CLASSIFYING NEWS ANNOUNCEMENTS USING NAÏVE BAYES METHOD TO PREDICT EURO / DOLLAR VOLATILITIES

dc.contributor.authorMeliala, Janita S
dc.contributor.authorFaustine, Petrina
dc.contributor.authorWijaya, Luxky
dc.date.accessioned2011-03-21T06:31:02Z
dc.date.accessioned2019-10-21T11:45:52Z
dc.date.available2011-03-21T06:31:02Z
dc.date.available2019-10-21T11:45:52Z
dc.date.issued2008
dc.description.abstractCommonly used analysis of price movements in foreign exchange (forex) market are fundamental analysis and technical analysis. One among many indicators which influences the forex price is news articles. In this study, it was selected and classified news announcements which affected euro/dollar return volatilities. By using the Naïve Bayes theorem, the news was “weighted” to become the predictor of the forex price movements. The post-announcement reactions were highlighted and analyzed. They were classified and labeled as: “up”, “down”, or “unchanged”. The study revealed a significant predictive power of news announcements over the forex price movements of euro/dollar return volatilities.en_US
dc.identifier.urihttp://repository.widyatama.ac.id/handle/123456789/1318
dc.language.isootheren_US
dc.publisherUniversitas Widyatamaen_US
dc.relation.ispartofseries;KII CD 008
dc.subjectNaïve Bayesen_US
dc.subjectforexen_US
dc.subjectnews announcementen_US
dc.titleCLASSIFYING NEWS ANNOUNCEMENTS USING NAÏVE BAYES METHOD TO PREDICT EURO / DOLLAR VOLATILITIESen_US
dc.typeOtheren_US
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