Retail Investor Sentiment and Behavior (eBook)

Matthias Burghardt received a doctorate degree in business administration from the Karlsruhe Institute of Technology where he worked as a research fellow under the supervision of Prof. Dr. Christof Weinhardt at the Institute of Information Systems and Management. He currently works at a leading European exchange organization for retail investors.

Acknowledgements 6
Table of Contents 7
Abbreviations 10
List of Figures 12
List of Tables 13
1 Introduction 14
1.1. Motivation 14
1.2. Research Outline 15
1.3. Overview and Structure 20
1.4. Related Publications 21
2 Related Theoretical and Empirical Work 22
2.1. Introduction to Behavioral Finance 22
2.1.1. Are Financial Markets Efficient? 22
2.1.2. Challenges to Efficient Markets 24
2.1.3. Emergence of Behavioral Finance 26
2.2. Theoretical Work 29
2.3. Empirical Work 33
2.3.1. Noise Traders 33
2.3.2. Investor Sentiment 34
2.3.3. Individual Investors 34
2.3.4. Correlated Trading 35
2.4. Discussion 36
2.4.1. Behavioral Finance 36
2.4.2. Correlated Trading 37
2.4.3. Return Correlation 41
2.4.4. Market Efficiency 44
2.5. Conclusion 45
3 Investor Sentiment Construction 47
3.1. Classification of Sentiment Measures 47
3.1.1. Related Work 47
3.1.2. Advantages and Disadvantages 49
3.2. Sentiment Measures in Research 50
3.2.1. The Closed-End Funds Discount 50
3.2.2. Meta-Measures 53
3.3. Sentiment Measures in Practice 56
3.3.1. Survey-Based Measures 56
3.3.2. Market-Data-Based Measures 63
3.3.3. Meta-Measures 66
3.3.4. Summary Statistics 67
3.4. Evaluation of Sentiment Measures 69
3.4.1. Direct Sentiment Measures 69
3.4.2. Indirect Sentiment Measures 71
3.4.3. Direct vs. Indirect Sentiment Measures 73
3.4.4. Sentiment Measures vs. Market Returns 76
3.4.5. Review of Results 79
3.5. Conclusion 79
4 Construction of the Euwax Sentiment Index 81
4.1. Introduction 81
4.1.1. Securitized Derivatives 81
4.1.2. European Warrant Exchange 85
4.1.3. Key Facts 85
4.2. Data Set 86
4.3. Basic Index Calculation 88
4.4. Sentiment Analysis 92
4.4.1. Numbervs. Volume-Based Measures 92
4.4.2. Product Types 95
4.4.3. Order Types 95
4.4.4. Order Volume Groups 95
4.4.5. Submitted Orders 96
4.4.6. Leverage 97
4.5. Comparison with Other Sentiment Measures 98
4.5.1. Indirect Sentiment Measures 99
4.5.2. Direct Sentiment Measures 101
4.5.3. Review of Results 103
4.6. Conclusion 104
5 Retail Investor Herding 105
5.1. Introduction 105
5.2. Related Work 106
5.2.1. Definitions of Herding 106
5.2.2. Empirical Findings 107
5.2.3. Discussion 110
5.3. Evidence of Market-Wide Herding 112
5.3.1. Data 112
5.3.2. Herding Measure Construction 112
5.3.3. Results 113
5.3.4. Review of Results 117
5.4. Market-Wide Herding on a Broker Level 117
5.4.1. Data 117
5.4.2. Results 119
5.4.3. Review of Results 121
5.5. Stock-Level Herding 122
5.5.1. Data 122
5.5.2. Herding Measure 124
5.5.3. Results 126
5.5.4. Review of Results 128
5.6. Conclusion 129
6 The Predictive Power of Retail Investor Sentiment 131
6.1. Related Work 131
6.2. Data and Methodology 134
6.2.1. Data Set 135
6.2.2. Methodology 136
6.3. Results 137
6.3.1. Preand Post-Portfolio-Formation Returns 137
6.3.2. Control Variables 142
6.3.3. Portfolio Holding Returns 146
6.4. Robustness Checks 151
6.5. Conclusion 154
7 Conclusion and Future Work 155
7.1. Conclusion 155
7.2. Summary of Contributions 159
7.3. Future Work 160
Appendix 163
A Appendix to Chapter 4 163
Bibliography 165