NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
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Behavioral Finance

November 3, 2017
Nicholas Barberis of Yale University, Organizer

Augustin Landier, Toulouse School of Economics; Yueran Ma, Harvard University; and David Thesmar, MIT

New Experimental Evidence on Expectations Formation

In this paper, Landier, Ma, and Thesmar measure belief formation in an experimental setting where agents are incentivized to provide accurate forecasts of a random variable, drawn from a stable and simple statistical process. Using these data, they estimate an empirical model that builds on the recent literature on expectation dynamics: It nests rational expectations, but also allows for extrapolation and under-reaction. Their findings are threefold. First, the rational expectation hypothesis is strongly rejected in our setting, and researchers find little evidence or learning. Second, both extrapolation and underreaction patterns are statistically discernible in the data, but extrapolation quantitatively dominates. Third, their model coefficients are very robust to changes in experimental setting: They do not depend on process parameters, individual characteristics or framing. These large and stable deviations from rationality occur even though the forecasting exercise is simple and transparent.


Lawrence J. Jin and Pengfei Sui, California Institute of Technology

Asset Pricing with Return Extrapolation

>Jin and Sui develop a representative agent general equilibrium model with return extrapolation and recursive preferences. The model generates a large and countercyclical equity premium, a low and procyclical interest rate, a sizable and countercyclical Sharpe ratio, low interest rate volatility, strong excess volatility for equity, predictability of equity returns using price-dividend ratios, negative autocorrelations of equity returns, persistence of price-dividend ratios, as well as low correlations between consumption growth and stock returns. In addition, the model matches in magnitude the degree of return extrapolation and the investor memory structure derived directly from survey evidence. Their model can serve as a quantitative benchmark for the comparison between behavioral asset pricing models and more traditional models.


Ned Augenblick, the University of California at Berkeley, and Eben Lazarus, Harvard University

Restrictions on Asset-Price Movements Under Rational Expectations: Theory and Evidence

Augenblick and Lazarus examine restrictions on the variation in asset prices -- specifically, variation in risk-neutral beliefs expressed in option prices -- that must hold in a broad class of rational-expectations equilibria. They derive an upper bound for intertemporal movement in risk-neutral beliefs under rational expectations, and they show that this implies a lower bound on the curvature of utility (or, more generally, the slope of the stochastic discount factor) required to rationalize the marginal investor's beliefs. These restrictions have empirical counterparts, and researchers conduct empirical tests using risk-neutral distributions measured from S&P 500 index option prices. They find empirically that very high utility curvature is required to rationalize the behavior of risk-neutral beliefs, and in some cases, no stochastic discount factor in the class Augenblick and Lazarus consider is capable of rationalizing these beliefs. Under the theory they develop, this can be understood as providing evidence of overreaction to new information, though researchers consider the possibility that alternative explanations or option-market idiosyncracies could be driving our results. They conclude by considering the statistical and macroeconomic correlates of their findings and possible theoretical channels underlying these results.

Christian Leuz, the University of Chicago and NBER; Steffen Meier and Andreas Hackethal, Goethe University; Maximilian Muhn, Humboldt University; and Eugene F. Soltes, Harvard University

Who Falls Prey to the Wolf of Wall Street? Investor Participation in Market Manipulation

Manipulative communications touting stocks are common in capital markets around the world. Although the price distortions created by so-called "pump-and-dump" schemes are well known, little is known about the investors in these frauds. By examining 421 "pump-and-dump" schemes between 2002 and 2015 and a proprietary set of trading records for over 110,000 individual investors from a major German bank, Leuz, Meier, Hackethal, Muhn, and Soltes provide evidence on the participation rate, magnitude of losses, and the characteristics of the individuals who invest in such schemes. Their evidence suggests that participation is quite common and involves sizable losses, with more than 5% of active investors participating in at least one "pump-and-dump" and an average loss of nearly 30%. Moreover, researchers find that there are several distinct types of investors, some of which should not be viewed as simply falling prey to these frauds. Leuz, Meier, Hackethal, Muhn, and Soltes also find that portfolio composition and past trading behavior are better able to explain participation in manipulated stocks than demographics. Their analysis offers insights into the challenges associated with designing effective investor protection against market manipulation.


Laurent E. Calvet, HEC Paris; Claire Celerier, the University of Toronto; Paolo Sodini, Stockholm School of Economics; and Boris Vallee, Harvard University

Can Financial Innovation Solve Household Reluctance to Take Risk?

Using a large administrative panel of Swedish households, Calvet, Celerier, Sodini, and Vallee document the fast and broad adoption of retail structured products, an innovative class of contracts offering non-linear exposures to equity markets. Households investing in structured products differ from traditional stock market participants on key characteristics and significantly increase their equity exposures over the sample period. The introduction of retail structured products thereby raises both the likelihood and the extent of stock market participation, especially for households with lower wealth and IQ and of older age. The design of purchased products varies strongly with household characteristics, suggesting the importance of heterogeneity in preferences and financial circumstances. A simple portfolio choice model shows that household loss aversion best explains the demand for structured products and the empirical facts we observe. Their results illustrate how financial innovation can mitigate investor behavioral biases.


Francesco D'Acunto, Nagpurnanand R. Prabhala, and Alberto G. Rossi, the University of Maryland

The Promises and Pitfalls of Robo-advising

D'Acunto, Prabhala, and Rossi study a robo-advising portfolio optimizer that constructs tailored strategies based on investors' holdings and preferences. Adopters are similar to non-adopters in terms of demographics, but have more assets under management, trade more, and have higher risk-adjusted performance. The robo-advising tool has opposite effects across investors with different levels of diversification before adoption. It increases portfolio diversification and decreases volatility for those that held less than 5 stocks before adoption. These investors' portfolios perform better after using the tool.At the same time, robo-advising barely affects diversification for investors that held more than 10 stocks before adoption. It increases the fees they pay, but not their performance. For all investors, robo-advising reduces - but does not fully eliminate - pervasive behavioral biases such as the disposition effect, trend chasing, and the rank effect, and increases attention based on online account logins. Their results inform the optimal design of robo-advising tools, which are becoming ubiquitous all over the world.


 
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