A Group Decision Support System Using Hybrid Kansei -som Model for Stock Market Investment Strategies and Its Application

In this paper, we propose a Hybrid Kansei-SOM model, using Kansei Evaluation integrated with Self-Organizing Map (SOM) for stock market investment strategies. The proposed approach, using a group Decision Support System (DSS), aims to aggregate experts’ preferences with the selection of the most suitable stocks, matching with investing strategies to achieve investment returns by dealing with complex situations in stock market dynamics. The new contribution in this study using Kansei evaluation is to quantify experts’ sensibilities and preferences in stock trading with uncertain values in various stock market conditions, matching with appropriate stock market investment strategies for investment. To evaluate companies for investment, the fuzzy evaluation model of stock market investments is applied by using fuzzy rules on stock market dynamics to represent stock market factors in fuzzy weights and Kansei weights for Kansei stock matrix construction. The matrix is visualized by SOM, together with aggregating experts’ preferences in order to select potential companies that match appropriate stock market investment strategies. The proposed approach has been tested and performed well in daily stock trading on the HOSE, HNX (Vietnam), NYSE and NASDAQ (US) stock markets to validate the method in various stock markets. In order to evaluate the effectiveness of this approach, experimental results show that the proposed approach performs better than other current DSS methods to deal with various stock market conditions.