The Possibilistic Mean-Variance Model with Uncertain Possibility Distributions

Furkan Göktaş

Makale detayları

The Possibilistic Mean-Variance Model with Uncertain Possibility Distributions

Yazarlar:

Furkan Göktaş

Yayıncı:

Burdur Mehmet Akif Ersoy University

Ana Başlıklar:

Operations Research | Investment and Portfolio Management

Dergi:

Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty Vol.11 Issue 2, pp.535-550

Belge Tipi:

Makale

Yayın Tarihi:

6/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001321761

pISSN:

2149-1658

Anahtar kelimeler:

Özet:

 The possibilistic meanvariance MV model is the counterpart of Markowitzs MV model in the possibility theory. This study aims to examine the possibilistic MV model when the possibility distributions of stock returns are uncertain triangular fuzzy numbers. We define an uncertainty vector and use its ellipsoidal uncertainty set in a minimax optimization problem to model this uncertainty. We also show that this minimax optimization problem reduces to a strictly convex minimization problem. Thus, unlike the possibilistic MV model, we get diversified optimal portfolios uniquely with our approach. After laying down the theoretical points of our approach, we illustrate it with a real-world example in the literature by using a software package for convex optimization. To the best of our knowledge, this is the first paper that considers uncertain possibility distributions in the possibilistic MV model.

 The possibilistic meanvariance MV model is the counterpart of Markowitzs MV model in the possibility theory. This study aims to examine the possibilistic MV model when the possibility distributions of stock returns are uncertain triangular fuzzy numbers. We define an uncertainty vector and use its ellipsoidal uncertainty set in a minimax optimization problem to model this uncertainty. We also show that this minimax optimization problem reduces to a strictly convex minimization problem. Thus, unlike the possibilistic MV model, we get diversified optimal portfolios uniquely with our approach. After laying down the theoretical points of our approach, we illustrate it with a real-world example in the literature by using a software package for convex optimization. To the best of our knowledge, this is the first paper that considers uncertain possibility distributions in the possibilistic MV model.

 The possibilistic meanvariance MV model is the counterpart of Markowitzs MV model in the possibility theory. This study aims to examine the possibilistic MV model when the possibility distributions of stock returns are uncertain triangular fuzzy numbers. We define an uncertainty vector and use its ellipsoidal uncertainty set in a minimax optimization problem to model this uncertainty. We also show that this minimax optimization problem reduces to a strictly convex minimization problem. Thus, unlike the possibilistic MV model, we get diversified optimal portfolios uniquely with our approach. After laying down the theoretical points of our approach, we illustrate it with a real-world example in the literature by using a software package for convex optimization. To the best of our knowledge, this is the first paper that considers uncertain possibility distributions in the possibilistic MV model.

 The possibilistic meanvariance MV model is the counterpart of Markowitzs MV model in the possibility theory. This study aims to examine the possibilistic MV model when the possibility distributions of stock returns are uncertain triangular fuzzy numbers. We define an uncertainty vector and use its ellipsoidal uncertainty set in a minimax optimization problem to model this uncertainty. We also show that this minimax optimization problem reduces to a strictly convex minimization problem. Thus, unlike the possibilistic MV model, we get diversified optimal portfolios uniquely with our approach. After laying down the theoretical points of our approach, we illustrate it with a real-world example in the literature by using a software package for convex optimization. To the best of our knowledge, this is the first paper that considers uncertain possibility distributions in the possibilistic MV model.

Makale detayları

The Possibilistic Mean-Variance Model with Uncertain Possibility Distributions

Yazarlar:

Furkan Göktaş

Yayıncı:

Burdur Mehmet Akif Ersoy University

Ana Başlıklar:

Operations Research | Investment and Portfolio Management

Dergi:

Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty Vol.11 Issue 2, pp.535-550

Belge Tipi:

Makale

Yayın Tarihi:

6/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001321761

pISSN:

2149-1658

Convex Optimization

Fuzzy Set

Normal Distribution

Portfolio Selection

Possibility Theory

Triangular Fuzzy Number

Sayı

Makale detayları

The Possibilistic Mean-Variance Model with Uncertain Possibility Distributions

Yazarlar: Furkan Göktaş

Yayıncı: Burdur Mehmet Akif Ersoy University

Ana Başlıklar: Operations Research | Investment and Portfolio Management

Dergi: Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty Vol.11 Issue 2, pp.535-550

Belge Tipi: Makale

Yayın Tarihi: 6/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001321761

pISSN: 2149-1658

Convex Optimization

Fuzzy Set

Normal Distribution

Portfolio Selection

Possibility Theory

Triangular Fuzzy Number

Sayı

Yazarlar:

Furkan Göktaş

Yayıncı:

Burdur Mehmet Akif Ersoy University

Ana Başlıklar:

Operations Research | Investment and Portfolio Management

Dergi:

Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty Vol.11 Issue 2, pp.535-550

Belge Tipi:

Makale

Yayın Tarihi:

6/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001321761

pISSN:

2149-1658