...
首页> 外文期刊>Matematika >Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization
【24h】

Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization

机译:混合粒子群算法的两阶段投资组合选择与优化模型

获取原文
           

摘要

The selection criteria play an important role in the portfolio optimization using any ratio model. In this paper, the authors have considered the mean return as profit and variance of return as risk on the asset return as selection criteria, as the first stage to optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been considered to be the optimization ratio model. In this regard, the historical data taken from Shanghai Stock Exchange (SSE) has been considered. A metaheuristic technique has been developed, with financial tool box available in MATLAB and the particle swarm optimization ( PSO ) algorithm. Hence, called as the hybrid particle swarm optimization ( HPSO ) or can also be called as financial tool box particle swarm optimization ( FTB - PSO ). In this model, the budgets as constraint, where as two different models i.e. with and without short sale, have been considered. The obtained results have been compared with the existing literature and the proposed technique is found to be optimum and better in terms of profit.
机译:选择标准在使用任何比率模型的投资组合优化中起着重要作用。在本文中,作者将平均收益率作为利润,收益率方差作为资产收益率的风险作为选择标准,这是优化所选投资组合的第一步。此外,锐利比率(SR)被认为是优化比率模型。在这方面,已经考虑了从上海证券交易所(SSE)获得的历史数据。已经开发了一种元启发式技术,在MATLAB中提供了财务工具箱,并采用了粒子群优化(PSO)算法。因此,称为混合粒子群优化(HPSO)或也可以称为金融工具箱粒子群优化(FTB-PSO)。在该模型中,考虑了预算约束,作为两个不同的模型,即有和没有卖空。将获得的结果与现有文献进行了比较,发现所提出的技术是最佳的,并且在利润方面更好。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号