IDEAS home Printed from https://ideas.repec.org/a/rfa/aefjnl/v2y2015i2p1-13.html
   My bibliography  Save this article

Applications of §®-GARCH Model for the Selection of Securities of Banks¡¯ Investment Portfolio

Author

Listed:
  • Eleftherios I. Thalassinos
  • Bozhana Venediktova
  • Vicky Zampeta

Abstract

The main aim of this article is to investigate the accuracy of the Multivariate Generalized Autoregressive Conditional Heteroskedasticity Model (M-GARCH) for the selection of the best investment portfolio. There is extended literature on M-GARCH in this field with a great number of studies using different sets of variables among them the returns of assets, the volatility of the assets in the investment portfolio, the maturity date of the asset etc. The origin of M-GARCH is associated with the elements of the Dynamic Conditional Correlations Model (DDCM) as proposed by Engle. An earlier version of DDCM with time variations in the correlation matrix has been developed by Bollerslev. DCCM offers flexibility by incorporating different levels of volatilities able to structure portfolios with a great number of assets. M-GARCH models take into account separate univariate GARCH models, associate with each asset in the portfolio, in order to form a complete M-GARCH model. The present article uses a multiple dimension classic M-GARCH volatility model on a data set consisting from three time series. The daily ASE index on stock returns (Athens), the DAX index (Germany) and the CAC index (France). For each national index, the continuously compounded return was estimated as rt=100[log(pt)-log(pt-1)], where pt is the price on day t.

Suggested Citation

  • Eleftherios I. Thalassinos & Bozhana Venediktova & Vicky Zampeta, 2015. "Applications of §®-GARCH Model for the Selection of Securities of Banks¡¯ Investment Portfolio," Applied Economics and Finance, Redfame publishing, vol. 2(2), pages 1-13, May.
    • Handle: RePEc:rfa:aefjnl:v:2:y:2015:i:2:p:1-13
    as

    Download full text from publisher

    File URL: http://redfame.com/journal/index.php/aef/article/view/711/656
    Download Restriction: no
    File URL: http://redfame.com/journal/index.php/aef/article/view/711
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    commercial banks; m-garch models; portfolio selection; forecasting;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:rfa:aefjnl:v:2:y:2015:i:2:p:1-13. 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: Redfame publishing (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.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.