The Portfolio Optimization Based on Sharp Performance Ratio

Azize Zehra CELENLİ BASARAN; Vedide Rezan USLU

Makale detayları

The Portfolio Optimization Based on Sharp Performance Ratio

Yazarlar:

Azize Zehra CELENLİ BASARAN | Vedide Rezan USLU

Yayıncı:

Giresun University

Ana Başlıklar:

Matematik

Dergi:

Turkish Journal of Forecasting 2019 Vol.03 Issue 1, pp.7-14

Belge Tipi:

Makale

Yayın Tarihi:

8/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000637123

Sıklık:

İki Yıllık

eISSN:

2618-6594

Özet:

 


In recent years investors evaluate their portfolio
using modern portfolio theory developed by Markowitz while in the past they
evaluated portfolio types according to the traditional portfolio theory based
on simple diversification. In modern portfolio theory, it has been defended that
the relationships among financial assets included in the portfolio should be
taken into account. In addition, the return and risk of the portfolio can be
calculated by the mean-variance model. Investors always expect the maximum
return and the minimum risk. Therefore they want to choose the optimum one. In
Economics literature there are some measurements to evaluate the performances
of the different portfolios. In this study, it is aimed at the portfolio analysis
to do for the data of the BIST 30 index. For portfolio optimization, some
Artificial Intelligence techniques such as the Genetic Algorithm and Particular
Swarm Optimization were used for the data belonging to the year 2018. In these algorithms, different values for the
parameters were tried and Sharp Performance Ratio (SPR) was used as a
performance criterion. The portfolio found with the maximum SPR has been
determined as the optimum portfolio. Finally, the risk and the expected return
of the portfolio, the included financial assets and their weights have been
obtained. The values of the parameters of the final result are considered as
the best.


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Makale detayları

The Portfolio Optimization Based on Sharp Performance Ratio

Yazarlar: Azize Zehra CELENLİ BASARAN | Vedide Rezan USLU

Yayıncı: Giresun University

Ana Başlıklar: Matematik

Dergi: Turkish Journal of Forecasting 2019 Vol.03 Issue 1, pp.7-14

Belge Tipi: Makale

Yayın Tarihi: 8/2019

Belge Dili: İngilizce

Document ID (Org No.): 2000637123

Sıklık: İki Yıllık

eISSN: 2618-6594

Sayı

Yazarlar:

Azize Zehra CELENLİ BASARAN | Vedide Rezan USLU

Yayıncı:

Giresun University

Ana Başlıklar:

Matematik

Dergi:

Turkish Journal of Forecasting 2019 Vol.03 Issue 1, pp.7-14

Belge Tipi:

Makale

Yayın Tarihi:

8/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000637123

Sıklık:

İki Yıllık

eISSN:

2618-6594