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Google Search Volume Index: A Systematic Review

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Google Search Volume Index: A Systematic Review

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dc.contributor.author Ayala Marín, María José es_ES
dc.contributor.author Gonzálvez-Gallego, Nicolás es_ES
dc.contributor.author Arteaga-Sánchez, Rocío es_ES
dc.date.accessioned 2024-01-10T11:20:12Z
dc.date.available 2024-01-10T11:20:12Z
dc.date.issued 2023-09-22
dc.identifier.isbn 9788413960869
dc.identifier.uri http://hdl.handle.net/10251/201697
dc.description.abstract [EN] Information is a crucial and key element when studying stock markets and the way it is analyzed can be determinant for measuring financial market movements. With Internet uptake, investors are exposed to a vast amount of information and hence, analyzing what they search can provide relevant data about potential investment actions and trading decisions. In other words, measuring what investors search yields information about how present and future assets prices change. Recently, the research community has focus on measuring investor attention through search queries on Google. In this manner, investor attention is considered as the frequency of a specific term searched, presented by Google Search Volume Index (GSVI). This paper conducts a systematic review of the current literature about the use of Google Search Volume Index (GSVI) as a proxy variable for investor attention and stock market movements explanations. Using Web of Sciences and Science Direct data bases, we analyze 51 academic studies published between 2010 and 2021. The articles are classified and synthetixed based on the selection criteria for building GSVI: keyword of the search term,, market region and frequency of the data sample. After that, we analyze the effect over the financial variable Return, Volatility and Trading volume. The main results can be summarized as follows: (1) GSVI is positively related with volatility and trading volume regardless the keyword, market region or frequency used for the sample. Hence, an increase on investor attention toward a specific financial term will lead to an increment on volatility and trading volume; (2) GSVI can improve forecasting models for stock market movements. To conclude, this paper consolidates for the first time the research literature about GSVI, being highly valuable for academic practitioners of the area. es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof 5th International Conference on Advanced Research Methods and Analytics (CARMA 2023)
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Google Trends es_ES
dc.subject Investor attention es_ES
dc.subject GSVI es_ES
dc.subject Stock market prediction es_ES
dc.title Google Search Volume Index: A Systematic Review es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Ayala Marín, MJ.; Gonzálvez-Gallego, N.; Arteaga-Sánchez, R. (2023). Google Search Volume Index: A Systematic Review. Editorial Universitat Politècnica de València. 83-84. http://hdl.handle.net/10251/201697 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2023 - 5th International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate Junio 28-30, 2023 es_ES
dc.relation.conferenceplace Sevilla, España es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2023/paper/view/16427 es_ES
dc.description.upvformatpinicio 83 es_ES
dc.description.upvformatpfin 84 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\16427 es_ES


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