A study on stock selection strategy by using Cart, vikor and manifold learning method

• Main Authors: Guo-Wei Li, 李國偉
• Other Authors: 林鳳儀
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/wqnrva

碩士 === 國立臺北科技大學 === 商業自動化與管理研究所 === 97 === The stock market has gradually become one of the major investment markets in Taiwan. The stock market is very complex, and changes too fast that too invest. There are many studies using data mining technology in the stock market. Using neural network and support vector machine could provide a precise classification, but the results generated by black-box interpretation is not easy to understand. Therefore, this study provides prediction rules by choose the decision tree, from several financial and non-financial ratios to understand the process of model construction. Since 2004, The burst of financial scandal of PEWC and ProComp, and the second half of 2007, the outbreak of the subprime mortgage crisis in the U.S.A. This study is to investigate whether corporate governance variables and system risk has affected in the stock return. To the improve forecasting power, we take the methodology manifold learning and VIKOR together and combine with decision tree respectively to construct prediction models. The results found that corporate governance has gradually become an important factor in stock return, and VIKOR can serves better forecasting model.