IDEAS home Printed from https://ideas.repec.org/p/cdl/anderf/qt8zz2d0q8.html
   My bibliography  Save this paper

Simulated Likeliehood Estimation of Diffusions With an Application to the Short Tem Interest Rate

Author

Listed:
  • Santa-Clara, Pedro

Abstract

This paper develops a new econometric method to estimate continuous time processes from discretely sampled data. This method extends the maximum likelihood technique to cases where the transition density of the process cannot be computed in closed form but can nevertheless be computed by simulation. The asymptotic properties of the estimator are obtained, showing it to have the same behavior in large samples of the (unknown) true likelihood estimator. That is, the simulated likelihood estimator is consistent and asymptotically normal. The econometric method is used to estimate the parameters of a broad family of processes for the short-term interest rate and test some restrictions to well-known models of the term structure.

Suggested Citation

  • Santa-Clara, Pedro, 1997. "Simulated Likeliehood Estimation of Diffusions With an Application to the Short Tem Interest Rate," University of California at Los Angeles, Anderson Graduate School of Management qt8zz2d0q8, Anderson Graduate School of Management, UCLA.
    • Handle: RePEc:cdl:anderf:qt8zz2d0q8
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/8zz2d0q8.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Sun, Libo & Lee, Chihoon & Hoeting, Jennifer A., 2015. "A penalized simulated maximum likelihood approach in parameter estimation for stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 54-67.

    More about this item

    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:cdl:anderf:qt8zz2d0q8. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/aguclus.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.