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Quantifying the Diversity of News Around Stock Market Moves

Chester Curme, Ying Daisy Zhuo, Helen Susannah Moat and Tobias Preis, Quantifying the diversity of news around stock market moves, Journal of Network Theory in Finance 3(1), 1–20 (2017).

20 Pages Posted: 23 Mar 2017  

Chester Curme

Boston University

Ying Daisy Zhuo

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Helen Susannah Moat

University College London - Department of Civil, Environmental and Geomatic Engineering; Boston University - Center for Polymer Studies

Tobias Preis

Data Science Lab, Behavioural Science, Warwick Business School; Artemis Capital Asset Management GmbH

Date Written: March 22, 2017

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 large-scale 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.

Keywords: complexity science; computational social science; latent Dirichlet allocation (LDA); financial news; financial markets

JEL Classification: A10, B40, C10, C20, C22, C53, C90, D70, D79, D83, J10, J11, O40, O47

Suggested Citation

Curme, Chester and Zhuo, Ying Daisy and Moat, Helen Susannah and Preis, Tobias, Quantifying the Diversity of News Around Stock Market Moves (March 22, 2017). Chester Curme, Ying Daisy Zhuo, Helen Susannah Moat and Tobias Preis, Quantifying the diversity of news around stock market moves, Journal of Network Theory in Finance 3(1), 1–20 (2017).. Available at SSRN: https://ssrn.com/abstract=2939505

Chester Curme

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

Ying Daisy Zhuo

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

77 Massachusetts Ave. E62-663
Cambridge, MA 02142
United States

Helen Susannah Moat

University College London - Department of Civil, Environmental and Geomatic Engineering ( email )

Gower Street
London, WC1E 6BT
United Kingdom

HOME PAGE: http://www.suzymoat.co.uk

Boston University - Center for Polymer Studies ( email )

590 Commonwealth Avenue
Boston, MA 02215
United States

Tobias Preis (Contact Author)

Data Science Lab, Behavioural Science, Warwick Business School ( email )

University of Warwick
Coventry, CV4 7AL
United Kingdom

HOME PAGE: http://www.tobiaspreis.com

Artemis Capital Asset Management GmbH ( email )

Gartenstrasse 14
Holzheim, 65558
Germany

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