Distinguishing the Effect of Overconfidence from Rational Best-Response on Information Aggregation
Review of Financial Studies, 2009
In this paper I study -- theoretically and in a laboratory setting -- a new bilateral game in which subjects estimate the value of an asset and have incentives to learn from each other. By inducing subjects to overconfidence is some treatments, I find that overconfidence has a causal effect on the dispersion and convergence of these estimates. Interestingly, I show that even when subjects are not overconfident, qualitatively results may be observed due to subjects’ strategic response to each other’s errors.
Predicting Risk from Financial Reports with Regression
Proceedings of the North American Association for Computational Linguistics Human Language Technologies Conference, Boulder, CO, May/June 2009
with Dimitry Levin, Bryan Routledge, Jacob Sagi, and Noah Smith
In this paper, we take a novel approach to predicting long-horizon firm volatility. Instead of relying on statistical properties of returns, we extract the information relevant for firm volatility from the Management Discussion and Analysis (“MD&A”) section in annual reports by applying machine learning to the text. We find that a model that uses both past volatility and text data significantly outermost out-of-sample standard benchmarks.
Securities Auctions under Moral Hazard: An Experimental Study
Review of Finance, 2009
with John Morgan
We study, both theoretically and in the lab, the performance of debt and equity auctions in the presence of both private information and hidden effort. We show that the revenues to sellers in debt and equity auctions differ systematically depending on the returns to entrepreneurial effort. Using a controlled laboratory experiments we test the model’s predictions and find strong support for the theory.
Coordination in the Presence of Asset Markets
American Economic Review, 2011
with Anthony Kwasnica and Roberto Weber
In this paper, we explore experimentally the influence of two-sided futures asset markets on behavior and outcomes in an economic activity characterized by multiplicity of equilibria (a coordination game with Pareto-ranked equilibria). Across several experiments, we find that the presence of an asset market has a negative effect on output (efficiency) and that this cannot be explained entirely by the distorted payoffs of a portfolio incentive effect.
Investor Inattention and the Market Impact of Summary Statistics
Management Science, Special Issue on Behavioral Economics and Finance, 2012
with Thomas Gilbert, Lars Lochstoer, and Ataman Ozyildirim
We show that U.S. stock and Treasury futures prices respond sharply to recurring stale information releases. In particular, we identify a unique macroeconomic series — the U.S. Leading Economic Index (LEI) — which is released monthly and constructed as a summary statistic of previously released inputs. We show that a front-running strategy that trades S&P 500 futures in the direction of the announcement a day before its release and then trades in the opposite direction of the announcement following its release generates an average annual return of close to 8%.
Trading Complex Assets
Journal of Finance, 2013
with Bruce Ian Carlin and Richard Lowery
We perform an experimental study to assess the effect of complexity on asset trading. We find that higher complexity leads to increased price volatility, lower liquidity, and decreased trade efficiency especially when repeated bargaining takes place. This is caused by complexity altering the bidding strategies used by traders, making them less inclined to trade, even when we control for estimation error across treatments. As such, it appears that adverse selection plays an important role in explaining the trading abnormalities caused by complexity.
Business Microloans for U.S. Subprime Borrowers
Journal of Financial and Quantitative Analysis, 2016
with Cesare Fracassi, Mark J. Garmaise, and Gabriel Natividad
We show that business microloans to U.S. subprime borrowers have a very large impact on subsequent firm success. Using data on startup loan applicants from a lender that employed an automated algorithm in its application review, we implement a regression discontinuity design assessing the causal impact of receiving a loan on firms. Startups receiving funding are dramatically more likely to survive, enjoy higher revenues, and create more jobs
Is Investor Rationality Time Varying? Evidence from the Mutual Fund Industry
Behavioral Finance: Where do Investors Biases Come From?, Itzhak Venezia [ed.], World Scientific Publishing Co., 2016
with Vincent Glode, Burton Hollifield, and Marcin Kacperczyk
We provide novel evidence that mutual fund returns are predictable after periods of high market returns but not after periods of low market returns. Performance predictability is more pronounced for funds catering to retail investors than for funds catering to institutional investors, suggesting that unsophisticated investors make systematic mistakes in their capital allocation decisions.
Information, Trading, and Volatility: Evidence from Firm-Specific News
Review of Financial Studies, Volume 32, Issue 3, 1 March 2019
with Jacob Boudoukh, Ronen Feldman, and Matthew Richardson
What moves stock prices? Prior literature concludes that the revelation of private information through trading, and not public news, is the primary driver. We revisit the question by using textual analysis to identify fundamental information in news. We find that this information accounts for 49.6% of overnight idiosyncratic volatility (vs. 12.4% during trading hours), with a considerable fraction due to days with multiple news types. As applications, we use our measure of public information arrival to reinvestigate two important contributions in the literature related to individual R2s of stock returns on aggregate factors, namely Roll (1988) and Morck, Yeung and Yu (2000).
Fake News: Evidence from Financial Markets
with Tobias Moskowitz and Marina Niessner
Using a unique dataset of fake stock promotion articles prosecuted by the Securities and Exchange Commission, we examine the impact of fake news. In addition, we use a linguistic algorithm to detect deception in expression for a much larger set of news content using the fake articles as a training sample. We find increased trading activity and temporary price impact from fake news about small firms, but no impact for large firms. Using the SEC investigation as a shock to investor awareness of fake news, we find a marked decrease in reaction to news, particularly content deemed less authentic, but also legitimate news. These findings, including the indirect spillover effects on other news, are most pronounced for small firms with high retail ownership and for the most circulated articles. Understanding the motivation behind the fake articles, we find that small firms engage in corporate actions and insider trading designed to profit from the fake articles, consistent with concerns of coordinated stock price manipulation. No such patterns are observed for large firms. The setting offers a unique opportunity to quantify the direct and indirect impact of fake news.
[*NEW*] Uncertainty Shocks and Personal Investment: Evidence From a Global Brokerage
with Rawley Heimer and Nancy Xu
We use novel data from a global retail brokerage to study how shocks to uncer- tainty affect personal investment around the world. We consider three empirical uncertainty shocks that have been proposed by the literature — terrorism, natu- ral disasters, and large stock price jumps. We then consider how within-country uncertainty shocks affect investment and delegation in global assets on the broker- age. Importantly, the within-country uncertainty shocks (e.g., a natural disaster in Spain) are unlikely to affect world asset fundamentals (e.g., the SPX500). This allows us to isolate the effects of uncertainty shocks on personal risk aversion from their effects on asset fundamentals. We find that uncertainty shocks have scant effects on personal investing. They primarily affect delegation to asset managers on the brokerage, but that the direction of the effects depends on the type of uncertainty shock. Investors increase their delegation by 5% following terrorist activity and reduce delegation by 8% following positive and negative stock market jumps. These findings suggest that the exogenous uncertainty shocks proposed by the literature have heterogeneous effects on individual investment.
[*NEW*] The Asymmetry in Responsible Investing Preferences
with Jacquelyn Humphrey, Jacob Sagi, and Laura Starks
We run an experiment to elicit stock allocation and probability assessment under three treatments: Neutral, as in Kuhnen (2015); Positive, where a non-profit organization benefits proportionately from the subject’s stock allocation outcomes; Negative, where a non-profit organization benefits inversely from the subject’s stock allocation outcomes. The design attempts to mimic the setting of, and incentives behind, responsible investment (RI). We find that probability perception and allocations adjusted for probability perceptions change significantly between the neutral and negative treatment. Differences are more muted between the positive and neutral treatments. This unambiguously demonstrates that a taste for RI can lead to significantly different investment choices. In addition, both the impact of treatment on probability perceptions and the asymmetry between positive and negative treatments suggest important directions for accurately modeling tastes for RI.
Aggregate Sentiment and Investment: An Experimental Study
with Donja Darai, Anthony Kwasnica, and Roberto Weber
Sentiment indices, such as measures of consumer confidence, are often discussed as potential indicators of future investment, consumption and growth. However, documenting a causal relationship between consumer confidence and output using field data has been challenging. We rely on the high degree of control afforded by laboratory environments to experimentally test a simple model of investment with complementarities and time-varying fundamentals. Our experiment manipulates the presence of aggregate confidence measures to test both how they reflect available information and how they influence future output. We find that an aggregate sentiment measure can be as effective as a highly precise exogenous public signal in coordinating behavior on more efficient equilibria. Furthermore, our analysis indicates that the confidence measure also impacts expectations by influencing beliefs about aggregate investment.
Information Environment and the Geography of Firms and Investors
with Gennaro Bernile and Johan Sulaeman
We develop a model linking stock ownership and returns to the distribution of private information and quality of public information. Supporting the model, we find that the firm’s information environment affects investors’ propensity to hold and trade its stocks, but its effects hinge on investors’ access to private information. Nearby investors with potential access decrease their holdings when private information becomes more dispersed and public information quality improves, whereas distant investors display opposite patterns.
Work in Progress
Collective Self Deception
with Florian Schneider and Roberto Weber
We run a set of experiments that involve group tasks to understand the difference between self-deception of individuals relative to that of groups.
With Jacob Sagi
We apply machine learning to the text contained in annual reports to develop an-ante measure of firm-level CAPM betas.