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Multi-Period Model of Portfolio Investment and Adjustment Based on Hybrid Genetic Algorithm

Multi-Period Model of Portfolio Investment and Adjustment Based on Hybrid Genetic Algorithm
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摘要 This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on portfolio investment based on the practical conditions of securities market. In addition, investors should adjust the portfolio according to market changes, changing or not changing the category of risky securities. Markowitz meanvariance approach is applied to the multi-period portfolio selection problems. Because the sub-models are optimal mixed integer program, whose objective function is not unimodal and feasible set is with a particular structure, traditional optimization method usually fails to find a globally optimal solution. So this paper employs the hybrid genetic algorithm to solve the problem. Investment policies that accord with finance market and are easy to operate for investors are put forward with an illustration of application. This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on portfolio investment based on the practical conditions of securities market. In addition, investors should adjust the portfolio according to market changes, changing or not changing the category of risky securities. Markowitz meanvariance approach is applied to the multi-period portfolio selection problems. Because the sub-models are optimal mixed integer program, whose objective function is not unimodal and feasible set is with a particular structure, traditional optimization method usually fails to find a globally optimal solution. So this paper employs the hybrid genetic algorithm to solve the problem. Investment policies that accord with finance market and are easy to operate for investors are put forward with an illustration of application.
机构地区 School of Sciences
出处 《Transactions of Tianjin University》 EI CAS 2009年第6期415-422,共8页 天津大学学报(英文版)
基金 Supported by Natural Science Foundation of Tianjin (No 09JCYBJC01800, No07JCYBJC05200) Application Mathematic Center of Liu Hui, Nankai University and Tianjin University (No2001T08)
关键词 混合遗传算法 调整模型 组合投资 证券市场 混合整数规划 投资组合 全局最优解 投资者 portfolio transaction cost class constraint hybrid genetic algorithm
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