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Quantifying the diversity of news around stock market moves

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Curme, Chester, Zhuo, Ying Daisy, Moat, Helen Susannah and Preis, Tobias (2017) Quantifying the diversity of news around stock market moves. The Journal of Network Theory in Finance, 3 (1). pp. 1-20. doi:10.21314/JNTF.2017.027 ISSN 2055-7795.

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Official URL: http://dx.doi.org/10.21314/JNTF.2017.027

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Abstract

The dynamics of news are such that some days are dominated by a single story while others see news outlets reporting on a range of different events. While these largescale features of news are familiar to many, they are often ignored in settings where they may be important in understanding complex decision-making processes, such as in financial markets. In this paper, we use a topic-modeling approach to quantify the changing attentions of a major news outlet, the Financial Times, to issues of interest. Our analysis reveals that the diversity of financial news, as quantified by our method, can improve forecasts of trading volume. We also find evidence which suggests that, while attention in financial news tends to be concentrated on a smaller number of topics following stock market falls, there is a "healthy diversity" of news following upward market movements. We conclude that the diversity of financial news can be a useful forecasting tool, offering early warning signals of increased activity in financial markets.

Item Type: Journal Article
Subjects: H Social Sciences > HG Finance
P Language and Literature > PN Literature (General)
Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Social Sciences > Warwick Business School > Behavioural Science
Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH): Capital market, Financial institutions, Ranking and selection (Statistics), Stock exchanges , Journalism, Commercial
Journal or Publication Title: The Journal of Network Theory in Finance
Publisher: Incisive Media Ltd.
ISSN: 2055-7795
Official Date: 22 March 2017
Dates:
DateEvent
22 March 2017Published
13 March 2017Accepted
Volume: 3
Number: 1
Page Range: pp. 1-20
DOI: 10.21314/JNTF.2017.027
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 2 June 2017
Date of first compliant Open Access: 2 June 2017
Funder: Engineering and Physical Sciences Research Council (EPSRC)
Grant number: EP/K039830/1; EP/N510129/1
Open Access Version:
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