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Forex Foreteller: News-Based Currency Predictor

A cutting-edge system that predicts currency movements based on news analysis, sentiment analysis, past trends, and economic indicators.

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Forex Foreteller: News-Based Currency Predictor

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  1. Forex-foreteller: A News Based Currency Predictor • Fang Jin (fang8), Nathan Self (nwself), Parang Saraf (parang), Patrick Butler (pabutler), Wei Wang (tskatom) & Naren Ramakrishnan (naren) • Department of Computer Science, Virginia Tech Email: pid@cs.vt.edu

  2. Introduction - Foreign Exchange Market • Most liquid financial market in the world • Average daily turnover was USD 3.98 trillion in April 2010 • Growth of approximately 20% as compared to 2007 • United States GDP is around USD 16.62 trillion • Operates 24 hours a day except on weekends • Geographically Dispersed • Traders include large banks, central banks, institutional investors, currency speculators, corporations, governments and retail investors • A variety of factors effect exchange rate: • Economic Factors • Political Conditions • Market Psychology

  3. Related Work • Fundamental Analysis • Analyses economic health of a country • Employment Reports • Inflation • Productivity • Trade • Growth • Technical Analysis • Mathematical Techniques like VAR, ARCH, GARCH etc • Based on Past Trends of financial indicators • Can’t rely on just one type. Have to use a combination of both the techniques

  4. Our Approach Fundamental Technical Bloomberg News Past Currency Values Unanticipated News Interest Rates Inflation Past Stock Values Linear Regression Model Final Prediction

  5. System Framework

  6. Language Modeling Out of 30 topics, manually identify topics of Interest Latent Dirichlet Allocation Model to identify different topics Top 30 topics are Identified Different Types of News List of Interesting topics

  7. Topic Clustering Identify trending topics by tracking topic distribution movement over time

  8. Sentiment Analysis Inflation Increase/Decrease Interest Rate Increase/Decrease Sentiment Analysis Unanticipated News

  9. Linear Regression Past Stock Values Inflation Past Currency Values Interest Rates Unanticipated News Final Prediction Linear Regression Model • Where: • Δc is currency change • Δr is interest rate change • Δf is interest rate change • Δs is currency change • Δe is currency change • βr, βf, βs, βe are respective weights

  10. Off-line Components

  11. Online Components Displays the generated alerts and associated Audit trails for user analysis

  12. EMBERS Visualizer Link: http://embers.cs.vt.edu/embers/alerts/visualizer_fin?layout=grid

  13. Other EMBERS Products Civil Unrest Predictor Influenza Like Illness Predictor Ablation Visualizer Rare Diseases Predictor Link: http://embers.cs.vt.edu/embers/alerts/visualizer_fin?layout=grid

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