﻿ 基于遗传–蚁群算法的证券组合投资优化研究

# 基于遗传–蚁群算法的证券组合投资优化研究Research on Protfolio Investment Optimization Based on Genetic-Ant Colony Algorithm

Abstract: Based on the Markowitz portfolio theory, the multi-objective programming model of portfolio investment is established when considering the risk and return of portfolio investment. The genetic algorithm and ant colony algorithm are combined and applied to solve the above model. In detail, the initial solution of problems which is generated by the genetic algorithm with fast global searching ability is transformed into the initial information distribution of the ant colony algorithm. And then we carry on the genetic operation to the ant colony. Finally, we use the ant colony algorithm parallelism, positive feedback mechanism and the solution efficiency high characteristic to seek the optimal solution. Experiments show that: the fusion of the two algorithms has better behaviors on the quality and efficiency than separate genetic algorithm or ant colony algorithm.

[1] Markowitz, H. (1952) Portfolio Selection. The Journal of Finance, 7, 77-91.
https://doi.org/10.1111/j.1540-6261.1952.tb01525.x

[2] 刘侠, 刘红霞, 王科俊. 基于粒子群算法的证券组合投资模型的研究[J]. 投资模型的研究, 2006(16): 49-51.

[3] 陈国良, 王熙法, 庄镇泉, 王东生. 遗传算法及其应用[M]. 北京: 北京人民邮电出版社, 1996: 56-61.

[4] 云庆元. 遗传算法与遗传规则[M]. 北京: 冶金工业出版社, 1997: 3-7.

[5] Dorigo, M. and Stutzle, T. (2004) Ant Colony Optimization. The MIT Press, London, England, 69-75.

[6] 恩格尔伯里特. 计算群体智能基础[M]. 谭营, 译. 北京: 清华大学出版社, 2009: 46-51.

[7] Dorigo, M. and Gambardella, L.M. (1997) Ant Colonies for the Travelling Salesman Problem. Biosystems, 43, 73-81.
https://doi.org/10.1016/S0303-2647(97)01708-5

[8] 肖宏峰, 谭冠政. 遗传算法在蚁群算法中的融合研究[J]. 小型微型计算机系统, 2009, 30(3): 512-517.

[9] 李士勇. 蚁群算法及其应用[M]. 哈尔滨: 哈尔滨工业大学出版社, 2004: 78-82.

[10] 米凯利维茨. 演化程序: 遗传算法和数据编码的结合[M]. 周家驹, 何险峰, 译. 北京: 科学出版社, 2000, 89-92.

[11] 金海丰. 基于遗传算法的企业生产调度研究[D]: [硕士学位论文]. 武汉: 华中科技大学, 2011.

[12] 王喆. 蚁群算法及其在火力分配问题中的应用[J]. 火力与指挥控制, 2009, 34(11): 92-94.

[13] Ding, J.L., Chen, Z.Q. and Yuan, Z.Z. (2003) On the Combination of Genetic Algorithm and Ant Algorithm. Journal of Computer Research and Development, 40, 1351-1356.

[14] 段海滨. 蚁群算法原理及其应用[M]. 北京: 科学出版社, 2010: 112-116.

[15] Markowitz, H. (1952) Portfolio Selection. The Journal of Finance, 7, 77-91.
https://doi.org/10.1111/j.1540-6261.1952.tb01525.x

[16] 刘侠, 刘红霞, 王科俊. 基于粒子群算法的证券组合投资模型的研究[J]. 投资模型的研究, 2006(16): 49-51.

[17] 陈国良, 王熙法, 庄镇泉, 王东生. 遗传算法及其应用[M]. 北京: 北京人民邮电出版社, 1996: 56-61.

[18] 云庆元. 遗传算法与遗传规则[M]. 北京: 冶金工业出版社, 1997: 3-7.

[19] Dorigo, M. and Stutzle, T. (2004) Ant Colony Optimization. The MIT Press, London, England, 69-75.

[20] 恩格尔伯里特. 计算群体智能基础[M]. 谭营, 译. 北京: 清华大学出版社, 2009: 46-51.

[21] Dorigo, M. and Gambardella, L.M. (1997) Ant Colonies for the Travelling Salesman Problem. Biosystems, 43, 73-81.
https://doi.org/10.1016/S0303-2647(97)01708-5

[22] 肖宏峰, 谭冠政. 遗传算法在蚁群算法中的融合研究[J]. 小型微型计算机系统, 2009, 30(3): 512-517.

[23] 李士勇. 蚁群算法及其应用[M]. 哈尔滨: 哈尔滨工业大学出版社, 2004: 78-82.

[24] 米凯利维茨. 演化程序: 遗传算法和数据编码的结合[M]. 周家驹, 何险峰, 译. 北京: 科学出版社, 2000, 89-92.

[25] 金海丰. 基于遗传算法的企业生产调度研究[D]: [硕士学位论文]. 武汉: 华中科技大学, 2011.

[26] 王喆. 蚁群算法及其在火力分配问题中的应用[J]. 火力与指挥控制, 2009, 34(11): 92-94.

[27] Ding, J.L., Chen, Z.Q. and Yuan, Z.Z. (2003) On the Combination of Genetic Algorithm and Ant Algorithm. Journal of Computer Research and Development, 40, 1351-1356.

[28] 段海滨. 蚁群算法原理及其应用[M]. 北京: 科学出版社, 2010: 112-116.

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