A new possibilistic mean – Variance model based on the principal components analysis: An application on the Turkish holding stocks
Küçük Resim Yok
Tarih
2019
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Old City Publishing
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Possibility Theory is a great tool to deal with the imprecise probability. However, the possibilistic counterpart of the mean – variance (MV) model has serious shortcomings. Thus, we propose a new possibilistic MV model, which depends on the Principal Components Analysis. The proposed model enables to incorporate subjective judgments into the portfolio selection. In addition, it captures the asymmetry in the return data unlike the MV model. The proposed model is also tractable as the MV model since it can be expressed as a concave quadratic maximization problem. After laying down the theoretical points, we illustrate it by using a real data set of six holding stocks trading on the Borsa Istanbul (BIST). We also compare the profitability and performance results of the proposed model and the MV model. © 2019 Old City Publishing, Inc.
Açıklama
Anahtar Kelimeler
Fuzzy logic, Imprecise probability, Mean-variance model, Portfolio selection, Possibility theory, Principal components analysis, Subjective judgments, Triangular fuzzy numbers
Kaynak
Journal of Multiple-Valued Logic and Soft Computing
WoS Q Değeri
Scopus Q Değeri
Q3
Cilt
32
Sayı
5-6
