Pervasive underreaction: Evidence from high-frequency data

61 Pages Posted: 26 Oct 2015 Last revised: 3 Aug 2020

See all articles by Hao Jiang

Hao Jiang

Michigan State University

Sophia Zhengzi Li

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick

Hao Wang

Prime Quantitative Research

Date Written: July 31, 2020

Abstract

We propose a novel high-frequency decomposition of daily stock returns into news- and non-news-driven components, and uncover evidence of pervasive stock market underreaction to firm news. Prices tend to drift in the same direction as the initial market response for several days after the news arrival without reversals. A trading strategy exploiting the return drift generates high abnormal returns and remains profitable after transaction costs. To understand the economic mechanism, we find that the return drift is stronger when investors are distracted. Analysts' slow adjustments of market expectations following firm news also contribute to the market underreaction.

Keywords: Underreaction; High-Frequency; News; Attention; Expectation Formation

JEL Classification: G10; G14; G40

Suggested Citation

Jiang, Hao and Li, Sophia Zhengzi and Wang, Hao, Pervasive underreaction: Evidence from high-frequency data (July 31, 2020). Journal of Financial Economics (JFE), Forthcoming, Available at SSRN: https://ssrn.com/abstract=2679614 or http://dx.doi.org/10.2139/ssrn.2679614

Hao Jiang

Michigan State University ( email )

315 Eppley Center
Department of Finance
East Lansing, MI 48824
United States

HOME PAGE: http://sites.google.com/site/haojiangfinance/

Sophia Zhengzi Li

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick

100 Rockafeller Rd
Piscataway, NJ 08854
United States

Hao Wang (Contact Author)

Prime Quantitative Research ( email )

MI
United States

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