投资组合选择的多阶段多群粒子群优化

Thales F. Dal Molim, Francisco Carlos M. Souza
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引用次数: 0

摘要

本研究提出了一种新的基于元启发式的方法,在文献中被称为MS2PSO,以解决巴西股票市场的投资组合选择问题。研究分为两个实验,分别评估了算法得到的解决方案的质量,以及在不同时间窗和风险概况下推荐投资组合的有效性。结果表明,与PSO相比,MS2PSO收敛速度较慢,但提供的结果更令人满意。此外,所提方法推荐的投资组合根据风险状况表现出正、负两种表现,且在该期间获得的整体最高收益均优于基准。本研究为投资组合选择提供了一个成熟而有效的解决方案,有助于金融经济领域的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multistage, Multiswarm Particle Swarm Optimization for Investment Portfolio Selection
This study proposes a new metaheuristic-based approach, identified in the literature as MS2PSO, to solve the problem of investment portfolio selection in the Brazilian stock market. The study was divided into two experiments that evaluated the quality of the solutions obtained by the algorithm and the effectiveness of the recommended portfolios in different time windows and risk profiles. The results indicated that MS2PSO presented slower convergence but offered more satisfactory results compared to PSO. In addition, the portfolios recommended by the proposed method showed positive and negative performances according to the risk profile, and all of them outperformed the benchmark in terms of the overall highest gain obtained during the period. This study contributes to the development of the area of finance and economics by providing a sophisticated and efficient solution for investment portfolio selection.
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