« Back to Results

Behavioral Finance and Asset Pricing

Paper Session

Friday, Jan. 7, 2022 10:00 AM - 12:00 PM (EST)

Hosted By: American Finance Association
  • Chair: Samuel Hartzmark, University of Chicago

Model-Free and Model-Based Learning as Joint Drivers of Investor Behavior

Nicholas Barberis
,
Yale University
Lawrence Jin
,
California Institute of Technology

Abstract

In the past decade, researchers in psychology and neuroscience studying human decision-making have increasingly adopted a framework that combines two systems, namely "model-free" and "model-based" learning. We import this framework into a simple financial setting, study its implications, and link it to a wide range of applications. We show that it provides a foundation for extrapolative demand and experience effects; resolves a puzzling disconnect between investor allocations and beliefs in both the frequency domain and the cross-section; and can help capture the primary role of individual fixed effects in explaining the variation in investor beliefs. More broadly, the framework offers a way of thinking about investor behavior that is grounded in recent evidence on the computations that the brain makes when estimating the values of different courses of action.

Currency Anomalies

Sohnke Bartram
,
University of Warwick and CEPR
Leslie Djuranovik
,
University of Warwick
Anthony Garratt
,
University of Warwick

Abstract

This paper is the first to study the cross-section of currency excess return predictors to explore alternative explanations for their existence. Using real-time data, quantitative currency trading strategies are profitable during in-sample and out-of-sample periods, even after transaction costs and comprehensive risk adjustments. However, (risk-adjusted) profits decrease substantially after the publication of the underlying academic research. In line with predictor profits reflecting mispricing, the decline is greater for strategies with larger in-sample profits and lower arbitrage costs. Moreover, the effect of risk adjustments on trading profits is limited, and signal ranks and alphas decay quickly. While analysts’ currency forecasts are inconsistent with currency predictors, analysts update their forecasts quickly to incorporate lagged predictor information. The results suggest that market participants learn about mispricing from academic publications, while contributing to it when following analysts’ forecasts.

Risk Aversion Propagation: Evidence from Financial Markets and Controlled Experiments

Xing Huang
,
Washington University in St. Louis
Nancy Xu
,
Boston College

Abstract

While the time variation in investor risk appetite is widely examined, there is scant research on how investor risk appetite may respond in an international context. We study risk aversion (RA) propagation from US to other major developed economies using both financial market data and controlled experiments. By exploiting daily financial market and news data between 2000 and 2017, we identify US risk aversion events -- both high and low -- and show that the international pass-through of US high RA events is significantly higher (61%) than that of US low RA events (43%), suggesting asymmetric US risk aversion propagation. Next, in our experiment, non-US subjects when primed with a US financial bust shock exhibited asymmetrically lower positive emotion, higher negative emotion and higher risk aversion than those primed with a US boom shock. The foreign nature of negative shocks may change emotions more than that of positive shocks, hence resulting in asymmetric risk aversion propagation. Our evidence shows that such an ``emotion'-related mechanism explained up to 20% of the asymmetry.

Can Agents Add and Subtract When Forming Beliefs? Evidence from the Lab and Field

Pascal Kieren
,
University of Mannheim
Jan Müller-Dethard
,
University of Mannheim
Martin Weber
,
University of Mannheim

Abstract

Bayes’ Theorem has an implicit, fundamental rule of how subjects should incorporate informationally equivalent signals of opposite direction: two opposite-directional signals should cancel out such that prior beliefs remain constant. In this study, we test whether agents always follow this simple counting heuristic. We find that this is not the case. Whenever a sequence of signals that go in the same direction is interrupted by a signal of opposite direction, agents violate the simple counting heuristic and strongly overreact to the signal of opposite direction. In contrast to that, subjects correctly follow the counting heuristic whenever opposite-directional signals alternate. Building on our experimental findings, we empirically analyze announcement and post-announcement stock return reactions. In line with our experimental evidence, we identify that initial stock reactions are significantly more extreme for opposite-directed earnings surprises than for same-directed earnings surprise.
Discussant(s)
Joshua Schwartzstein
,
Harvard University
Wenxin Du
,
University of Chicago
Yueran Ma
,
University of Chicago
Anastassia Fedyk
,
University of California-Berkeley
JEL Classifications
  • G3 - Corporate Finance and Governance