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Portföy optimizasyonunda SVFM ile bulanık doğrusal olmayan model yaklaşımı

Authors: Kocadağlı, Ozan; Cinemre, Nalan;

Portföy optimizasyonunda SVFM ile bulanık doğrusal olmayan model yaklaşımı

Abstract

Hisse senedi piyasalarında dogru yatırım kararları alabilmek için göz önünde bulundurulması gereken en önemli iki faktör getiri ve risktir. Bu ikiliye ait bilgi açık ve kesin olmadıgından, portföy optimizasyonunda kullanılan deterministik ve stokastik modeller yatırım kararları için yeterli olmamaktadır. Bu çalısmada, getiri ve risk için gelistirilen üyelik fonksiyonları yardımıyla "Bulanık Dogrusal Olmayan Portföy Modeli" gelistirilmistir. Bu modelin kurulmasında ilk olarak, Konno ve Yamazaki’nin deterministik portföy modeli temel alınmıstır. İkinci asama olarak, Konno ve Yamazaki’nin modelinin beklenen getiri kısıtı bulanıklastırılmıstır. Beklenen getirinin bulanık olmasından dolayı riski ifade eden amaç fonksiyonu degerleri de bulanık sayı olarak kabul edilmis ve böylece bulanık amaç ve kaynaklı dogrusal olmayan portföy modeli olusturulmustur. Ayrıca, önerilen modelin pazarın trendini de göz önünde bulundurması için, 'sermaye Varlıklarını Fiyatlandırma Modeli (SVMF)" ile uyumlu bir beta üyelik fonksiyonu olusturulmus ve bu fonksiyon yardımıyla modele, pazarın hassasiyetini içeren bir kısıt eklenmistir. Uygulama kısmında, iMKB30 da islem gören hisse senetlerinin kapanıs degerleri kullanılarak, önerilen modelin performansı Markowitz ve Konno–Yamazaki modellerinin performanslarıyla karsılastırılmıstır

In the stocks markets, main factors which have to be considered to make accurate investment decisions are return and risk. Since the knowledge related this couple is not certain and precise, deterministic and stochastic models used in portfolio optimization are not sufficient for investment decisions. In this study, a new fuzzy nonlinear portfolio model is proposed by means of membership functions developed for return and risk. In construction of the mentioned model, Konno and Yamazaki's model is taken as reference model. As a second stage, expected return of this model is assumed to be fuzzy. Since the expected return is taken as fuzzy, the values of objective function which denote risk can also be accepted as fuzzy. For this reason the nonlinear programming model with fuzzy source and objective is constituted. Besides, in order to consider stocks market trend, the constraint, which includes sensitivity of market, is added in this model by means of membership function of portfolio beta that is consistent with Capital Asset Pricing Model (CAPM). In application part, using the closure data of stocks operated in ISE30 index, the performance of the proposed model is compared with ones of Markowitz and Konno-Yamazaki model

Country
Turkey
Keywords

Fuzzy mathematical programming;nonlinear programming;fuzzy portfolio optimization;Konno-Yamazaki portfolio model;beta coeffecient;CAPM, Bulanık matematiksel programlama;doğrusal olmayan programlama;bulanık portföy optimizasyonu;Konno-Yamazaki portföy modeli;beta katsayısı;SVFM

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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