本研究提出一個新的投資組合建構方法，它是以決策樹模型建構股票組合，能夠為投資人創造價值。以股票的主要市場交易資料，做為決策變數，並以股票的績效指標作為目標變數，建立決策樹模型。然後以其決策規則建立股票投資組合。使用S&P 500 股價指數成份股票的研究結果，依據股票市場交易資料的決策規則所建立之投資組合，具有較高的組合績效之預測正確率及股票分類。

The study proposes a new stock portfolio constructed by the decision tree model, for creating values for investors. Using stocks’ market trading data to be the decision variables and using the Sharpe ratios to be objective variable, we develop a decision tree model for stock performances. Specifically, the stock portfolio is constructed by its decision rules in the decision tree model. Analyzing S&P 500 index’s stocks, the study shows that the decision-tree portfolio performs better in the accuracy rate and classifications of stocks, in the performance evaluations.

摘要 i
Abstract ii
目錄 iii
圖目錄 iv
表目錄 iv
第壹章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究結果概述 4
第四節 研究貢獻 5
第五節 章節架構 6
第貳章 文獻探討 7
第一節 資料探勘應用在財務分析 7
第二節 以決策樹演算法進行之財務研究 9
第三節 投資組合與績效 10
第參章 研究設計 13
第一節 資料來源與變數定義 13
第二節 決策樹演算法 14
第三節 研究程序 15
第肆章 實證結果 19
第一節 決策樹模型 19
第二節 投資組合 20
第三節 投資組合表現 22
第四節 投資組合績效比較 23
第伍章 結論與建議 27
第一節 結論 27
第二節 未來研究建議 28
參考文獻 31

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