- 學位論文
以資料探勘法比較葛拉漢在封測產業之投資實證
The comparison study of using Data Mining and Graham investment for the stocks of company on IC-testing and package
摘要
葛拉漢(Benjamin Graham)是華爾街公認的證券分析之父，在投資上皆有傑出的表現，且對股票分析有制定相當明確的規則。資料探勘是一個電腦科學處理資料的分析方法， 它是用人工智慧、機器學習、統計學和資料庫的交叉方法在相對較大型的資料集中發現模式的計算過程。 在本研究中，以粗集合理論是一種處理不精確、不確定和不完全數據的新的數學方法。它可以通過對數據的分析和推理來發現隱含的知識、揭示潛在的規律。因此本研究以資料探勘中的粗集合理論分析台灣股票封測產業在2015年至2016年的財務屬性建立投資組合，並建立if-then規則，同時比較投資大師葛拉漢所制定選股規則下，兩者投資正確率和報酬率之差異比較。
並列摘要
Benjamin Graham is the father of Wall Street who was recognized as outstanding performance in investment. He has fairly clear rules for stock analysis. Data mining is considered as a computer science processing data analysis method. It is a computational process to discover patterns in a relatively large data set using the artificial intelligence, machine learning, statistics, and database. In this study, a rough set is a new mathematical method for dealing with collecting data. It can discover hidden knowledge and reveal potential rules through analysis and presented given data. Therefore, this study uses the rough set theory in data exploration to analyze the financial properties of Taiwan's stock packaging and testing industry from 2015 to 2016. It is decide to establish the if-then rule, and compare the difference between the correct rate of investment and the rate of return between the two investors under the rules of stock selection by the investment Benjamin Graham.