An extension to the classical mean–variance portfolio optimization model

Çelen N. Ötken, Z. Batuhan Organ, E. Ceren Yıldırım, Mustafa Çamlıca, Volkan S. Cantürk, Ekrem Duman, Z. Melis Teksan and Enis Kayış

The Engineering Economist, 2019, vol. 64, issue 3, 310-321

Abstract: 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.

Date: 2019
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DOI: 10.1080/0013791X.2019.1636440

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