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  2. ASSA Annual Meeting
  3. 2027
  4. Preliminary Program
  5. Investor Behavior
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Investor Behavior

Paper Session

Sunday, Jan. 3, 2027 8:00 AM - 10:00 AM (EST)

Westin DC Downtown
Hosted By: American Finance Association
  • Chair: Baolian Wang, University of Florida

Limited Consideration Sets and Financial Decision-Making

Alex Imas
,
Carnegie Mellon University
Ye Jin
,
New York University-Shanghai
Yiqing Lu
,
New York University-Shanghai

Abstract

Economic models of financial decision-making typically assume that investors evaluate all available assets when forming their portfolios. Yet a growing body of work in psychology and behavioral economics suggests that attention is a scarce cognitive resource and that individuals rarely consider the full menu of available options. This paper provides the first large-scale evidence on how limited attention shapes portfolio choice by using unique, high-frequency data on investors’ actual consideration sets. Our proprietary dataset from a major Chinese financial platform records every asset page viewed by more than 13,000 retail investors, allowing us to directly observe which funds they attend to prior to trading. We complement these observational data with a controlled online experiment that exogenously directs attention. Across both settings, we find that (i) investors consider only a small subset of available options, and (ii) conditional on the assets they actually consider, their choices are substantially better than standard analyses suggest. We first document systematic deviations in consideration set formation relative to a simulated set randomly drawn from the available fund universe: observed sets are tilted toward lower-risk, higher-salience funds and are more concentrated within fund companies. Comparing chosen assets to the full universe reproduces the canonical finding that retail investors underperform. But comparing chosen assets to the investor’s consideration set reverses this conclusion: investors systematically pick the better-performing assets within the set they attend to. Our results show that mismeasured opportunity sets lead to overstated investor biases and that attention constraints play a central—and previously unmeasured—role in financial decision-making.

Divine Catalysts: Religion and Portfolio Choices

Maxime Bonelli
,
London Business School
Pulak Ghosh
,
Indian Insitute of Management-Bangalore
S. lakshmi Naaraayanan
,
London Business School
Purnoor Tak
,
London Business School

Abstract

This paper examines how religious framing influences equity investment and portfolio diversification. To do so, we exploit religiously-framed trading sessions held during a major festival emphasizing new beginnings and long-term prosperity as a cue. Individuals whose religion is associated with the festival invest significantly more during these sessions and buy new stocks, while others do not respond. We rule out alternative explanations including gambling motives and sentiment effects. Consistent with the emphasis on long-term prosperity, these new positions are held longer than other portfolio holdings. Consequently, they lead to persistent increases in equity portfolio size and mechanically increase diversification, without reducing risk-adjusted returns. Our findings highlight that religious framing can nudge individuals towards long-term investments, with implications for wealth accumulation.

The Rise of Retail Trading Since the Pandemic and Its Market Implications

Charles Jones
,
Columbia University
Lin Tan
,
Shanghai University of Finance and Economics
Xiaoyan Zhang
,
Tsinghua University
Xinran Zhang
,
Central University of Finance and Economics

Abstract

The marketable retail daily trading volumes in the U.S. stock market rise from $17 billion between 2018-2020 to $32 billion between 2020-2021, and stay high after the pandemic. We find government’s relief checks, the Fed’s monetary policies, retail investors’ rising attention towards trading apps and social media all contribute to the increase of retail trading. The retail order flows positively predict cross-sectional returns, with stronger predictive power during and after the pandemic. Higher retail trading is associated with wider future effective spreads, and these relations are weaker during the pandemic, suggesting that retail investors demand less liquidity during this special period.

Haven’t We Seen This Before? Return Predictions from 200 Years of News

AJ Yuan Chen
,
University of British Columbia
Gerard Hoberg
,
University of Southern California
Miao Zhang
,
University of Southern California

Abstract

Our historical record has become adequately long that newly arriving economic states often resemble historical states. We develop a framework that predicts future economic outcomes using the average outcomes following similar historical states. Using 210 million newspaper articles from 1815-2021, we construct SeenItRet, which strongly predicts aggregate stock market returns, 4–7% annualized, lasting up to two years. A virtue of our approach is that it uses economic principles to reduce a high-dimensional state space to an intuitive unidimensional predictor. The framework yields novel textual interpretations, predicts macro variables beyond returns, and performs better when historical states are more similar.

Discussant(s)
Daniel Graves
,
Harvard University
Tony Cookson
,
Pennsylvania State University
Xing Huang
,
Cornell University
Andrei Goncalves
,
Ohio State University
JEL Classifications
  • G1 - General Financial Markets