An extension to the classical mean–variance portfolio optimization model |
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Authors: | Çelen N Ötken Z Batuhan Organ E Ceren Y?ld?r?m Mustafa Çaml?ca Volkan S Cantürk Ekrem Duman |
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Institution: | Department of Industrial Engineering, Ozyegin University, Istanbul, Turkey |
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Abstract: | AbstractThe 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. |
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