IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v21y2022i02ns0219622021500589.html
   My bibliography  Save this article

Decision Support for Portfolio Management by Information System with Black–Litterman Model

Author

Listed:
  • Todor Stoilov

    (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Acad. G. Bonchev Street, BL2, Bulgaria)

  • Krasimira Stoilova

    (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Acad. G. Bonchev Street, BL2, Bulgaria)

  • Miroslav Vladimirov

    (��Varna University of Economics, Administration and Management Department, 9002 Varna, 1 Kniaz Boris Street, Bulgaria)

Abstract

An algorithm is derived for the development of portfolio decision-support information service. The algorithm allows being automated evaluations for the definition and solution of portfolio problems. Small set of historical data of asset returns with limited set of assets are used for the portfolio, which is the case for no institutional portfolio manager. The algorithm applies analytical relations for decreasing the computational workload for the estimation of the market parameters due to the limited number of assets. The subjective expert views in the Black–Litterman (BL) model are defined from additional assessment of historical data of the asset returns. The algorithm makes comparisons of the results for active portfolio management from the mean variance (MV) model, the BL one and the equal-weighted investment strategy. Benefits of the algorithm are the usage of small set of historical data and limited number of assets, which are proved in investment rolling horizon.

Suggested Citation

  • Todor Stoilov & Krasimira Stoilova & Miroslav Vladimirov, 2022. "Decision Support for Portfolio Management by Information System with Black–Litterman Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 643-664, March.
    • Handle: RePEc:wsi:ijitdm:v:21:y:2022:i:02:n:s0219622021500589
    DOI: 10.1142/S0219622021500589
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622021500589
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219622021500589?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:wsi:ijitdm:v:21:y:2022:i:02:n:s0219622021500589. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    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.