Web search queries can predict stock market volumes

Ilaria Bordino, Stefano Battiston, Guido Caldarelli, Matthieu Cristelli, Antti Ukkonen, Ingmar Weber

Research output: Contribution to journalArticle

98 Citations (Scopus)

Abstract

We live in a computerized and networked society where many of our actions leave a digital trace and affect other people's actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www.

Original languageEnglish
Article numbere40014
JournalPLoS One
Volume7
Issue number7
DOIs
Publication statusPublished - 19 Jul 2012
Externally publishedYes

Fingerprint

stock exchange
Search Engine
Search engines
engines
Unemployment
Social sciences
Social Sciences
Physics
markets
unemployment
Computer science
computer science
social sciences
Sales
Railroad cars
physics
traffic
sales
Research
Financial markets

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Bordino, I., Battiston, S., Caldarelli, G., Cristelli, M., Ukkonen, A., & Weber, I. (2012). Web search queries can predict stock market volumes. PLoS One, 7(7), [e40014]. https://doi.org/10.1371/journal.pone.0040014

Web search queries can predict stock market volumes. / Bordino, Ilaria; Battiston, Stefano; Caldarelli, Guido; Cristelli, Matthieu; Ukkonen, Antti; Weber, Ingmar.

In: PLoS One, Vol. 7, No. 7, e40014, 19.07.2012.

Research output: Contribution to journalArticle

Bordino, I, Battiston, S, Caldarelli, G, Cristelli, M, Ukkonen, A & Weber, I 2012, 'Web search queries can predict stock market volumes', PLoS One, vol. 7, no. 7, e40014. https://doi.org/10.1371/journal.pone.0040014
Bordino I, Battiston S, Caldarelli G, Cristelli M, Ukkonen A, Weber I. Web search queries can predict stock market volumes. PLoS One. 2012 Jul 19;7(7). e40014. https://doi.org/10.1371/journal.pone.0040014
Bordino, Ilaria ; Battiston, Stefano ; Caldarelli, Guido ; Cristelli, Matthieu ; Ukkonen, Antti ; Weber, Ingmar. / Web search queries can predict stock market volumes. In: PLoS One. 2012 ; Vol. 7, No. 7.
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