Behavioral Finance

Members of the NBER's Behavioral Finance Working Group met April 12-13 in Chicago. Research Associate Nicholas C. Barberis of Yale University organized the meeting. These researchers' papers were presented and discussed:

Niels Joachim Gormsen, University of Chicago, and Eben Lazarus, MIT

Expected Returns and Cash-Flow Growth

Gormsen and Lazarus find that most cross-sectional variation in expected stock returns can be summarized by cross-sectional variation in cash-flow duration. They show empirically and theoretically that most firm characteristics that predict high returns also predict a low cash-flow growth and thus a short cash-flow duration. A duration factor therefore explains the return to many equity anomalies, including factors based on valuation, profit, investment, low risk, and payout measures, both in the U.S. and globally. Using a novel dataset of single stock dividend futures, the researchers find evidence that this duration factor predicts returns exactly because it predicts the timing of cash flows and not because it predicts other firm characteristics. A simple theoretical framework can reproduce these findings and is consistent with the empirical properties of the aggregate market portfolio and the equity term structure.

Stefano Giglio, Yale University and NBER; Matteo Maggiori, Harvard University and NBER; Johannes Stroebel, New York University and NBER; and Stephen Utkus, Vanguard

Five Facts About Beliefs and Portfolios (NBER Working Paper No. 25744)

Giglio, Maggiori, Stroebel, and Utkus administer a newly-designed survey to a large panel of retail investors who have substantial wealth invested in financial markets. The survey elicits beliefs that are crucial for macroeconomics and finance, and matches respondents with administrative data on their portfolio composition and their trading activity. The researchers establish five facts in this data: (1) Beliefs are reflected in portfolio allocations. The sensitivity of portfolios to beliefs is small on average, but varies significantly with investor wealth, attention, trading frequency, and confidence. (2) It is hard to predict when investors trade, but conditional on trading, belief changes affect both the direction and the magnitude of trades. (3) Beliefs are mostly characterized by large and persistent individual heterogeneity, demographic characteristics explain only a small part of why some individuals are optimistic and some are pessimistic. (4) Investors who expect higher cash flow growth also expect higher returns and lower long-term price-dividend ratios. (5) Expected returns and the subjective probability of rare disasters are negatively related, both within and across investors. These five facts challenge the rational expectation framework for macro-finance, and provide important guidance for the design of behavioral models.

Can Gao, Imperial College London, and Ian Martin, London School of Economics

Volatility, Valuation Ratios, and Bubbles: An Empirical Measure of Market Sentiment

Gao and Martin define a sentiment indicator that exploits two contrasting views of return predictability, and study its properties. The indicator, which is based on option prices, valuation ratios and interest rates, was unusually high during the late 1990s, reflecting dividend growth expectations that in the researchers' view were unreasonably optimistic. The researchers interpret it as helping to reveal irrational beliefs about fundamentals. They show that the measure is a leading indicator of detrended volume, and of various other measures associated with financial fragility. The researchers also make two methodological contributions. First, they derive a new valuation-ratio decomposition that is related to the Campbell and Shiller (1988) loglinearization, but which resembles the traditional Gordon growth model more closely and has certain other advantages for the researchers' purposes. Second, they introduce a volatility index that provides a lower bound on the market's expected log return.

Klakow Akepanidtaworn, University of Chicago; Rick Di Mascio, Inalytics Ltd; Alex Imas, Carnegie Mellon University; and Lawrence Schmidt, MIT

Selling Fast and Buying Slow: Heuristics and Trading Performance of Institutional Investors

Most research on heuristics and biases in financial decision-making has focused on non-experts, such as retail investors who hold modest portfolios. Akepanidtaworn, Di Mascio, Imas, and Schmidt use a unique data set to show that financial market experts - institutional investors with portfolios averaging $573 million -- exhibit costly, systematic biases. A striking finding emerges: while investors display clear skill in buying, their selling decisions underperform substantially -- even relative to strategies involving no skill such as randomly selling existing positions -- in terms of both benchmark-adjusted and risk-adjusted returns. Across many specifications, foregone profits from underperformance in selling relative to a random-sell strategy are of a similar order of magnitude (though somewhat smaller) as the gains accrued from buying. The researchers present evidence that an asymmetric allocation of cognitive resources such as attention towards buying relative to selling can explain this discrepancy. Looking at events when attention is more likely to be evenly split between prospective buys and sells -- earning announcement days -- the researchers find that stocks bought and sold both outperform counterfactual strategies. They show that a heuristic process associated with limited attention can explain selling but not buying decisions. Assets with salient features in the form of extreme past returns are 50% more likely to be sold than those with zero benchmark-adjusted returns. Past returns have little predictive power for buying decisions. Lastly, the researchers show that such heuristics are costly, funds that are more prone to use heuristic strategies exhibit the most underperformance in selling.

Jordan Brooks and Michael Katz, AQR Capital Management, and Hanno Lustig, Stanford University and NBER

Post-FOMC Announcement Drift in U.S. Bond Markets (NBER Working Paper No. 25127)

The sensitivity of long-term rates to short-term rates represents a puzzle for standard macro-finance models. Post-FOMC announcement drift in Treasury markets after Federal Funds target changes contributes to the excess sensitivity of long rates. Mutual fund investors respond to the salience of Federal Funds target rate increases by selling short and intermediate duration bond funds, thus gradually increasing the effective supply to be absorbed by arbitrageurs. The gradual increase in supply generates post-announcement drift in longer Treasury yields, which spills over to other bond markets. Brooks, Katz, and Lustig's findings shed new light on the causes of time-series-momentum in bond markets. A model in which mutual fund investors slowly adjust their extrapolative expectations of future short rates after a target change can qualitatively match the dynamics of yields and fund flows.

Jessica Wachter, University of Pennsylvania and NBER, and Michael J. Kahana, University of Pennsylvania

A Retrieved-Context Theory of Financial Decisions

Studies of human memory indicate that features of an event evoke memories of prior associated contextual states, which in turn become associated with the current event's features. This mechanism allows the remote past to influence the present, even as agents gradually update their beliefs about their environment. Wachter and Kahana apply the context framework from the memory literature to four problems in asset pricing and portfolio choice: over-persistence of beliefs, providence of financial crises, price momentum, and the impact of fear on asset allocation. These examples suggest a recasting of neoclassical rational expectations in terms of beliefs as governed by principles of human memory.

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