News Momentum

45 Pages Posted: 26 Oct 2015 Last revised: 9 Jun 2019

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: June 6, 2019

Abstract

We decompose daily stock returns into news- and non-news-driven components, using a comprehensive sample of high-frequency firm-level news arrivals. We find that news-driven returns tend to exhibit momentum, different from non-news returns that precede a reversal. A news momentum strategy that buys (sells) stocks with high (low) news returns generates a monthly return of 3.34% in the following week, with a four-factor alpha of 3.37%. The news momentum effect is stronger when investors are distracted. Using analyst earnings forecasts as a proxy, we also find that slow adjustments of market expectations following firm news contribute to news momentum.

Keywords: News; Momentum; Underreaction; Attention; Expectation

JEL Classification: G02, G10, G14

Suggested Citation

Jiang, Hao and Li, Sophia Zhengzi and Wang, Hao, News Momentum (June 6, 2019). 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

Register to save articles to
your library

Register

Paper statistics

Downloads
1,383
Abstract Views
5,558
rank
13,022
PlumX Metrics