Exploring the predictive power of Google searches over the US stock market

Detalhes bibliográficos
Autor(a) principal: Sàágua, João Guilherme Martins Borges
Data de Publicação: 2014
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/11694
Resumo: A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
id RCAP_eae33435f826cb12dcf630e5e617fea3
oai_identifier_str oai:run.unl.pt:10362/11694
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Exploring the predictive power of Google searches over the US stock marketInvestor attentionSearch dataStock market predictabilityNoise tradingA Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and EconomicsThis paper takes search intensity for stock tickers in Google (SVI) as a direct measure of retail investor attention and assesses whether it holds predictive power over short-term market outcomes. In a sample of the most representative US stocks, during the period 2005 – 2008, I provide evidence that (1) surges of investor attention forecast higher stock liquidity and volatility; (2) depending severely on what is considered an abnormal level of SVI, retail investor attention can also be priced; and (3) SVI does not relate to firm-specific features, such as size and value. Furthermore, I extend the investigation to the aggregate market level, finding that investor attention to the market index predicts greater market liquidity, volatility and return.NSBE - UNLPrado, MelissaRUNSàágua, João Guilherme Martins Borges2014-03-18T17:06:13Z2014-012014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/11694TID:201474638enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T03:46:18Zoai:run.unl.pt:10362/11694Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:20:28.739372Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Exploring the predictive power of Google searches over the US stock market
title Exploring the predictive power of Google searches over the US stock market
spellingShingle Exploring the predictive power of Google searches over the US stock market
Sàágua, João Guilherme Martins Borges
Investor attention
Search data
Stock market predictability
Noise trading
title_short Exploring the predictive power of Google searches over the US stock market
title_full Exploring the predictive power of Google searches over the US stock market
title_fullStr Exploring the predictive power of Google searches over the US stock market
title_full_unstemmed Exploring the predictive power of Google searches over the US stock market
title_sort Exploring the predictive power of Google searches over the US stock market
author Sàágua, João Guilherme Martins Borges
author_facet Sàágua, João Guilherme Martins Borges
author_role author
dc.contributor.none.fl_str_mv Prado, Melissa
RUN
dc.contributor.author.fl_str_mv Sàágua, João Guilherme Martins Borges
dc.subject.por.fl_str_mv Investor attention
Search data
Stock market predictability
Noise trading
topic Investor attention
Search data
Stock market predictability
Noise trading
description A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
publishDate 2014
dc.date.none.fl_str_mv 2014-03-18T17:06:13Z
2014-01
2014-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/11694
TID:201474638
url http://hdl.handle.net/10362/11694
identifier_str_mv TID:201474638
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv NSBE - UNL
publisher.none.fl_str_mv NSBE - UNL
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799137846123036672

Registros relacionados