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Forex-foreteller: A News Based Currency Predictor

Developed by Virginia Tech, EMBERS predicts events in Latin America. Forex market details, analysis techniques, and prediction system framework. Explore more! •

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Forex-foreteller: A News Based Currency Predictor

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  1. Forex-foreteller: A News Based • Currency Predictor • Fang Jin, Nathan Self, Parang Saraf, • Patrick Butler, Wei Wang, Naren Ramakrishnan • Department of Computer Science • Virginia Tech • Aug 13, 2013

  2. EMBERS • Funded by Intelligent Advanced Research Projects Activity (IARPA) • Primarily Interested in making predictions about Latin American Countries • The primary prediction areas are as follows: • Civil Unrest Events • Influenza Like Illness Events • Rare Diseases Events • Elections • Financial Events

  3. 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

  4. 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

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

  6. System Framework

  7. 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

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

  9. Sentiment Analysis • Inflation Increase/Decrease • Interest Rate Increase/Decrease • Sentiment Analysis • Unanticipated News

  10. 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

  11. Off-line Components

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

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

  14. 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

  15. Fang Jin: jfang8@cs.vt.edu Parang Saraf: parang@cs.vt.edu

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