Author
Ötken, Çelen Naz, Organ, Zeynel Batuhan, Yıldırım, Elif Ceren, Çamlıca, Mustafa, Cantürk, Volkan Selim, Duman, Ekrem, Teksan, Zehra Melis, Kayış, Enis
Publication Date
2019-07
Publication Place
-
Taylor & Francis
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
0013-791X
Record ID
9837223d-d7d3-4cc6-9dd5-685c561fdb58
Library Location
Industrial Engineering
Date
2019-07
Sample Text
The purpose of this study is to find a portfolio that maximizes the risk-adjusted returns subject to constraints frequently faced during portfolio management by extending the classical Markowitz mean-variance portfolio optimization model. We propose a new two-step heuristic approach, GRASP & SOLVER, that evaluates the desirability of an asset by combining several properties about it into a single parameter. Using a real-life data set, we conduct a simulation study to compare our solution to a benchmark (S&P 500 index). We find that our method generates solutions satisfying nearly all of the constraints within reasonable computational time (under an hour), at the expense of a 13% reduction in the annual return of the portfolio, highlighting the effect of introducing these practice-based constraints.
DOI
10.1080/0013791X.2019.1636440
Cilt
64
