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

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

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Title: CLASSIFYING NEWS ANNOUNCEMENTS USING NAÏVE BAYES METHOD TO PREDICT EURO / DOLLAR VOLATILITIES
Author: Meliala, Janita S; Faustine, Petrina; Wijaya, Luxky
Abstract: Commonly 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.
URI: http://repository.widyatama.ac.id/xmlui/handle/123456789/1318
Date: 2008


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