergence implies that stocks with large past price run-ups and stocks on which most investors experienced capital gains have higher expected returns than those that have experienced large declines and capital losses. The profitability of a momentum strategy, which makes use of this spread, depends on the path of past stock prices. The authors find that stocks with large aggregate unrealized capital gains tend to have higher expected returns than stocks with large aggregate unrealized capital losses; this capital gains "overhang" appears to be the key variable that generates the profitability of a momentum strategy. When this capital gains variable is used along with past returns and volume to predict future returns, the momentum effect disappears.

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