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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Information Technology & Decision Making
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
