Literature DB >> 21078644

Complex dynamics of our economic life on different scales: insights from search engine query data.

Tobias Preis1, Daniel Reith, H Eugene Stanley.   

Abstract

Search engine query data deliver insight into the behaviour of individuals who are the smallest possible scale of our economic life. Individuals are submitting several hundred million search engine queries around the world each day. We study weekly search volume data for various search terms from 2004 to 2010 that are offered by the search engine Google for scientific use, providing information about our economic life on an aggregated collective level. We ask the question whether there is a link between search volume data and financial market fluctuations on a weekly time scale. Both collective 'swarm intelligence' of Internet users and the group of financial market participants can be regarded as a complex system of many interacting subunits that react quickly to external changes. We find clear evidence that weekly transaction volumes of S&P 500 companies are correlated with weekly search volume of corresponding company names. Furthermore, we apply a recently introduced method for quantifying complex correlations in time series with which we find a clear tendency that search volume time series and transaction volume time series show recurring patterns.

Entities:  

Year:  2010        PMID: 21078644     DOI: 10.1098/rsta.2010.0284

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  44 in total

1.  Switching processes in financial markets.

Authors:  Tobias Preis; Johannes J Schneider; H Eugene Stanley
Journal:  Proc Natl Acad Sci U S A       Date:  2011-04-26       Impact factor: 11.205

2.  Hidden interactions in financial markets.

Authors:  Stavros K Stavroglou; Athanasios A Pantelous; H Eugene Stanley; Konstantin M Zuev
Journal:  Proc Natl Acad Sci U S A       Date:  2019-05-13       Impact factor: 11.205

3.  Quantifying the semantics of search behavior before stock market moves.

Authors:  Chester Curme; Tobias Preis; H Eugene Stanley; Helen Susannah Moat
Journal:  Proc Natl Acad Sci U S A       Date:  2014-07-28       Impact factor: 11.205

4.  The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy.

Authors:  David Garcia; Claudio J Tessone; Pavlin Mavrodiev; Nicolas Perony
Journal:  J R Soc Interface       Date:  2014-10-06       Impact factor: 4.118

5.  Quantifying the behavior of stock correlations under market stress.

Authors:  Tobias Preis; Dror Y Kenett; H Eugene Stanley; Dirk Helbing; Eshel Ben-Jacob
Journal:  Sci Rep       Date:  2012-10-18       Impact factor: 4.379

6.  Web search queries can predict stock market volumes.

Authors:  Ilaria Bordino; Stefano Battiston; Guido Caldarelli; Matthieu Cristelli; Antti Ukkonen; Ingmar Weber
Journal:  PLoS One       Date:  2012-07-19       Impact factor: 3.240

7.  Quantifying the advantage of looking forward.

Authors:  Tobias Preis; Helen Susannah Moat; H Eugene Stanley; Steven R Bishop
Journal:  Sci Rep       Date:  2012-04-05       Impact factor: 4.379

8.  Tracking traders' understanding of the market using e-communication data.

Authors:  Serguei Saavedra; Jordi Duch; Brian Uzzi
Journal:  PLoS One       Date:  2011-10-25       Impact factor: 3.240

9.  Quantifying trading behavior in financial markets using Google Trends.

Authors:  Tobias Preis; Helen Susannah Moat; H Eugene Stanley
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

10.  Evolution of the most common English words and phrases over the centuries.

Authors:  Matjaz Perc
Journal:  J R Soc Interface       Date:  2012-07-25       Impact factor: 4.118

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