Knowledge Discovery with Self-Organizing Map in Investment Strategy

• Main Authors: Shih-Yu Tseng, 曾士育
• Other Authors: Sheng-Tun Li
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/81886226686155662648

碩士 === 國立高雄第一科技大學 === 資訊管理所 === 91 === Financial investment is a knowledge-intensive industry. In the past years, with the electronic transaction technology advances, vast amount of transaction data have been collected and the emergence of knowledge discovery technology sheds light toward building up a financial investment decision support system. Data of financial markets are essentially time-series which bring more challenges than the traditional discrete data for uncovering the hidden knowledge. In this research, Taifex Index in Taiwan Futures Exchange K-chart patterns as the target dataset, we tackle with these challenges by proposing an integrated solution on the basis of knowledge-discovery methodology which supports four important tasks of data mining: clustering, classification, forecasting and visualization. In order to provide a decision maker the functionality of visualization, this project utilizes self-organization map that can transform high- dimensional, complicated, and nonlinear data onto low-dimensional ones with topology preservation. For clustering, the silhouette coefficient algorithm are applied to validate the clusters. Following, the trading signals are classified by performing pattern-match with K-Chart patterns in the trained SOM and the sliding-window data. Finally, the closing price in the next day is predicted based on the first 24 days pattern. In contrast to related work, we not only endeavor to improve the accuracy of classification of trading signals, we also are in an attempt to maximize the profits of trading. The resulting intelligence investment decision support system can help fund managers and investment decision-makers of national stable funds make the profitable decision. In addition, financial experts can benefit from the ability of verifying or refining their tacit investment knowledge offered by the uncovered knowledge.