This paper studied cardinality constrained portfolio with integer weight.We suggested two optimization models and used two genetic algorithms to solve them.In this paper,after finding well matching stocks,according to...This paper studied cardinality constrained portfolio with integer weight.We suggested two optimization models and used two genetic algorithms to solve them.In this paper,after finding well matching stocks,according to investor’s target by using first genetic algorithm,we gave optimal integer weight of portfolio with well matching stocks by using second genetic algorithm.Through numerical comparisons with other feasible portfolios,we verified advantages of designed portfolio with two genetic algorithms.For a numerical comparison,we used a prepared data consisted of 18 stocks listed in S&P 500 and numerical example strongly supported the designed portfolio in this paper.Also,we made all comparisons visible through all feasible efficient frontiers.展开更多
文摘This paper studied cardinality constrained portfolio with integer weight.We suggested two optimization models and used two genetic algorithms to solve them.In this paper,after finding well matching stocks,according to investor’s target by using first genetic algorithm,we gave optimal integer weight of portfolio with well matching stocks by using second genetic algorithm.Through numerical comparisons with other feasible portfolios,we verified advantages of designed portfolio with two genetic algorithms.For a numerical comparison,we used a prepared data consisted of 18 stocks listed in S&P 500 and numerical example strongly supported the designed portfolio in this paper.Also,we made all comparisons visible through all feasible efficient frontiers.
