IDEAS home Printed from https://ideas.repec.org/a/taf/eurjfi/v11y2005i2p137-150.html
   My bibliography  Save this article

Prediction in chaotic time series: methods and comparisons with an application to financial intra-day data

Author

Listed:
  • D. Guegan
  • L. Mercier

Abstract

Different prediction methods for chaotic deterministic systems are compared. Two methods of reconstructing the dynamics of the systems are considered with a view to producing a profitable trading model. The methods developed are the 'nearest neighbours' method and the 'radial basis functions' method. The optimal prediction horizon according to the sampling time step, and a reliable method to measure the prediction error are discussed. These methods are applied to the intra-day series of exchange rates, namely DEM/FRF. Developments concerning the importance of noise when chaotic systems are studied are provided.

Suggested Citation

  • D. Guegan & L. Mercier, 2005. "Prediction in chaotic time series: methods and comparisons with an application to financial intra-day data," The European Journal of Finance, Taylor & Francis Journals, vol. 11(2), pages 137-150.
  • Handle: RePEc:taf:eurjfi:v:11:y:2005:i:2:p:137-150
    DOI: 10.1080/13518470110074846
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/13518470110074846
    Download Restriction: Access to full text is restricted to subscribers.

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

    References listed on IDEAS

    as
    1. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-337, July.
    2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. repec:dau:papers:123456789/12729 is not listed on IDEAS
    5. Dominique Guegan & Mercier Ludovic, 1997. "prediction in chaotic time series: methods and comparisons using simulations," Post-Print halshs-00375663, HAL.
    6. Weigend, Andreas S. & Lebaron, Blake, 1994. "Evaluating Neural Network Predictors by Bootstrapping," SFB 373 Discussion Papers 1994,35, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Gaëlle Le Fol & Mercier Ludovic, 1998. "Time Deformation: Definition and Comparisons," Post-Print halshs-00586097, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Rachida Hennani & Michel Terraza, 2015. "Contributions of a noisy chaotic model to the stressed Value-at-Risk," Economics Bulletin, AccessEcon, vol. 35(2), pages 1262-1273.
    2. Rachida Hennani, 2015. "Can the Lasota(1977)’s model compete with the Mackey-Glass(1977)’s model in nonlinear modelling of financial time series?," Working Papers 15-09, LAMETA, Universtiy of Montpellier, revised Jun 2015.
    3. Dominique Guegan, 2007. "Chaos in economics and finance," Post-Print halshs-00187885, HAL.
    4. Dominique Guegan, 2009. "Chaos in Economics and Finance," Post-Print halshs-00375713, HAL.

    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:taf:eurjfi:v:11:y:2005:i:2:p:137-150. 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: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/REJF20 .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.