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Learning in and from Financial Markets

Paper Session

Friday, Jan. 6, 2023 8:00 AM - 10:00 AM (CST)

Sheraton New Orleans, Rhythms II
Hosted By: American Finance Association
  • Chair: Michael Sockin, University of Texas-Austin

Trading Ahead of Barbarians' Arrival at the Gate: Insider Trading on Non-Inside Information

Georgy Chabakauri
London School of Economics
Vyacheslav Fos
Boston College
Wei Jiang
Emory University


This paper formalizes a novel form of corporate insider trading based on non-insider
information. In our model, insiders make trading decisions in anticipation of activist
intervention. Because insiders have access to private information about firm fundamentals,
they can better separate activism-motivated trades from those by speculators based on
signals about firm fundamentals. We validate this prediction empirically by showing that
when activists (privately) accumulate shares ahead of Schedule 13D filings, insiders are
less likely to sell shares and are more likely to buy shares. Consistently with the proposed
mechanism, insiders respond to activist trading more decisively precisely when there is
an absence of positive news about the firm’s fundamentals—so that insiders are able
to attribute high buy order flow to activist interest instead of speculation on positive

Incentivizing Effort and Informing Investment: The Dual Role of Stock Prices

Snehal Banerjee
University of California-San Diego
Jesse Davis
University of North Carolina-Chapel Hill
Naveen Gondhi


Stock prices reflect managerial performance and aggregate investor information about investment opportunities. We show that these dual roles are in tension: when prices are more informative about future opportunities, they may be less effective at incentivizing managerial effort. Firm value can decrease with price informativeness, but increase with ex-post inefficient investment rules and lower transparency. The relation among price informativeness, performance sensitivity and duration of man- agerial compensation, delegation, and firm value depends crucially on the importance of investment opportunities relative to managerial performance. Standard empirical measures of efficiency can be misleading because they ignore the dual role of prices.

Valuing Financial Data

Maryam Farboodi
Massachusetts Institute of Technology
Dhruv Singal
Columbia University
Laura Veldkamp
Columbia University
Vaidyanathan Venkateswaran
New York University


How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information about others' characteristics. It can value data that is public or private, about one or many assets, relevant for dividends or for sentiment. While different data types have different valuations, heterogeneous investors value the same data very differently, which suggests a low price elasticity for data demand. Heterogeneous investors' data valuations are also affected differentially by market illiquidity.

News Selection and its Implications to Financial Markets

Charles Martineau
University of Toronto
Jordi Mondria
University of Toronto


This paper builds a theoretical framework to endogeneize the editorial decisions of media and analyze their asset pricing implications. The decision to publish a story about a particular firm will not only provide information to investors about the firm selected for publication (which is the focus of the literature), but also will convey information about non-reported firms. Specifically, the investor will be able to distinguish the risk regime of non-reported firms with high expected news coverage and those with low expected news coverage. As a consequence, the decision to select a firm to be reported in a media outlet will have asset pricing implications for reported firms, non-reported firms with high expected news coverage and non-reported firms with low expected news coverage. Failing to capture the information implications for all types of firms may lead the econometrician to estimate a misspecified asset pricing model. We provide empirical evidence inline with the model predictions.

Nadya Malenko
University of Michigan
Ilona Babenko
Arizona State University
Daniel Andrei
McGill University
Diego Garcia
University of Colorado Boulder
JEL Classifications
  • G1 - Asset Markets and Pricing