THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET

Detalhes bibliográficos
Autor(a) principal: RAMOS,HENRIQUE PINTO
Data de Publicação: 2017
Outros Autores: RIBEIRO,KADJA KATHERINE MENDES, PERLIN,MARCELO SCHERER
Tipo de documento: Artigo
Idioma: eng
Título da fonte: RAM. Revista de Administração Mackenzie
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712017000200184
Resumo: ABSTRACT Purpose: To analyze the predictability of Google's search queries in the Brazilian financial market. Originality/gap/relevance/implications: Despite a growing foreign literature using Google's search query data, there is no acknowledgement of work on this area in Brazil. An application to the Brazilian financial market shows new sources of information about market movements and may contribute to researchers and practitioners to understand how changes in specific search queries affect the market. Key methodological aspects: Following previous studies, we estimate VAR models and Granger causality tests to investigate the effects over three variables in both stock and fixed income markets: traded volume, return and volatility. Following this procedure, we verify both the hypothesis of financial variables being affected by search queries, as well as the opposite relationship. Weekly data from Google's search queries and financial markets was gathered for the period between 2007 and 2014. Summary of key results: The existence of a predictive effect between search query data and financial variables, particularly in the stock market, is evident. However, this result was not robust in all cases studied. It is noteworthy that, for the inverse relationship, i.e. financial market impacting search queries on Google, strong evidence of a causal relationship has been found. A trading strategy based on this type of data yielded higher returns than the defined benchmarks. Key considerations/conclusions: A significant relationship between Google's search query data and the financial market has been discovered. Results provide a new source of information that affects the Brazilian financial market.
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spelling THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKETGoogle TrendsInvestor attentionMarket efficiencyMarket microstructureVAR ModelsABSTRACT Purpose: To analyze the predictability of Google's search queries in the Brazilian financial market. Originality/gap/relevance/implications: Despite a growing foreign literature using Google's search query data, there is no acknowledgement of work on this area in Brazil. An application to the Brazilian financial market shows new sources of information about market movements and may contribute to researchers and practitioners to understand how changes in specific search queries affect the market. Key methodological aspects: Following previous studies, we estimate VAR models and Granger causality tests to investigate the effects over three variables in both stock and fixed income markets: traded volume, return and volatility. Following this procedure, we verify both the hypothesis of financial variables being affected by search queries, as well as the opposite relationship. Weekly data from Google's search queries and financial markets was gathered for the period between 2007 and 2014. Summary of key results: The existence of a predictive effect between search query data and financial variables, particularly in the stock market, is evident. However, this result was not robust in all cases studied. It is noteworthy that, for the inverse relationship, i.e. financial market impacting search queries on Google, strong evidence of a causal relationship has been found. A trading strategy based on this type of data yielded higher returns than the defined benchmarks. Key considerations/conclusions: A significant relationship between Google's search query data and the financial market has been discovered. Results provide a new source of information that affects the Brazilian financial market.Editora MackenzieUniversidade Presbiteriana Mackenzie2017-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712017000200184RAM. Revista de Administração Mackenzie v.18 n.2 2017reponame:RAM. Revista de Administração Mackenzieinstname:Universidade Presbiteriana Mackenzie (UPM)instacron:MACKENZIE10.1590/1678-69712017/administracao.v18n2p184-210info:eu-repo/semantics/openAccessRAMOS,HENRIQUE PINTORIBEIRO,KADJA KATHERINE MENDESPERLIN,MARCELO SCHEREReng2017-06-12T00:00:00Zoai:scielo:S1678-69712017000200184Revistahttps://www.scielo.br/j/ram/https://old.scielo.br/oai/scielo-oai.phprevista.adm@mackenzie.br1678-69711518-6776opendoar:2017-06-12T00:00RAM. Revista de Administração Mackenzie - Universidade Presbiteriana Mackenzie (UPM)false
dc.title.none.fl_str_mv THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET
title THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET
spellingShingle THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET
RAMOS,HENRIQUE PINTO
Google Trends
Investor attention
Market efficiency
Market microstructure
VAR Models
title_short THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET
title_full THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET
title_fullStr THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET
title_full_unstemmed THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET
title_sort THE FORECASTING POWER OF INTERNET SEARCH QUERIES IN THE BRAZILIAN FINANCIAL MARKET
author RAMOS,HENRIQUE PINTO
author_facet RAMOS,HENRIQUE PINTO
RIBEIRO,KADJA KATHERINE MENDES
PERLIN,MARCELO SCHERER
author_role author
author2 RIBEIRO,KADJA KATHERINE MENDES
PERLIN,MARCELO SCHERER
author2_role author
author
dc.contributor.author.fl_str_mv RAMOS,HENRIQUE PINTO
RIBEIRO,KADJA KATHERINE MENDES
PERLIN,MARCELO SCHERER
dc.subject.por.fl_str_mv Google Trends
Investor attention
Market efficiency
Market microstructure
VAR Models
topic Google Trends
Investor attention
Market efficiency
Market microstructure
VAR Models
description ABSTRACT Purpose: To analyze the predictability of Google's search queries in the Brazilian financial market. Originality/gap/relevance/implications: Despite a growing foreign literature using Google's search query data, there is no acknowledgement of work on this area in Brazil. An application to the Brazilian financial market shows new sources of information about market movements and may contribute to researchers and practitioners to understand how changes in specific search queries affect the market. Key methodological aspects: Following previous studies, we estimate VAR models and Granger causality tests to investigate the effects over three variables in both stock and fixed income markets: traded volume, return and volatility. Following this procedure, we verify both the hypothesis of financial variables being affected by search queries, as well as the opposite relationship. Weekly data from Google's search queries and financial markets was gathered for the period between 2007 and 2014. Summary of key results: The existence of a predictive effect between search query data and financial variables, particularly in the stock market, is evident. However, this result was not robust in all cases studied. It is noteworthy that, for the inverse relationship, i.e. financial market impacting search queries on Google, strong evidence of a causal relationship has been found. A trading strategy based on this type of data yielded higher returns than the defined benchmarks. Key considerations/conclusions: A significant relationship between Google's search query data and the financial market has been discovered. Results provide a new source of information that affects the Brazilian financial market.
publishDate 2017
dc.date.none.fl_str_mv 2017-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712017000200184
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712017000200184
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-69712017/administracao.v18n2p184-210
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Editora Mackenzie
Universidade Presbiteriana Mackenzie
publisher.none.fl_str_mv Editora Mackenzie
Universidade Presbiteriana Mackenzie
dc.source.none.fl_str_mv RAM. Revista de Administração Mackenzie v.18 n.2 2017
reponame:RAM. Revista de Administração Mackenzie
instname:Universidade Presbiteriana Mackenzie (UPM)
instacron:MACKENZIE
instname_str Universidade Presbiteriana Mackenzie (UPM)
instacron_str MACKENZIE
institution MACKENZIE
reponame_str RAM. Revista de Administração Mackenzie
collection RAM. Revista de Administração Mackenzie
repository.name.fl_str_mv RAM. Revista de Administração Mackenzie - Universidade Presbiteriana Mackenzie (UPM)
repository.mail.fl_str_mv revista.adm@mackenzie.br
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