Advertisement

Exchange Rate Modelling Using News Articles and Economic Data

  • Debbie Zhang
  • Simeon J. Simoff
  • John Debenham
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3809)

Abstract

This paper provides a framework of using news articles and economic data to model the exchange rate changes between Euro and US dollars. Many studies have conducted on the approach of regressing exchange rate movement using numerical data such as macroeconomic indicators. However, this approach is effective in studying the long term trend of the movement but not so accurate in short to middle term behaviour. Recent research suggests that the market daily movement is the result of the market reaction to the daily news. In this paper, it is proposed to use text mining methods to incorporate the daily economic news as well as economic and political events into the prediction model. While this type of news is not included in most of existing models due to its non-quantitative nature, it has important influence in short to middle terms of market behaviour. It is expected that this approach will lead to an exchange rate model with improved accuracy.

Keywords

Exchange Rate Euro Area News Article Exchange Rate Regime Menu Item 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Rose, A.K.: Exchange rate regimes and stability: Where do we stand? Technical Report Unpublished working report, U.C. Berkeley (2004)Google Scholar
  2. 2.
    Meese, R., Rogoff, K.: Empirical exchange rate models of the seventies. do they fit out of sample? Journal of International Economics 14, 3–24 (1983)CrossRefGoogle Scholar
  3. 3.
    Dornbusch, R.: Expectations and exchange rate dynamics. Journal of Political Economy 84, 1161–1176 (1976)CrossRefGoogle Scholar
  4. 4.
    Prast, H.M., de Vor, M.P.H.: Investor reactions to news: a cognitive dissonance analysis of the euro-dollar exchange rate. European Journal of Political Economy 21(1), 115–141 (2005) TY- JOURGoogle Scholar
  5. 5.
    Ehrmann, M., Fratzscher, M.: Exchange rates and fundamentals: new evidence from real-time data. Journal of International Money and Finance 24, 317–341 (2005) TY- JOURCrossRefGoogle Scholar
  6. 6.
    Eddelbüttel, D., McCurdy, T.: The impact of news on foreign exchange rates: evidence from high frequency data. Technical report, University of Toronto (1998)Google Scholar
  7. 7.
    Peramunetilleke, D., Wong, R.K.: Currency exchange rate forecasting from news headlines. Aust. Comput. Sci. Commun. 24, 131–139 (2002)Google Scholar
  8. 8.
    Manning, C.D., Schutze, H.: Foundations of statistical natural language processing. MIT Press, Cambridge; Christopher D. Manning, Hinrich Schéutze. 24 cm (1999)Google Scholar
  9. 9.
    Dunning, T.: Accurate methods for the statistics of surprise and coincidence. Computational Linguistics 19, 61–74 (1994)Google Scholar
  10. 10.
    Vogel, D.: Using generic corpora to learn domain-specific terminology. In: The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Workshop on Link Analysis for Detecting Complex Behavior), Washington, DC, USA (2003)Google Scholar
  11. 11.
    Berry, M.W.: Survey of text mining: clustering, classification, and retrieval. Springer, New York (2003)Google Scholar
  12. 12.
    Galati, G., Ho, C.: Macroeconomic news and the euro/dollar exchange rate. Technical Report 105, Bank for International Settlements (2001)Google Scholar
  13. 13.
    Zhang, D., Simoff, S.: Informing the curious negotiator: Automatic news extraction from the internet. In: Australasian Data Mining Conference, Cairns, Australia (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Debbie Zhang
    • 1
  • Simeon J. Simoff
    • 1
  • John Debenham
    • 1
  1. 1.Faculty of Information TechnologyUniversity of TechnologySydney

Personalised recommendations