IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article

An automated econometric decision support system: forecasts for foreign exchange trades

  • Bernd Brandl

    ()

  • Christian Keber
  • Matthias Schuster
Registered author(s):

    Making decisions challenges foreign exchange (FX) market brokers due to the volatility of the foreign exchange market, as well as the unmanageable flood of possibly relevant information. Thus, decision making in this complex and dynamically changing environment is a difficult task requiring automated decision support systems. In this contribution, we describe an econometric decision support approach, which enables the extraction of essential information indispensable to set up accurate forecasting models. Our approach is based on a genetic algorithm (GA) and applies the resulting models to forecast daily EUR/USD-exchange rates. In doing so, the genetic algorithm optimizes single-equation regression forecast models. The approach discussed is new in literature and, moreover, allows flexibility in automated model selection within a reasonably short time. Copyright Springer-Verlag 2006

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://hdl.handle.net/10.1007/s10100-006-0013-8
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Springer & Slovak Society for Operations Research & Hungarian Operational Research Society & Czech Society for Operations Research & Österr. Gesellschaft für Operations Research (ÖGOR) & Slovenian Society Informatika - Section for Operational Research & Croatian Operational Research Society in its journal Central European Journal of Operations Research.

    Volume (Year): 14 (2006)
    Issue (Month): 4 (December)
    Pages: 401-415

    as
    in new window

    Handle: RePEc:spr:cejnor:v:14:y:2006:i:4:p:401-415
    Contact details of provider: Web page: http://www.springer.com

    Web page: http://www.fhi.sk/ssov

    Web page: http://www.mot.org.hu/index_en.html

    Web page: http://nb.vse.cz/csov/english.htm

    Web page: http://www.oegor.at/

    Web page: http://www.drustvo-informatika.si/sekcije/sor/

    Web page: http://hdoi.hr/en_US/en/

    Order Information: Web: http://www.springer.com/business/operations+research/journal/10100

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. Pesaran, M Hashem & Timmermann, Allan G, 2004. "Real Time Econometrics," CEPR Discussion Papers 4402, C.E.P.R. Discussion Papers.
    2. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(04), pages 405-426, December.
    3. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    4. Francis X. Diebold & James M. Nason, 1989. "Nonparametric exchange rate prediction?," Finance and Economics Discussion Series 81, Board of Governors of the Federal Reserve System (U.S.).
    5. Yin-Wong Cheung & Menzie D. Chinn, 2000. "Currency Traders and Exchange Rate Dynamics: A Survey of the U.S. Market," CESifo Working Paper Series 251, CESifo Group Munich.
    6. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
    7. Peter C.B. Phillips, 2004. "Automated Discovery in Econometrics," Cowles Foundation Discussion Papers 1469, Cowles Foundation for Research in Economics, Yale University.
    8. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    9. Vilasuso Jon & Cunningham Steve, 1996. "Tests for Nonlinearity in EMS Exchange Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(3), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:spr:cejnor:v:14:y:2006:i:4:p:401-415. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)

    or (Rebekah McClure)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.