科研之友
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摘要
The key to successful stock market investment is achieving the best investment returns in real-world stock trading. Currently, many studies have investigated Decision Support System (DSS) techniques, soft computing models and hybrid systems for stock market investments, mostly based on historical data. However, most approaches show incomplete solutions for investors to achieve higher investment returns since many uncertain conditions are not considered concurrently in those studies, such as stock prices, technical indicators, macroeconomics, event news and investor sensibilities for buying/selling stocks. In this paper, we propose a Hybrid Kansei-SOM model, which is a new approach using Kansei evaluation integrated with DSS techniques using group decision making for stock market investment. The proposed approach aims to assist experts with a selection of the most suitable stocks at the right time for trading to achieve the greatest investment returns, dealing with complex situations on stock market dynamics. The proposed approach has also performed well in daily stock trading on the HOSE (Vietnam), NYSE and NASDAQ (US) stock markets. The experiments through case studies show the new approach, applying to Kansei evaluation based on expert's sensibilities about uncertain values together with quantitative and qualitative factors on stock market dynamics to enhance the capability of investment returns. In order to evaluate the effectiveness of this approach, the experimental results show that the proposed approach performs better than other current methods to deal with various stock market conditions.
- 出版日期2011-5
