本論文研究投資人情緒指標對於利用基本分析與技術分析之投資策略所建構之投資組合績效的影響，進一步探討除了傳統常被投資人採用的基本面與技術面投資策略外，是否存在由投資人所引發的情緒動能，並用於解釋投資組合績效。另外，本研究亦檢視依基本分析與技術分析所建構之投資組合是否能顯著提高投組報酬且優於整體市場報酬。本文分別以Piotroski (2000) 所提出的FSCORE及Mohanram (2005) 的GSCORE結合利用過去報酬率與成交量的技術面動能投資策略建立本文之投資組合，並使用三種代表不同投資族群的情緒指標，以主成份分析法依各情緒指標之第一主成份建構一複合情緒指標，探討投資人情緒是否對當期或未來股票報酬具解釋能力。實證結果顯示，以價值股投資策略結合技術面動能投資策略之投組報酬高於以成長股投資策略為主的投組報酬並顯著優於大盤。此外，本研究證實投資人情緒對依照基本面與技術面所建構之頭組當期報酬呈現正向相關，並對價值股投資策略之投組報酬具有預測能力，顯示投資人情緒這類屬於行為財務領域的非傳統指標在股票報酬解釋上佔有一定的重要性。

This study examines the impact of sentiment measures on portfolio returns constructed on the basis of fundamental analysis and technical analysis to investigate how emotion momentum on account of behavioral finance explains in stock performance. Whether the combined investment strategy with both fundamental and technical in-formation can beat the market was verified as well. We start with investment portfolio formation by adopting two fundamental scoring systems - the FSCORE (Piotroski 2000) and the GSCORE (Mohanram 2005) incorporating technical momentum strategy consist of past return and past trading volume. Then we consider a number of proxies to construct a comprise sentiment indicator by principal component analysis to explore the explaining ability of investor sentiment in portfolio returns. The empirical evidence shows that the value stock investing strategy combined with momentum strategy outperform the growth stock investment strategy. Additionally, investor sentiment has positive influence and predictive power on current and future returns, which indicating that investor sentiment indeed plays a role in sentiment-return relation and investing strategies combining sentiment measures can provide incremental value to the portfolio formed by using both fundamental and technical analysis as in-vestment strategies in Taiwan stock market.

中文摘要 i
Abstract ii
Contents iii
Table Contents iv
Chapter1 Introduction 1
1.1 Background and Motivation 1
1.2 Objectives 4
Chapter2 Literature Review 6
2.1 Fundamental Analysis 6
2.2 Technical Analysis 10
2.3 Fundamental and Technical Analysis 13
2.4 Investor Sentiment 15
2.5 Hypothesis 19
Chapter3 Methodology and Data 21
3.1 Methodology 21
3.2 Fundamental Analysis 21
3.3 Technical Analysis-BOS Ratio 27
3.4 Investor Sentiment Measures 28
3.5 Principal Component Analysis 31
3.6 Data and Sample Selection 31
3.7 Performance Analysis 34
3.8 Paired Sample T-Test 34
3.9 Model Construction 35
Chapter4 Empirical Results 37
4.1 Return Analysis on Alternative Portfolio 37
4.2 Regression Analysis 44
4.3 Hypotheses Tests Summary 50
Chapter5 Conclusions 51
5.1 Main Findings 51
5.2 Theoretical and Practical Contributions 52
5.3 Limitations and Recommendations 53
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