title: Quantifying trading behavior in financial markets using Google Trends.
abstract: Crises in financial markets affect humans worldwide. Detailed market data on trading decisions reflect some of the complex human behavior that has led to these crises. We suggest that massive new data sources resulting from human interaction with the Internet may offer a new perspective on the behavior of market participants in periods of large market movements. By analyzing changes in Google query volumes for search terms related to finance, we find patterns that may be interpreted as "early warning signs" of stock market moves. Our results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior.
authors.affiliation: Warwick Business School, University of Warwick, Scarman Road, Coventry, CV4 7AL, UK. Tobias.Preis@wbs.ac.uk
authors.forename: Tobias
authors.initials: T
authors.lastname: Preis
authors.forename: Helen Susannah
authors.initials: HS
authors.lastname: Moat
authors.forename: H Eugene
authors.initials: HE
authors.lastname: Stanley
mesh_terms: D003198:Computer Simulation; D005716:Game Theory; D020407:Internet; D007449:Investments; D018803:Models, Economic; D057386:Search Engine; D012984:Software