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dc.contributor.advisorMolnár, Peter
dc.contributor.authorKim, Neri
dc.contributor.authorVilla, Roviel
dc.descriptionMaster's thesis in Financenb_NO
dc.description.abstractWe investigate whether Google search volume index (SVI) can explain and predict trading activity at the Norwegian stock market (OSE). Our sample focuses on the companies listed on OSE’s tradeable index OBX. We use abnormal returns, trading volume, and volatility as measures of market activity. SVI were classified as a) search term, which Google uses to keep track of word-specific search queries; and b) business term, which Google uses to keep track of all search queries done in any language and classifies these queries together under one topic. The regression models we developed were two-fold: (1) a descriptive model that tests whether a relationship exists between each of the three indicators and SVI; and (2) a predictive model that tests the predictive power of SVI towards the three indicators. Our results show that both SVIs neither exhibit a significant relationship nor a predictive power on abnormal returns. However, both SVIs show a significant positive relationship and a predictive power on trading volume. Lastly, search activity only exhibits a predictive power with volatility. Therefore, Google searches can tell more about future trading activity than current trading activity.nb_NO
dc.publisherUniversity of Stavanger, Norwaynb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.subjectGoogle Trendsnb_NO
dc.subjectstock marketnb_NO
dc.subjectfinancial marketsnb_NO
dc.subjectOslo børsnb_NO
dc.subjectsearch volume indexnb_NO
dc.titleGoogle and Financial Markets: Can Google Trends describe and predict the dynamics of Norwegian stock market?nb_NO
dc.typeMaster thesisnb_NO
dc.subject.nsiVDP::Samfunnsvitenskap: 200::Økonomi: 210nb_NO

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal