IDEAS home Printed from https://ideas.repec.org/a/wsi/nmncxx/v01y2005i01ns1793005705000056.html
   My bibliography  Save this article

Extended Daily Exchange Rates Forecasts Using Wavelet Temporal Resolutions

Author

Listed:
  • MAK KABOUDAN

    (School of Business, University of Redlands, 1200 East Colton Avenue, Redlands, California 92373, USA)

Abstract

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.

Suggested Citation

  • Mak Kaboudan, 2005. "Extended Daily Exchange Rates Forecasts Using Wavelet Temporal Resolutions," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 79-107.
    • Handle: RePEc:wsi:nmncxx:v:01:y:2005:i:01:n:s1793005705000056
    DOI: 10.1142/S1793005705000056
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S1793005705000056
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S1793005705000056?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jalal Shiri & Ali Keshavarzi & Ozgur Kisi & Sahar Mohsenzadeh Karimi & Sepideh Karimi & Amir Hossein Nazemi & Jesús Rodrigo-Comino, 2020. "Estimating Soil Available Phosphorus Content through Coupled Wavelet–Data-Driven Models," Sustainability, MDPI, vol. 12(5), pages 1-23, March.
    2. Joanna Bruzda, 2020. "The wavelet scaling approach to forecasting: Verification on a large set of Noisy data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 353-367, April.
    3. Ozgur Kisi, 2011. "Wavelet Regression Model as an Alternative to Neural Networks for River Stage Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(2), pages 579-600, January.
    4. Fathi Abid & Wafa Abdelmalek & Sana Ben Hamida, 2020. "Dynamic Hedging using Generated Genetic Programming Implied Volatility Models," Papers 2006.16407, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:nmncxx:v:01:y:2005:i:01:n:s1793005705000056. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/nmnc/nmnc.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.