An approach to improve mean-variance portfolio optimization model

2015 ◽  
Vol 16 (3) ◽  
pp. 209-219 ◽  
Author(s):  
Rafael Yanushevsky ◽  
Daniel Yanushevsky's
Keyword(s):  
Portfolio Optimization ◽  
Optimization Model ◽  
Portfolio Optimization Model ◽  
Mean Variance Portfolio ◽  
Mean Variance

An extension to the classical mean–variance portfolio optimization model

2019 ◽  
Vol 64 (3) ◽  
pp. 310-321
Author(s):  
Çelen N. Ötken ◽  
Z. Batuhan Organ ◽  
E. Ceren Yıldırım ◽  
Mustafa Çamlıca ◽  
Volkan S. Cantürk ◽  
...  
Keyword(s):  
Portfolio Optimization ◽  
Optimization Model ◽  
Portfolio Optimization Model ◽  
Mean Variance Portfolio ◽  
Mean Variance

Extended Mean - Variance Portfolio Optimization Model: A Comparative Study Among Swarm Intelligence Algorithms

2019 ◽  
Vol 9 (2) ◽  
pp. 184
Author(s):  
R. K. Jena
Keyword(s):  
Portfolio Optimization ◽  
Swarm Intelligence ◽  
Portfolio Risk ◽  
Expected Return ◽  
Monthly Data ◽  
Bee Colony ◽  
Portfolio Optimization Model ◽  
Mean Variance Portfolio ◽  
Portfolio Selection Model ◽  
Mean Variance

Portfolio optimization is one of the important issues in the effective management of investment. There is plenty of research in the literature addressing these issues. Markowitz’s primary portfolio selection model is a more suitable method to solve the model for obtaining fairly optimum portfolios. But, the problem of portfolio optimization is multi-objective in nature that aims at simultaneously maximizing the expected return of the portfolio and minimizing portfolio risk. The computational complexity increases with an increase in the total number of available assets. Therefore heuristic methods are more suitable for portfolio optimization in compare to deterministic methods. This research compares three well-known swarm intelligence algorithms (e.g. Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC)) for portfolio optimization. The Sharpe ratio was used as one of the important criteria for this comparison. PSO outperformed other algorithms in portfolio optimization experiments. The results were also showed that the portfolios which were made of monthly data had performed better than the yearly data.

A portfolio optimization model for corporate bonds subject to credit risk

2004 ◽  
Vol 6 (2) ◽  
pp. 31-48 ◽  
Author(s):  
Nagisa Akutsu ◽  
Masaaki Kijima ◽  
Katsuya Komoribayashi
Keyword(s):  
Credit Risk ◽  
Portfolio Optimization ◽  
Optimization Model ◽  
Corporate Bonds ◽  
Portfolio Optimization Model
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