Web Search Queries Can Predict Stock Market Volumes
Publication Date
July 19, 2012
Journal
PLOS ONE
Authors
Ilaria Bordino, Stefano Battiston, Guido Caldarelli, Matthieu Cristelli, et al
Volume
7
Issue
7
Pages
e40014
DOI
https://dx.plos.org/10.1371/journal.pone.0040014
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0040014
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/22829871
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3400625
Europe PMC
http://europepmc.org/abstract/MED/22829871
Web of Science
000306956300009
Scopus
84864135851
Mendeley
http://www.mendeley.com/research/web-search-queries-predict-stock-market-volumes
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Mendeley | Further Information

{"title"=>"Web search queries can predict stock market volumes", "type"=>"journal", "authors"=>[{"first_name"=>"Ilaria", "last_name"=>"Bordino", "scopus_author_id"=>"26325355900"}, {"first_name"=>"Stefano", "last_name"=>"Battiston", "scopus_author_id"=>"6603263932"}, {"first_name"=>"Guido", "last_name"=>"Caldarelli", "scopus_author_id"=>"55139905100"}, {"first_name"=>"Matthieu", "last_name"=>"Cristelli", "scopus_author_id"=>"26021118900"}, {"first_name"=>"Antti", "last_name"=>"Ukkonen", "scopus_author_id"=>"23393982600"}, {"first_name"=>"Ingmar", "last_name"=>"Weber", "scopus_author_id"=>"8943847500"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "arxiv"=>"1110.4784", "scopus"=>"2-s2.0-84864135851", "pui"=>"365292859", "doi"=>"10.1371/journal.pone.0040014", "isbn"=>"1932-6203", "sgr"=>"84864135851", "pmid"=>"22829871"}, "id"=>"669e0e83-2d4e-38a3-9b02-99454172fce1", "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 query volumes (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 exemples 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 trading volumes of stocks traded in NASDAQ-100 are correlated with the 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.", "link"=>"http://www.mendeley.com/research/web-search-queries-predict-stock-market-volumes", "reader_count"=>151, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>7, "Researcher"=>32, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>34, "Student > Postgraduate"=>6, "Student > Master"=>33, "Other"=>7, "Student > Bachelor"=>11, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>1, "Professor"=>7}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>7, "Researcher"=>32, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>34, "Student > Postgraduate"=>6, "Student > Master"=>33, "Other"=>7, "Student > Bachelor"=>11, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>1, "Professor"=>7}, "reader_count_by_subject_area"=>{"Unspecified"=>7, "Agricultural and Biological Sciences"=>6, "Business, Management and Accounting"=>19, "Chemistry"=>1, "Computer Science"=>34, "Decision Sciences"=>1, "Economics, Econometrics and Finance"=>31, "Energy"=>1, "Engineering"=>7, "Materials Science"=>1, "Mathematics"=>9, "Medicine and Dentistry"=>4, "Physics and Astronomy"=>17, "Psychology"=>3, "Social Sciences"=>8, "Linguistics"=>2}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Social Sciences"=>{"Social Sciences"=>8}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>17}, "Psychology"=>{"Psychology"=>3}, "Mathematics"=>{"Mathematics"=>9}, "Unspecified"=>{"Unspecified"=>7}, "Engineering"=>{"Engineering"=>7}, "Chemistry"=>{"Chemistry"=>1}, "Energy"=>{"Energy"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>31}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>6}, "Computer Science"=>{"Computer Science"=>34}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>19}, "Linguistics"=>{"Linguistics"=>2}}, "reader_count_by_country"=>{"United States"=>6, "Japan"=>1, "United Kingdom"=>3, "Switzerland"=>2, "Portugal"=>2, "Netherlands"=>1, "Belgium"=>1, "China"=>2, "Luxembourg"=>1, "Finland"=>1, "Brazil"=>1, "Italy"=>3, "Australia"=>1}, "group_count"=>22}

CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/608047"], "description"=>"<p>We observe some minor differences between the age of common users and the one of the users corresponding to queries belonging to NASDAQ-100 sample.</p>", "links"=>[], "tags"=>["nasdaq-100"], "article_id"=>278532, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t011", "stats"=>{"downloads"=>6, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Age_distribution_for_NASDAQ_100_sample_/278532", "title"=>"Age distribution for NASDAQ-100 sample.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:22:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/608195"], "description"=>"<p>Average cross-correlation functions between search-engine volumes and signed price returns for the clean NASDAQ-100 stocks (query: Ticker, ).</p>", "links"=>[], "tags"=>["cross-correlation", "functions", "search-engine", "volumes", "signed", "returns", "nasdaq-100", "stocks"], "article_id"=>278661, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t008", "stats"=>{"downloads"=>0, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_cross_correlation_functions_between_search_engine_volumes_and_signed_price_returns_for_the_clean_NASDAQ_100_stocks_query_Ticker_/278661", "title"=>"Average cross-correlation functions between search-engine volumes and signed price returns for the clean NASDAQ-100 stocks (query: Ticker, ).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:24:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/608245"], "description"=>"<p>The 100 traded companies included in the NASDAQ-100 index with their relative ticker.</p>", "links"=>[], "tags"=>["100", "traded", "companies", "included", "nasdaq-100"], "article_id"=>278726, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t001", "stats"=>{"downloads"=>1, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_100_traded_companies_included_in_the_NASDAQ_100_index_with_their_relative_ticker_/278726", "title"=>"The 100 traded companies included in the NASDAQ-100 index with their relative ticker.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:25:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/608439"], "description"=>"<p>Average cross-correlation time series for NASDAQ-100 stocks (query: Ticker, volumes: searches).</p>", "links"=>[], "tags"=>["cross-correlation", "nasdaq-100", "stocks"], "article_id"=>278922, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t004", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_cross_correlation_time_series_for_NASDAQ_100_stocks_query_Ticker_volumes_searches_/278922", "title"=>"Average cross-correlation time series for NASDAQ-100 stocks (query: Ticker, volumes: searches).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:28:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/608486"], "description"=>"<p>We compute the cross-correlation coefficient between query and trading volumes after removing the days characterized by the highest trading volumes, respectively the top five and top ten events are removed. We note that a significant correlation is still observed for most of the stocks considered. This important test supports the robustness of our findings. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040014#pone.0040014.s001\" target=\"_blank\">Supporting Information S1</a>for the complete results for the 87 clean stocks.</p>", "links"=>[], "tags"=>["coefficient", "query", "volumes", "removing", "largest"], "article_id"=>278963, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t007", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cross_correlation_coefficient_between_query_and_trading_volumes_after_removing_largest_events_/278963", "title"=>"Cross-correlation coefficient between query and trading volumes after removing largest events.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:29:23"}
  • {"files"=>["https://ndownloader.figshare.com/files/607932"], "description"=>"<p>Query volumes of NASDAQ-100 tickers are negligible during non-working days, then we consider only the contribution to query volumes deriving from working days.</p>", "links"=>[], "tags"=>["aapl", "days"], "article_id"=>278416, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g011", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Query_search_for_AAPL_stock_in_the_various_days_of_the_week_/278416", "title"=>"Query-search for AAPL stock in the various days of the week.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:20:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/606516"], "description"=>"<p>(<b>up</b>) Time evolution of normalized query-logs volumes for the ticker “NVDA” compared with the trading-volume of the “NVIDIA Corporation”. The data for both query-logs (blue) and trading volume (red) are aggregated on a daily basis. (<b>bottom</b>) The plot of the sample cross correlation function as defined in Eq. (1) absolute values of the time lag (positive values of correspond to solid lines while negative values of the time lag correspond to the broken lines). The correlation coefficients at positive time lags are always larger than the corresponding at negative ones, this suggests that today’s query volumes anticipate and affect the trading activity of the following days (typically one or two days at most).</p>", "links"=>[], "tags"=>["volumes"], "article_id"=>277010, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g002", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Query_log_volumes_and_trading_volumes_cross_correlation_analysis_ticker_8220_NVDA_8221_/277010", "title"=>"Query log volumes and trading volumes: cross correlation analysis (ticker: “NVDA”).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 01:56:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/607810"], "description"=>"<p>The fraction of one-time searchers appear to be very stable in time and we do not observe a correlation of these kind of users with anomalous trading volume or price movements.</p>", "links"=>[], "tags"=>["one-time"], "article_id"=>278296, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g010", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_the_percentage_of_one_time_searchers_/278296", "title"=>"Evolution of the percentage of one-time searchers.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:18:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/606788"], "description"=>"<p>(<b>up</b>) Time evolution of normalized query-logs volumes for the ticker “RIMM” compared with the trading-volume of the “Research In Motion Limited”. The data for both query-logs (blue) and trading volume (red) are aggregated on a daily basis. (<b>bottom</b>) The plot of the sample cross correlation function as defined in Eq. (1) vs absolute values of the time lag (positive values of correspond to solid lines while negative values of the time lag correspond to the broken lines). As in the case of the ticker “NVDA” corresponding to the company “NVIDIA Corporation” in Fig. 2, the correlation coefficients at positive time lags are always larger than the corresponding at negative ones, this suggests that today’s query volumes anticipate and affect the trading activity of the following days (typically one or two days at most).</p>", "links"=>[], "tags"=>["volumes"], "article_id"=>277273, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g003", "stats"=>{"downloads"=>1, "page_views"=>33, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Query_log_volumes_and_trading_volumes_cross_correlation_analysis_ticker_8220_RIMM_8221_/277273", "title"=>"Query log volumes and trading volumes: cross correlation analysis (ticker: “RIMM”).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:01:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/608388"], "description"=>"<p>Correlations are lower than the case in which we consider the queries deriving from the tickers (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040014#pone-0040014-t004\" target=\"_blank\">Table 4</a>).</p>", "links"=>[], "tags"=>["cross-correlation", "nasdaq-100", "stocks"], "article_id"=>278876, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t005", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_cross_correlation_time_series_for_NASDAQ_100_stocks_query_Company_name_volumes_searches_/278876", "title"=>"Average cross-correlation time series for NASDAQ-100 stocks (query: Company name, volumes: searches).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:27:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/607558"], "description"=>"<p>Distribution of the number of days that users searched for AMZN within one month (left) and over the whole year (right).</p>", "links"=>[], "tags"=>["users"], "article_id"=>278046, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g008", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Behavior_of_the_users_who_search_for_AMZN_/278046", "title"=>"Behavior of the users who search for AMZN.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:14:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/607181"], "description"=>"<p>Trading volume and volatility are correlated and given the fact that volatility is also autocorrelated, the correlation between present query volume and future trading volume could be simply originated by this autocorrelated term. However, we show that the cross-correlation between query and volatility (broken line) is significantly smaller than the one between query and trading volume (solid line). Moreover the branch in the volatility case is equal or even smaller than the value observed in the one. If the origin of the effect were due to the autocorrelation component of the volatility, we would expect a similar behavior for both cross-correlation function. This facts support that the non-autocorrelated origin of the correlation between between present query volume and future trading volume. As a proxy for the volatility we use the absolute value of daily price returns.</p>", "links"=>[], "tags"=>["cross-correlation", "query", "volumes"], "article_id"=>277663, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g005", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_cross_correlation_function_between_query_volumes_and_trading_volumes_and_query_volumes_and_volatility_/277663", "title"=>"Comparison of the cross-correlation function between query volumes and trading volumes and query volumes and volatility.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:07:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/608140"], "description"=>"<p>Adding information about yesterday’s query volume reduces the average prediction error (in an autoregressive model) for today’s trade volume by about , and for half of the companies the reduction is statistically significant at .</p>", "links"=>[], "tags"=>["causality"], "article_id"=>278626, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t009", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Granger_causality_test_/278626", "title"=>"Granger causality test.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:23:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/608340"], "description"=>"<p>By clean stocks we mean that we remove those stocks which give rise to spurious queries such as the one containing a common words like LIFE or for instance the stock EBAY. In <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040014#pone.0040014.s001\" target=\"_blank\">Supporting Information S1</a> we report the cross correlation functions of the 87 stocks on which the average is performed.</p>", "links"=>[], "tags"=>["cross-correlation", "functions", "nasdaq-100", "stocks"], "article_id"=>278822, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_cross_correlation_functions_for_the_clean_NASDAQ_100_stocks_query_Ticker_volumes_searches_/278822", "title"=>"Average cross-correlation functions for the clean NASDAQ-100 stocks (query: Ticker, volumes: searches).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:27:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/608532"], "description"=>"<p>The values of the cross-correlation function for is always higher than the value of . From this evidence it appears that query volumes anticipate trading volumes by one or two days. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040014#pone.0040014.s001\" target=\"_blank\">Supporting Information S1</a> for the complete results for the 87 clean stocks.</p>", "links"=>[], "tags"=>["cross-correlation", "functions"], "article_id"=>279018, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t006", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Values_of_cross_correlation_functions_for_some_selected_stocks_/279018", "title"=>"Values of cross-correlation functions for some selected stocks.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:30:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/606966"], "description"=>"<p>We plot the query-search volumes and trading volumes time series for four stocks (AAPL, AMZN, NFLX and ADBE) to show that the patterns observed in Figs. 2 and 3 are common to most of stocks of the set considered (NASDAQ-100).</p>", "links"=>[], "tags"=>["volumes"], "article_id"=>277458, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g004", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Query_volumes_and_trading_volumes_/277458", "title"=>"Query volumes and trading volumes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:04:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/607323"], "description"=>"<p>Average (left) monthly and (right) yearly distribution of the number of distinct tickers searched by any Yahoo! user.</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>277806, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g006", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Typical_users_8217_behavior_/277806", "title"=>"Typical users’ behavior.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:10:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/607442"], "description"=>"<p>Distribution of the number of days that users searched for AAPL within one month (left) and over the whole year (right).</p>", "links"=>[], "tags"=>["users"], "article_id"=>277935, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g007", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Behavior_of_the_users_who_search_for_AAPL_/277935", "title"=>"Behavior of the users who search for AAPL.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:12:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/608095"], "description"=>"<p>Average age distribution for a random sample collecting half of the data.</p>", "links"=>[], "tags"=>["computer science", "physics", "mathematics"], "article_id"=>278579, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t010", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Age_distribution_of_users_/278579", "title"=>"Age distribution of users.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:22:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/608294"], "description"=>"<p>The results from the queries of Yahoo! users or from all searches (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040014#pone-0040014-t002\" target=\"_blank\">Table 2</a>) are almost identical.</p>", "links"=>[], "tags"=>["cross-correlation", "nasdaq-100", "stocks"], "article_id"=>278778, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.t003", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_cross_correlation_time_series_for_NASDAQ_100_clean_stocks_query_Ticker_volumes_users_/278778", "title"=>"Average cross-correlation time series for NASDAQ-100 clean stocks (query: Ticker, volumes: users).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-19 02:26:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/607685"], "description"=>"<p>Distribution of the number of days that users searched for NFLX within one month (left) and over the whole year (right).</p>", "links"=>[], "tags"=>["users"], "article_id"=>278175, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g009", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Behavior_of_the_users_who_search_for_NFLX_/278175", "title"=>"Behavior of the users who search for NFLX.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 02:16:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/606305"], "description"=>"<p>The study of queries is gaining more and more attention as an important tool for the understanding of social and financial systems. Users perform web searches in order to collect news or browse e-newspaper sites. In particular local or global events such as natural disasters can generate local or global waves of searches through the web. As a result, the logs of these search-engines’ queries are an unprecedented source of anonymized information about human activities. In this paper we provide a detailed analysis on a particular application of these ideas; that is, the anticipation of market activity from user queries. This picture graphically summarizes our procedure. In particular, we investigate which is the relationship between web searches and market movements and whether web searches <i>anticipate</i> market activity. While we can expect that large fluctuations in markets, produce spreading of news or rumors or government’s actions and therefore induce web searches (solid green arrow in panel ), we would like to check if web searches affect or even anticipate financial activity (broken violet arrow in panel ). In detail we investigate if today’s query volumes about financial stocks somehow anticipate financial indicators of tomorrow such as trading volumes, daily returns, volatility, etc, (panels and ) and we find a significant anticipation for trading volumes.</p>", "links"=>[], "tags"=>["presented"], "article_id"=>276796, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040014.g001", "stats"=>{"downloads"=>1, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Graphical_illustration_of_the_analysis_presented_in_this_paper_/276796", "title"=>"Graphical illustration of the analysis presented in this paper.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-19 01:53:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/316718", "https://ndownloader.figshare.com/files/316832"], "description"=>"<div><p>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.</p> </div>", "links"=>[], "tags"=>["queries", "volumes"], "article_id"=>122493, "categories"=>["Information And Computing Sciences", "Mathematics", "Physics"], "users"=>["Ilaria Bordino", "Stefano Battiston", "Guido Caldarelli", "Matthieu Cristelli", "Antti Ukkonen", "Ingmar Weber"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0040014.s001", "https://dx.doi.org/10.1371/journal.pone.0040014.s002"], "stats"=>{"downloads"=>5, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Web_Search_Queries_Can_Predict_Stock_Market_Volumes/122493", "title"=>"Web Search Queries Can Predict Stock Market Volumes", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-07-19 00:41:33"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"11", "full-text"=>"12", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2013", "month"=>"4"}
  • {"unique-ip"=>"15", "full-text"=>"12", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2012", "month"=>"11"}
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  • {"unique-ip"=>"2", "full-text"=>"15", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"22", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"9"}
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  • {"unique-ip"=>"9", "full-text"=>"7", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2014", "month"=>"5"}
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  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"4"}
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  • {"unique-ip"=>"9", "full-text"=>"12", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
  • {"unique-ip"=>"14", "full-text"=>"9", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"10"}
  • {"unique-ip"=>"8", "full-text"=>"4", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"14", "full-text"=>"7", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"19", "full-text"=>"15", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"15", "full-text"=>"5", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"12", "full-text"=>"8", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"15", "full-text"=>"6", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"11", "full-text"=>"12", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
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  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"21", "full-text"=>"6", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"12", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
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  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
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Relative Metric

{"start_date"=>"2012-01-01T00:00:00Z", "end_date"=>"2012-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Engineering and technology/Signal processing", "average_usage"=>[341, 489, 598, 671, 741, 816, 898, 982, 1061, 1123, 1200, 1254, 1296, 1355, 1407, 1476, 1535, 1589, 1642, 1705, 1754, 1802, 1837, 1884, 1925]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[325, 522, 627, 718, 804, 884, 969, 1052, 1131, 1207, 1277, 1346, 1415, 1478, 1542, 1605, 1663, 1723, 1776, 1839, 1895, 1955, 2008, 2066, 2123]}]}
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