Applying Investment Satisfied Capability Index and Particle Swarm Optimization to Construct the Stocks Portfolio

Weekly data of stocks from Jan. 2006 to Dec. 2007 was adopted in this experiment. The experiment is divided into two stages. The first stage is to adduce process capability indices (PCI) of quality management to develop a new performance appreciation method. Furthermore, investors can utilize
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PL to realize individual stock performance rapidly and select the stocks that can achieve their investment satisfaction degree. In second stage, the Particle Swarm Optimization algorithm (PSO) was applied to these stocks for finding the optimal investment allocation of this portfolio by using the moving interval windows. The result shows that the Ratio of Return of our research is better than The Weighted Price Index of the Taiwan Stock Exchange (TAIEX).