Abstract

https://ssrn.com/abstract=2679614
 


 



News Momentum


Hao Jiang


Michigan State University

Sophia Zhengzi Li


Michigan State University

Hao Wang


Michigan State University; Prime Quantitative Research

October 1, 2015


Abstract:     
This paper combines a comprehensive sample of intraday firm-level news arrivals with high-frequency price movements of individual stocks, thereby decomposing daily stock returns into news-driven and non-news driven components. Consistent with prior literature, we find that non-news driven return precedes a reversal. For new-driven return, however, we find strong evidence of return continuation. 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 4-factor alpha of 40.44% controlling for the market, size, value, and momentum. This effect of news momentum is particularly pronounced for overnight and weekend news, and among small firms with less analyst coverage, higher volatility, and lower liquidity, which is consistent with imperfect investor reaction to news and limits to arbitrage.

Number of Pages in PDF File: 41

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

JEL Classification: G02, G10, G14


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Date posted: October 26, 2015 ; Last revised: May 12, 2016

Suggested Citation

Jiang, Hao and Li, Sophia Zhengzi and Wang, Hao, News Momentum (October 1, 2015). Available at SSRN: https://ssrn.com/abstract=2679614 or http://dx.doi.org/10.2139/ssrn.2679614

Contact Information

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
Michigan State University ( email )
315 Eppley Center
East Lansing, MI 48824-1122
United States
Hao Wang (Contact Author)
Michigan State University ( email )
College of Human Medicine
East Lansing, MI 48824-1122
United States
Prime Quantitative Research ( email )
MI
United States
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