Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MINLP) problem. To solve constrained problem, propose the use of modified spiral algorithm (SOA). Then, Bartholomew-Biggs Kane’s data to validate our ...

Dr. V. J.Sebastian (Corresponding author) Institute of Management Technology Gaziabad, Delhi, India E-mail: [email protected] Abstract Portfolio optimization, in case of finance, is the tradeoff between risk and return to maximize profit or return from the portfolio. Financial regulations are country specific and it depends upon the economic conditions prevailing in the country. The portfolio of...

The problem of portfolio optimization which deals with the twin objectives of minimizing risk and maximizing expected portfolio return can turn complex when constraints that model investor preferences and market norms such as bounding, cardinality and class constraints, and short sales are included in it. A complex-constrained portfolio optimization such as this has been beyond the reach of sol...

despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. in this paper, moeas have been used for solving multi-objective portfolio optimization problem in tehran stock market. f...

We consider power portfolio optimization of real and contractual assets, including derivative instruments in a multi-period setting. A model is introduced that incorporates fixed transmission rights in a three-node unidirectional network in order to evaluate the significance of transmission constraints. We use data from the PJM, which is located in the eastern United States for model implementa...

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem...

Classical statistical models can solve the problem of portfolio optimization and can determine the efficient frontier of investment when there are few investable assets and constraints. But these models cannot easily solve optimization problems when we consider real-world constraints. Therefore, data mining techniques such as evolutionary algorithms are important in portfolio optimization. The ...

This paper focuses on the application of an original global optimization algorithm, based on the hybridization between a genetic algorithm and a semi-deterministic algorithm, for the resolution of various constrained optimization problems for realistic credit portfolios. Results are analyzed from a financial point of view in order to confirm their relevance. KEYWORDCredit Portfolio Management, ...

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