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News Momentum

52 Pages Posted: 26 Oct 2015 Last revised: 7 Jul 2017

Hao Jiang

Michigan State University

Sophia Zhengzi Li

Michigan State University; Rutgers Business School

Hao Wang

Prime Quantitative Research

Date Written: July 6, 2017


We decompose daily stock returns into news- and non-news-driven components, using a comprehensive sample of intraday firm-level news arrivals matched with high-frequency movements of their stock prices. We find that, consistent with prior literature, non- news returns precede a reversal. For news-driven returns, however, we find strong evidence of return continuation without subsequent reversals. A strategy of news momentum that buys stocks with high news returns and sells stocks with low news returns generates an annualized return of 40.08% in the following week, with a four-factor alpha of 40.44%, controlling for the market, size, value, and momentum. The strategy’s profitability is driven by positive serial correlations in individual stock returns, and is particularly pronounced for overnight and weekend news and among small firms with low analyst coverage, high volatility, and low liquidity. These results suggest that investor under-reaction to news, coupled with limits to arbitrage, drives news momentum.

Keywords: News; Momentum; Reversal; Underreaction; Attention; Limits to Arbitrage

JEL Classification: G02, G10, G14

Suggested Citation

Jiang, Hao and Li, Sophia Zhengzi and Wang, Hao, News Momentum (July 6, 2017). Available at SSRN: or

Hao Jiang

Michigan State University ( email )

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


Sophia Zhengzi Li

Michigan State University ( email )

315 Eppley Center
East Lansing, MI 48824-1122
United States

Rutgers Business School

100 Rockafeller Rd
Piscataway, NJ 08854
United States

Hao Wang (Contact Author)

Prime Quantitative Research ( email )

United States

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