IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-319-02499-8_7.html
   My bibliography  Save this book chapter

Fitting Financial Returns Distributions: A Mixture Normality Approach

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Riccardo Bramante

    (University Cattolica del Sacro Cuore, Department of Statistical Sciences)

  • Diego Zappa

    (University Cattolica del Sacro Cuore, Department of Statistical Sciences)

Abstract

An important research field in finance is the identification of probability distribution model that fits at the best the empirical distribution of time series returns. In this paper we propose the use of mixtures of truncated normal distributions in modelling returns. An optimization algorithm has been developed to obtain the best fit by using the minimum distance approach. Empirical results show evidence of the capability of the method to fit return distributions at a satisfactory level, completely maintaining local normality properties in the model. Moreover, the model provides a good tail fit thus improving the accuracy of Value at Risk estimates.

Suggested Citation

  • Riccardo Bramante & Diego Zappa, 2014. "Fitting Financial Returns Distributions: A Mixture Normality Approach," Springer Books, in: Marco Corazza & Claudio Pizzi (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 81-88, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-02499-8_7
    DOI: 10.1007/978-3-319-02499-8_7
    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
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-3-319-02499-8_7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.