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Bu çalışmanın amacı tutucu yatırımcılar için sürdürülebilir portföy seçimini incelemektir. Bu kapsamda iki aşamalı bir yaklaşım önerilmiştir. İlk aşamada hisse senetlerinin sürdürülebilirlik skorları, R-FES olarak kısaltılan bir bulanık çok kriterli karar verme (ÇKKV) yaklaşımıyla uzman bilgisinden yararlanılarak elde edilmiştir. İkinci aşamada sürdürülebilirlik skoru vektörünü, örneklem ortalama vektörünü ve örneklem kovaryans matrisini dikkate alan bir dayanıklı optimizasyon problemi oluşturulmuştur. Ayrıca bu problemin analitik çözümü belirli varsayımlar altında verilmiştir. Önerilen dayanıklı teorik yaklaşımı tanıtmak amacıyla BIST katılım sürdürülebilirlik endeksi hisseleri üzerine bir uygulama yapılmıştır. Yapılan uygulamada sürdürülebilir yatırımın performans kaybına neden olmayabileceği görülmüştür. Ayrıca kısa pozisyon almama kısıtının; performansı artırırken, riski ve getiriyi azalttığı görülmüştür.

This study aims to examine sustainable portfolio selection for conservative investors. In this context, a two-stage approach is proposed. In the first stage, the sustainability scores of stocks are obtained by utilizing expert knowledge through a fuzzy multicriteria decision-making (FMCDM) approach abbreviated as R-FES. In the second stage, a robust optimization problem that takes into account the sustainability score vector, the sample mean vector and the sample covariance matrix is formulated. Moreover, the analytical solution of this problem is given under certain assumptions. In order to introduce the proposed robust theoretical approach, an application on BIST participation sustainability index stocks is made. In the application, it is seen that sustainable investment may not cause performance loss. In addition, the constraint of not taking short positions is found to improve performance while reducing risk and return. [ABSTRACT FROM AUTHOR]

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It is easy to use possibility theory in modeling incomplete information. Robust optimization is an important tool when there is parameter uncertainty. Thus, in this study, we propose robust versions of the lower and upper possibilistic mean - variance (MV) models when there are multiple possibility distribution scenarios. Here, we use entropy as a diversification constraint. In addition, we reduce these robust versions to concave maximization problems. Furthermore, we generalize them for two periods portfolio selection problem by using fuzzy addition and multiplication. On the other hand, these generalizations are not concave maximization problems. Finally, we give an illustrative example by using different solvers in Gams modeling system. [ABSTRACT FROM AUTHOR]