An extension to the classical mean–variance portfolio optimization model

Name: An extension to the classical mean–variance portfolio optimization model
Author: Ötken, Çelen Naz, Organ, Zeynel Batuhan, Yıldırım, Elif Ceren, Çamlıca, Mustafa, Cantürk, Volkan Selim, Duman, Ekrem, Teksan, Zehra Melis, Kayış, Enis

İsim	An extension to the classical mean–variance portfolio optimization model
Yazar	Ötken, Çelen Naz, Organ, Zeynel Batuhan, Yıldırım, Elif Ceren, Çamlıca, Mustafa, Cantürk, Volkan Selim, Duman, Ekrem, Teksan, Zehra Melis, Kayış, Enis
Basım Tarihi:	2019-07
Basım Yeri	- Taylor & Francis
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0013-791X
Kayıt Numarası	9837223d-d7d3-4cc6-9dd5-685c561fdb58
Lokasyon	Industrial Engineering
Tarih	2019-07
Örnek Metin	The purpose of this study is to find a portfolio that maximizes the risk-adjusted returns subject to constraints frequently faced during portfolio management by extending the classical Markowitz mean-variance portfolio optimization model. We propose a new two-step heuristic approach, GRASP & SOLVER, that evaluates the desirability of an asset by combining several properties about it into a single parameter. Using a real-life data set, we conduct a simulation study to compare our solution to a benchmark (S&P 500 index). We find that our method generates solutions satisfying nearly all of the constraints within reasonable computational time (under an hour), at the expense of a 13% reduction in the annual return of the portfolio, highlighting the effect of introducing these practice-based constraints.
DOI	10.1080/0013791X.2019.1636440
Cilt	64

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An extension to the classical mean–variance portfolio optimization model

Yazar Ötken, Çelen Naz, Organ, Zeynel Batuhan, Yıldırım, Elif Ceren, Çamlıca, Mustafa, Cantürk, Volkan Selim, Duman, Ekrem, Teksan, Zehra Melis, Kayış, Enis

Basım Tarihi 2019-07

Basım Yeri - Taylor & Francis

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0013-791X

Kayıt Numarası 9837223d-d7d3-4cc6-9dd5-685c561fdb58

Lokasyon Industrial Engineering

Tarih 2019-07

Örnek Metin The purpose of this study is to find a portfolio that maximizes the risk-adjusted returns subject to constraints frequently faced during portfolio management by extending the classical Markowitz mean-variance portfolio optimization model. We propose a new two-step heuristic approach, GRASP & SOLVER, that evaluates the desirability of an asset by combining several properties about it into a single parameter. Using a real-life data set, we conduct a simulation study to compare our solution to a benchmark (S&P 500 index). We find that our method generates solutions satisfying nearly all of the constraints within reasonable computational time (under an hour), at the expense of a 13% reduction in the annual return of the portfolio, highlighting the effect of introducing these practice-based constraints.

DOI 10.1080/0013791X.2019.1636440

Cilt 64