基于遗传算法的非负约束组合证券投资决策

讨论了非负约束条件下实现预期投资收益率的组合证券投资的遗传算法。在以往的投资组合中,一些假设往往与复杂多变的金融市场并不是相吻合的,所以对于一些特殊的情况,需要将模型的一些约束条件进行改进。在中国证券市场上,是不允许卖空出现的,因此,需要非负的约束。遗传算法作为一种高效、并行的全局优化搜索方法,已应用到很多领域。通过将遗传算法引入到证券投资分析领域,对最佳证券组合问题进行了优化计算,同时介绍了利用遗传算法计算最佳证券组合问题的求解步骤。

Portfolio Investment with Nonnegative Constraints on Genetic Algorithms

The genetic algorithms is used to solve the problem of the portfolio investment with expected rate of return under the condition of nonnegative constraints,and it is also applied to a six kind of stock investment problem.In the portfolio,there are some assumptions which are not in accordance with the reality.So the model should be modified.The hereditary way is the best way to find the key to the problem and it has been applied to many domains.By bringing the hereditary way to the domain of the portfolio,the model is proved to be reasonable,and the algorithm is efficient.