Learning from news, information flow, and financial markets

38 Pages Posted: 21 Jun 2024

See all articles by Alejandro Bernales

Alejandro Bernales

Universidad de Chile

Marcela Valenzuela

Pontificia Universidad Católica de Chile

Ilknur Zer

Board of Governors of the Federal Reserve System

Date Written: June 14, 2024

Abstract

Neuroscience reveals that human brain activity and cognitive load exhibit an inverted V-shape relationship, showing a turning point, beyond which agents are unable to process additional information. We investigate the implications of this cognitive phenomenon within the financial markets, where participants are continually faced with and have to process news. We use textual analysis and machine learning tools applied to The New York Times since 1885 to measure information overload and find that investors learn from the news but only up to a threshold. Information overload exhausts investors' processing capacity, making the extracted information imprecise. Increased estimation risk, in turn, leads to higher market risk premium. Information overload also has cross-sectional effects: stocks that are difficult to value and require large learning efforts have higher expected returns.

Keywords: Information overload, media content, sentiment, limited attention, predicting returns, behavioral biases. JEL classification: G40, G41, G12, G14

Suggested Citation

Bernales, Alejandro and Valenzuela, Marcela and Zer, Ilknur, Learning from news, information flow, and financial markets (June 14, 2024). Available at SSRN: https://ssrn.com/abstract=4865802 or http://dx.doi.org/10.2139/ssrn.4865802

Alejandro Bernales

Universidad de Chile ( email )

Diagonal Paraguay 257
Santiago
Chile

HOME PAGE: http://www.alejandrobernales.com

Marcela Valenzuela (Contact Author)

Pontificia Universidad Católica de Chile ( email )

Vicuña Mackenna 4860
Santiago, R. Metropolitana 7520421
Chile

Ilknur Zer

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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