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 Inc
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.
Açıklama
Anahtar Kelimeler
Portfolio selection, imprecise probability, possibility theory, fuzzy logic, triangular fuzzy numbers, subjective judgments, principal components analysis, mean-variance model
Kaynak
Journal of Multiple-Valued Logic and Soft Computing
WoS Q Değeri
Q2
Scopus Q Değeri
Cilt
32
Sayı
5-6
