World Scientific
  • Search
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
Our website is made possible by displaying certain online content using javascript.
In order to view the full content, please disable your ad blocker or whitelist our website

System Upgrade on Tue, Oct 25th, 2022 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at [email protected] for any enquiries.


    Applying genetic programming and artificial neural networks to raw as well as wavelet-transformed exchange rate data showed that genetic programming may have good extended forecasting abilities. Although it is well known that most predictions of exchange rates using many alternative techniques could not deliver better forecasts than the random walk model, in this paper employing natural computational strategies to forecast three different exchange rates produced two extended forecasts (that go beyond one-step-ahead) that are better than naïve random walk predictions. Sixteen-step-ahead forecasts obtained using genetic programming outperformed the one- and sixteen-step-ahead random walk US dollar/Taiwan dollar exchange rate predictions. Further, sixteen-step-ahead forecasts of the wavelet-transformed US dollar/Japanese Yen exchange rate also using genetic programming outperformed the sixteen-step-ahead random walk predictions of the exchange rate. However, random walk predictions of the US dollar/British pound exchange rate outperformed all forecasts obtained using genetic programming. Random walk predictions of the same three exchange rates employing raw and wavelet-transformed data also outperformed all forecasts obtained using artificial neural networks.


    • R. T. Baillie and T. Bollerslev, Journal of Business and Economic Statistics 7, 297 (1989). ISIGoogle Scholar
    • D. Hsieh, Journal of Business and Economic Statistics 7, 307 (1989). ISIGoogle Scholar
    • A. Cecen and C. Erkal, International Journal of Forecasting 12, 465 (1996). Crossref, ISIGoogle Scholar
    • C. Kuan and T. Liu, Journal of Applied Econometrics 10, 347 (1995). Crossref, ISIGoogle Scholar
    • G. Zang and M. Hu, Omega, International Journal of Management Science 26, 495 (1998). Crossref, ISIGoogle Scholar
    • M. Clements and J. Smith, Journal of International Money and Finance 20, 133 (2001). CrossrefGoogle Scholar
    • G. Zang and V. Berardi, Journal of Operations Research Society 52, 652 (2001). Crossref, ISIGoogle Scholar
    • N. Meade, International Journal of Forecasting 18, 67 (2002). Crossref, ISIGoogle Scholar
    • A.-S. Chen and M. Leung, Computers and Operations Research 31, 1049 (2004). Crossref, ISIGoogle Scholar
    • F. Fernandez-Rodriguez, S. Sosvilla-Rivero and J. Andrada-Felix, Computational Intelligence in Economics and Finance, eds. S.-H. Chen and P. Wang (Springer-Verlag, Berlin, 2004) pp. 297–325. CrossrefGoogle Scholar
    •, (2004) . Google Scholar
    • S.-H. Chen and T.-W. Kuo, Computational Intelligence in Economics and Finance, eds. S.-H. Chen and P. P. Wang (Springer-Verlag, Berlin, 2004) pp. 329–347. CrossrefGoogle Scholar
    • B.   Efron , The Jackknife, the Bootstrap, and Other Resampling Plans ( Society for Industrial and Applied Mathematics , Philadelphia , 1982 ) . CrossrefGoogle Scholar
    • D. Donoho and I. Johnstone, Journal of the American Statistical Association 90, 1200 (1995). Crossref, ISIGoogle Scholar
    • Z. Pan and X. Wang, Computational Economics 11, 89 (1998). CrossrefGoogle Scholar
    • V. Cherkassky and X. Shao, Neural Networks 14, 37 (2001). Crossref, ISIGoogle Scholar
    • R.   Gençay , F.   Selçuk and B.   Whitcher , An Introduction to Wavelets and Other Filtering Methods in Finance and Economics ( Academic Press , San Diego , 2002 ) . Google Scholar
    • G. Lee, Journal of Economic Theory and Econometrics 4, 123 (1998). Google Scholar
    • J.   Walker , A Primer on Wavelets and Their Scientific Applications ( Chapman & Hall/CRC , Boca Raton , 1999 ) . CrossrefGoogle Scholar
    • S. Mallat, IEEE Transactions on Pattern Analysis and Machine Intelligence 11, 674 (1989). Crossref, ISIGoogle Scholar
    • J.   Koza , Genetic Programming ( The MIT Press , Cambridge, MA , 1992 ) . Google Scholar
    • M. Kaboudan, TSGP: A time series genetic programming software, (2003) . Google Scholar
    • M. Kaboudan, Journal of Economic Dynamics and Control 25, 1719 (2001). Crossref, ISIGoogle Scholar
    • J.   Principe , N.   Euliano and C.   Lefebvre , Neural and Adaptive Systems: Fundamentals Through Simulations ( John Wiley & Sons, Inc. , New York , 2000 ) . Google Scholar