Forex-Foreteller: Currency Trend Modeling Using News Articles

KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Chicago Illinois USA August, 2013(2013)

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摘要
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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关键词
Topic discovery,currency markets,sentiment analysis
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