Using investment satisfaction capability index based particle swarm optimization to construct a stock portfolio

  • Authors:

  • Jui-Fang Chang;Peng Shi

  • Affiliations:

  • Department of International Business, National Kaohsiung University of Applied Sciences, Taiwan;Department of Computing and Mathematical Sciences, University of Glamorgan, UK and Division of Information Technology, Engineering and the Environment, University of South Australia, Australia

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2011

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Abstract

The goal of this study is to construct an enhanced process based on the investment satisfied capability index (ISCI). The process is divided into two stages. The first stage is to apply the Process Capability Indices (PCI) for quality management so as to develop a new performance appreciation method. Investors can utilize the ISCI index to rapidly evaluate individual stock performance and then select those stocks which can lead to achieve investment satisfaction. In the second stage, a particle swarm optimization (PSO) algorithm with moving interval windows is applied to find the optimal investment allocation of the stocks in this portfolio. Based on those algorithms we can ensure investment risk control and obtain a more profitable stock investment portfolio.