Advanced Search
MyIDEAS: Login to save this paper or follow this series

Some Simple ML Estimators in Stochastic Differential Equations

Contents:

Author Info

  • Erling B. Andersen

    (University of Copenhagen, Institute of Economics)

Registered author(s):

    Abstract

    For many stochastic differential equations often met in financial theory, it is the drift and the dispersion which are the principal parameters of the model. In such cases it is shown that the parameters can be estimated by ordinary methods from normal distribution theory.

    Download Info

    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://www.econ.ku.dk/english/research/publications/wp/2001/0110.pdf/
    Download Restriction: no

    Bibliographic Info

    Paper provided by University of Copenhagen. Department of Economics in its series Discussion Papers with number 01-10.

    as in new window
    Length: 12 pages
    Date of creation: Oct 2001
    Date of revision:
    Handle: RePEc:kud:kuiedp:0110

    Contact details of provider:
    Postal: Ă˜ster Farimagsgade 5, Building 26, DK-1353 Copenhagen K., Denmark
    Phone: (+45) 35 32 30 10
    Fax: +45 35 32 30 00
    Email:
    Web page: http://www.econ.ku.dk
    More information through EDIRC

    Related research

    Keywords: Stochastic differential equations; ML estimates; financial models;

    This paper has been announced in the following NEP Reports:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Lists

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

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:kud:kuiedp:0110. 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: (Thomas Hoffmann).

    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.