IDEAS home Printed from https://ideas.repec.org/p/sce/scecfa/276.html
   My bibliography  Save this paper

Using genetic algorithms to improve the term structure of interest rates fitting

Author

Listed:
  • Ricardo Gimeno

    (Research Department Banco de España)

  • Juan M. Nave

    (Universidad de Castilla la Mancha (Spain))

Abstract

The termstructure of interest rates is an instrument that gives us the necessary information for valueing deterministic financial cash flows, measuring the economic market expectations and testing the effectiveness of monetary policy decissions. However, it is not directly observable and needs to be measured by smoothing data obtained from asset prices through statistical techniques. Adjusting parsimonious functional forms - as proposed by Nelson and Siegel (1987) and Svensson (1994) - is the most popular technique. This method is based on bond yields to maturity and the high degree of non-linearity of the functions to be optimised make it very sensitive to the initial values omployed. In this context, this paper proposes the use og genetic algorithms to find these values and reduce the risk of false convergence, showing that stable time series parameters are obtained without the need to impose any kind of restrictions

Suggested Citation

  • Ricardo Gimeno & Juan M. Nave, 2006. "Using genetic algorithms to improve the term structure of interest rates fitting," Computing in Economics and Finance 2006 276, Society for Computational Economics.
  • Handle: RePEc:sce:scecfa:276
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Keywords

    forward and spot interest rates; Nelson and Siegel model; Svensson model; non-linear optimization; numerical methods; Svensson model; yield curve estimation;
    All these keywords.

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    Statistics

    Access and download statistics

    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:sce:scecfa:276. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.html .

    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.