论文标题
元神经化方法解决投资组合选择问题
Metaheuristic Approach to Solve Portfolio Selection Problem
论文作者
论文摘要
在本文中，正在使用基于Tabusearch和令牌搜索的启发式方法来解决投资组合优化问题。通过增加基数和数量约束，正在考虑Markowitz的开创性均值变化模型，以更好地捕获交易过程的动力学，该模型成为NP硬性问题，无法使用精确方法解决。通过禁忌搜索，正在探索三个不同邻里关系的组合。另外，提出了一种新的建设性方法。最后，我展示了提议的技术在公共基准测试中的表现
In this paper, a heuristic method based on TabuSearch and TokenRing Search is being used in order to solve the Portfolio Optimization Problem. The seminal mean-variance model of Markowitz is being considered with the addition of cardinality and quantity constraints to better capture the dynamics of the trading procedure, the model becomes an NP-hard problem that can not be solved using an exact method. The combination of three different neighborhood relations is being explored with Tabu Search. In addition, a new constructive method for the initial solution is proposed. Finally, I show how the proposed techniques perform on public benchmarks
