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Journals / An International Journal of Optimization and Control: Theories & Applications (IJOCTA) / 2016 / Cilt: 6 - Sayı: 2

Portfolio selection problem: a comparison of fuzzy goal programming and linear physical programming

Ceyhun ARAZ
Fusun KUCUKBAY
Pages
121–128
Publication Date
2022-10-11
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Investors have limited budget and they try to maximize their return with minimum risk.
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Key Findings & Data:In this respect, linear physical programming (LPP) technique is applied on Bist 100 stocks to be able to find out the optimum portfolio.
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Conclusion & Impact:The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.
🔬Design:Research Article
📍Scope:2009 Verileri
⚙️Variables:Domain Parameters

Abstract

Investors have limited budget and they try to maximize their return with minimum risk. Therefore this study aims to deal with the portfolio selection problem. In the study two criteria are considered which are expected return, and risk. In this respect, linear physical programming (LPP) technique is applied on Bist 100 stocks to be able to find out the optimum portfolio. The analysis covers the period from April 2009 to March 2015. This period is divided into two; April 2009-March 2014 and April 2014 - March 2015. April 2009-March 2014 period is used as data to find an optimal solution. April 2014-March 2015 period is used to test the real performance of portfolios. The performance of the obtained portfolio is compared with that obtained from fuzzy goal programming (FGP). Then the performances of both method, LPP and FGP, are compared with BIST 100 in terms of their Sharpe Indexes. The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.

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Cite This Article

ARAZ, C., KUCUKBAY, F. (2022). Portfolio selection problem: a comparison of fuzzy goal programming and linear physical programming. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Cilt: 6 - Sayı: 2, 121–128. https://ajindex.com/articles/440701

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