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  Forex Articles & Studies
 
 
 
              Forex-Foreteller: Currency Trend Modeling using News Articles
 
 
 Authors: Fang Jin. Department of Computer Science, Virginia Tech
               Nathan Self. Department of Computer Science, Virginia Tech
               Parang Saraf. Department of Computer Science, Virginia Tech
               Patrick Butler. Department of Computer Science, Virginia Tech
               Wei Wang. Department of Computer Science, Virginia Tech
               Naren Ramakrishnan Department of Computer Science, Virginia Tech
                                         Date: August 2013
 
 Abstract:

Financial markets are quite sensitive to unanticipated news and events. Identifying the effect of news on the market is a challenging task. In this demo, we present Forex-foreteller (FF) which mines news articles and makes forecasts about the movement of foreign currency markets. The system uses a combination of language models, topic clustering, and sentiment analysis to identify relevant news articles. These articles along with the historical stock index and currency exchange values are used in a linear regression model to make forecasts. The system has an interactive visualizer designed specifically for touch-sensitive devices which depicts forecasts along with the chronological news events and financial data used for making the forecasts.

 
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