جستجوی مقالات مرتبط با کلیدواژه « cardinality constraint » در نشریات گروه « مالی »

The optimization of the stock portfolio and the allocation of wealth between the various assets are among the most important issues in investing.In this study, the problem of optimizing stock portfolios, considering the real world constraints and with the assumption that the return on risky assets of fuzzy numbers is composed. Then, a new probabilistic model of mean-semi absolute deviation was presented in which transaction cost and cardinality constraints were also considered. The existence of such constraints transforms the model into a mixed-integer non-linear programming model that traditional approaches fail to solve, for this purpose a new meta-heuristic algorithm called the Unconscious Search Algorithm is used to solve the problem. Unconscious Search algorithm is a new algorithm based on Freud's psychoanalysis theory. In order to investigate the power and accuracy of solving this algorithm, a case study was carried out with the information of 50 top Tehran Stock Exchanges for years 2012 to 2016. The results were compared with Particle Swarm Optimization and Genetic algorithms, which showed the superiority of this algorithm in the optimization problem of Stock portfolio.

The portfolio optimization has become one of the most important issues for the companies operating in the capital market. When the real-world conditions and restrictions, including cardinality constraint are considered in portfolio optimization, the problem is not easily solvable. Therefore using the meta-heuristic methods will be considered. Regarding this fact, the main purpose of this paper is to solve portfolio optimization problem by using an entirely new and emerging meta-heuristic algorithm that called symbiotic organisms search, while considering the limitations of the real world in the formation of portfolio. This algorithm is inspired by the symbiotic relationship in diverse ecosystems that exist in nature, and introduced in 2014. Finally, the model used in this study has been solved with real data and the results have been analyzed. The results of this paper demonstrate that the symbiotic organism search has been successful in portfolio optimization and has been able to properly interact with the actual limitations of the market.