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Retail investor sentiment and behavior [Elektronische Ressource] : an empirical analysis / von Matthias Burghardt

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172 pages
Retail Investor Sentiment and Behavior – an Empirical Analysis Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswissenschaften (Dr. rer. pol.) von der Fakultät für Wirtschaftswissenschaften des Karlsruher Instituts für Technologie genehmigte DISSERTATION von Dipl.-Inform.Wirt Matthias Burghardt Tag der mündlichen Prüfung: 12. Mai 2010 Referent: Prof. Dr. Christof Weinhardt Korreferentin: Prof. Dr. Marliese Uhrig-Homburg 2010 Karlsruhe Acknowledgements I am indebted to many people for their support throughout the preparation of this thesis. In particular, I am grateful to my advisor Prof. Dr. Christof Weinhardt who gave me his support and advice while granting me the freedom to explore different ways to combine academic rigor and practical relevance in interdisciplinary research. In addition, I would like to thank Prof. Dr. Marliese Uhrig-Homburg for co-advising this thesis. My thanks also go to Prof. Dr. Ute Werner and Prof. Dr. Ingrid Ott for serving on the board of examiners. I would like to thank my colleagues from the research group Information and Market Engineering at the Institute of Information Systems and Management (IISM) for many fruitful discussions and their valuable comments. I am grateful to Dr. Henner Gimpel who was always ready to discuss problems with me and to share his ideas how to solve them. I also thank Dr. Stefan Seifert for his advice on the direction of this work.
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Retail Investor Sentiment and Behavior
– an Empirical Analysis
Zur Erlangung des akademischen Grades eines
Doktors der Wirtschaftswissenschaften

(Dr. rer. pol.)

von der Fakultät für
Wirtschaftswissenschaften
des Karlsruher Instituts für Technologie
genehmigte

DISSERTATION

von
Dipl.-Inform.Wirt Matthias Burghardt


Tag der mündlichen Prüfung: 12. Mai 2010
Referent: Prof. Dr. Christof Weinhardt
Korreferentin: Prof. Dr. Marliese Uhrig-Homburg

2010 Karlsruhe
Acknowledgements
I am indebted to many people for their support throughout the preparation of this thesis.
In particular, I am grateful to my advisor Prof. Dr. Christof Weinhardt who gave me his
support and advice while granting me the freedom to explore different ways to combine
academic rigor and practical relevance in interdisciplinary research.
In addition, I would like to thank Prof. Dr. Marliese Uhrig-Homburg for co-advising
this thesis. My thanks also go to Prof. Dr. Ute Werner and Prof. Dr. Ingrid Ott for
serving on the board of examiners.
I would like to thank my colleagues from the research group Information and Market
Engineering at the Institute of Information Systems and Management (IISM) for many
fruitful discussions and their valuable comments. I am grateful to Dr. Henner Gimpel
who was always ready to discuss problems with me and to share his ideas how to solve
them. I also thank Dr. Stefan Seifert for his advice on the direction of this work. Many
thanks also go to Dr. Ryan Riordan for being my co-author on many papers and for
providing me with encouragement and support. Ryan Riordan and Martin Wagener
deserve special thanks for proofreading major parts of the thesis and for providing me
with constructive comments.
Parts of this research have been done while I enjoyed the hospitality of London
Business School. I am grateful to Prof. Bruce Weber who made this possible.
Finally, I would like to express my gratitude to Oliver Hans, Dr. Christoph Mura, and
Christoph Lammersdorf for their constant support while I was research fellow at Boerse
Stuttgart. This work would not have been possible without their commitment and
dedication to this project.

Matthias Burghardt

Table of Contents ii
Table of Contents
Abbreviations ................................................................................................ v 
List of Figures ............................................................................................. vii 
List of Tables .............................................................................................. viii 
1  Introduction ............................................................................................ 1 
1.1.  Motivation .......................................................................................................... 1 
1.2.  Research Outline ................................................................................................ 3 
1.3.  Overview and Structure ...................................................................................... 7 
1.4.  Related Publications ........................................................................................... 8 
2  Related Theoretical and Empirical Work ............................................. 10 
2.1.  Introduction to Behavioral Finance .................................................................. 10 
2.1.1.  Are Financial Markets Efficient? .............................................................. 10 
2.1.2.  Challenges to Efficient Markets ............................................................... 12 
2.1.3.  Emergence of Behavioral Finance ............................................................ 14 
2.2.  Theoretical Work ............................................................................................. 17 
2.3.  Empirical Work ................................................................................................ 21 
2.3.1.  Noise Traders ............................................................................................ 21 
2.3.2.  Investor Sentiment .................................................................................... 22 
2.3.3.  Individual Investors .................................................................................. 23 
2.3.4.  Correlated Trading 23 
2.4.  Discussion ........................................................................................................ 25 
2.4.1.  Behavioral Finance ................................................................................... 25 
2.4.2.  Correlated Trading 26 
2.4.3.  Return Correlation 30 
2.4.4.  Market Efficiency ..................................................................................... 33 
2.5.  Conclusion ........................................................................................................ 34 
3  Investor Sentiment Construction .......................................................... 36 
3.1.  Classification of Sentiment Measures .............................................................. 36 
3.1.1.  Related Work ............................................................................................ 36 
3.1.2.  Advantages and Disadvantages ................................................................ 38 
3.2.  Sentiment Measures in Research ..................................................................... 39 
3.2.1.  The Closed-End Funds Discount 39 
3.2.2.  Meta-Measures .......................................................................................... 42 Table of Contents iii
3.3.  Sentiment Measures in Practice ....................................................................... 45 
3.3.1.  Survey-based Measures ............................................................................ 45 
3.3.2.  Market-data-based Measures .................................................................... 52 
3.3.3.  Meta-Measures .......................................................................................... 56 
3.3.4.  Summary Statistics ................................................................................... 57 
3.4.  Evaluation of Sentiment Measures ................................................................... 59 
3.4.1.  Direct Sentim59 
3.4.2.  Indirect Sentim61 
3.4.3.  Direct vs. Indirect Sentiment Measures .................................................... 63 
3.4.4.  Sentiment Measures vs. Market Returns .................................................. 66 
3.4.5.  Review of Results ..................................................................................... 69 
3.5.  Conclusion ........................................................................................................ 69 
4  Construction of the Euwax Sentiment Index ....................................... 71 
4.1.  Introduction ...................................................................................................... 71 
4.1.1.  Securitized Derivatives ............................................................................. 71 
4.1.2.  European Warrant Exchange .................................................................... 75 
4.1.3.  Key Facts .................................................................................................. 75 
4.2.  Data Set ............................................................................................................ 76 
4.3.  Basic Index Calculation ................................................................................... 79 
4.4.  Sentiment Analysis ........................................................................................... 82 
4.4.1.  Number vs. Volume Based Measures ....................................................... 82 
4.4.2.  Product Types 85 
4.4.3.  Order Types .............................................................................................. 86 
4.4.4.  Order Volume Groups .............................................................................. 86 
4.4.5.  Submitted Orders ...................................................................................... 87 
4.4.6.  Leverage .................................................................................................... 88 
4.5.  Comparison with other Sentiment Measures ................................................... 89 
4.5.1.  Indirect Sentiment Measures .................................................................... 90 
4.5.2.  Direct Sentim....................................................................... 92 
4.5.3.  Review of Results ..................................................................................... 95 
4.6.  Conclusion ........................................................................................................ 95 
5  Retail Investor Herding ........................................................................ 97 
5.1.  Introduction ...................................................................................................... 97 
5.2.  Related Work ................................................................................................... 98 
5.2.1.  Definitions of Herding .............................................................................. 98 
5.2.2.  Empirical Findings .................................................................................... 99 
5.2.3.  Discussion ............................................................................................... 102 
5.3.  Evidence of Market-wide Herding ................................................................. 104 
5.3.1.  Data ......................................................................................................... 104 
5.3.2.  Herding Measure Construction ............................................................... 104 
5.3.3.  Results ..................................................................................................... 106 
5.3.4.  Review of Results ................................................................................... 109 Table of Contents iv
5.4.  Market-wide herding on a broker level .......................................................... 109 
5.4.1.  Data ......................................................................................................... 110 
5.4.2.  Results ..................................................................................................... 111 
5.4.3.  Review of Results ................................................................................... 113 
5.5.  Stock-Level Herding ...................................................................................... 114 
5.5.1. 114 
5.5.2.  Herding Measure ..................................................................................... 116 
5.5.3. 118 
5.5.4.  Review of Results 120 
5.6.  Conclusion ...................................................................................................... 121 
6  The Predictive Power of Retail Investor Sentiment ........................... 123 
6.1.  Related Work ................................................................................................. 124 
6.2.  Data and Methodology ................................................................................... 127 
6.2.1.  Data Set ................................................................................................... 127 
6.2.2.  Methodology ........................................................................................... 128 
6.3.  Results ............................................................................................................ 129 
6.3.1.  Pre- and Post Portfolio Formation Returns ............................................. 129 
6.3.2.  Control Variables .................................................................................... 134 
6.3.3.  Portfolio Holding Returns ....................................................................... 140 
6.4.  Robustness Checks ......................................................................................... 143 
6.5.  Conclusion ...................................................................................................... 147 
7  Conclusion and Future Work ............................................................. 148 
7.1. 148 
7.2.  Summary of Contributions ............................................................................. 152 
7.3.  Future Work ................................................................................................... 154 
Appendices ................................................................................................... ix 
A  Appendix to Chapter 4 ...................................................................................... ix 
Bibliography ................................................................................................. xi 

Abbreviations v
Abbreviations
AAII American Association of Individual Investors
ADV/DEC Advances/Declines Ratio
ADV-DEC Advances minus Declines
ASX Australian Stock Exchange
CAUD Consolidated Equity Audit Trail Data
CBOE Chicago Board Options Exchange
CCI Consumer Confidence Index
CEFA Closed-End Funds Association
CEFD Closed-End Discount
col. column
DAX Deutscher Aktienindex
DJIA Dow Jones Industrial Average
e.g. for example
EMH Efficient Markets Hypothesis
et al. et alii
EUWAX European Warrant Exchange
G-Mind German Market Indicator
i.e. that is
ICE Index of Consumer Expectations
ICS er Sentiment
II Investors’ Intelligence
IPO Initial Public Offering
ISE International Securities Exchange
ISSM Institute for the Study of Security Markets
LSV Lakonishok, Shleifer, and Vishny (1992)
MSH Morgan Stanley High-Tech Index
NASDAQ National Association of Securities Dealers Automated
Quotations
NAV net asset value
NYSE New York Stock Exchange
p/c put/call ratio
REX Rentenindex
S&P Standard & Poor’s
SMH Signed Market Level Herding
TAQ Trade and Quote database
TRIN Traders Index
U.S. United States Abbreviations vi
UBS Union Bank of Switzerland
UMH Unsigned Market Level Herding
VAR Vector autoregression
VDAX Volatility DAX
VIX Volatility Index
VWD volume-weighted discount index
ZEW Zentrum für Europäische Wirtschaftsforschung
List of Figures vii
List of Figures
Figure 1.1: Thesis Structure .............................................................................................. 7 
Figure 3.1: CEFD History of Tri-Continental Corp. ...................................................... 42 
Figure 3.2: Baker and Wurgler (2006) composite sentiment .......................................... 44 
Figure 3.3: Sentix private investors sentiment ................................................................ 46 
Figure 3.4: Cognitrend Bull Bear Index ......................................................................... 47 
Figure 3.5: AAII Sentiment Index .................................................................................. 48 
Figure 3.6: Michigan Consumer Sentiment .................................................................... 49 
Figure 3.7: Consumer Confidence Index ........................................................................ 50 
Figure 3.8: UBS/Gallup Index of Investor Optimism ..................................................... 51 
Figure 3.9: G-Mind ......................................................................................................... 52 
Figure 3.10: CBOE put/call ratios .................................................................................. 53 
Figure 3.11: VDAX-New ............................................................................................... 54 
Figure 3.12: ISEE Sentiment Index ................................................................................ 55 
Figure 3.13: Investors’ Intelligence Bearish Sentiment Index ....................................... 57 
Figure 4.1: Euwax Sentiment Index (2004 – 2008) ........................................................ 80 
Figure 5.1: Pairwise broker correlation ........................................................................ 112 
Figure 6.1: Portfolio holding returns ............................................................................ 141 
Figure 6.2: Portfolio holding returns by market capitalization ..................................... 142 
Figure 6.3: Portfolio holding returns for small caps ..................................................... 143 
List of Tables viii
List of Tables
Table 2.1: Overview of empirical work on trading imbalances ..................................... 27 
Table 2.2: Evidence of return correlation found in empirical work ............................... 31 
Table 3.1: Summary statistics of sentiment measures .................................................... 58 
Table 3.2: Correlation of weekly and monthly sentiment measures 60 
Table 3.3: Correlation of daily indirect sentiment measures .......................................... 62 
Table 3.4: Correlation between indirect and direct weekly sentiment measures ............ 63 
Table 3.5: Codirect monthly sentiment m.......... 65 
Table 3.6: Correlation of sentiment measures and market returns ................................. 67 
Table 4.1: Summary statistics ......................................................................................... 77 
Table 4.2: Multivariate regression results for order volume .......................................... 84 
Table 4.3: Multivrder number 85 
Table 4.4: Leverage ........................................................................................................ 89 
Table 4.5: Daily sentiment correlation ........................................................................... 91 
Table 4.6: Weekly sentim........................................................................ 93 
Table 4.7: Monthly sentim....................................................................... 94 
Table 5.1: Signed and unsigned market herding measures ........................................... 106 
Table 5.2: Siarket herding measures by market period .............. 108 
Table 5.3: Daily herding measures on a broker level ................................................... 110 
Table 5.4: Daeasures by broker type ....................................................... 111 
Table 5.5: Correlation between broker types ................................................................ 113 
Table 5.6: Summary statistics by geographical origin of company .............................. 115 
Table 5.7: Summary statistics on market capitalization ............................................... 116 
Table 5.8: Modified LSV herding measure by product and order type ........................ 118 
Table 5.9: Modified LSV herding measure by firm size .............................................. 119 
Table 5.10: Comparison of LSV measures across studies ............................................ 121 
Table 6.1: Return statistics by product type ................................................................. 130 
Table 6.2: Return statistics by order and product type ................................................. 132 
Table 6.3: Return statistics for submitted orders .......................................................... 134 
Table 6.4: Controlling for market returns ..................................................................... 135 
Table 6.5: Comentum .......................................................................... 136 
Table 6.6: Controlling for market capitalization 138 
Table 6.7: Portfolio holding return statistics ................................................................ 139 
Table 6.8: Annual portfolio holding returns ................................................................. 146 
Table A.1: Summary statistics on executed order volume .............................................. ix 
Table A.2: Summary statistics on submitted orders ......................................................... x 


Introduction 1
1 Introduction
“It has long been market folklore that the best time to buy stocks is when individual
investors are bearish, and the best time to sell is when individual investors are bullish.”
Robert Neal and Simon Wheatley (1998), p.523
This citation by Robert Neal and Simon Wheatley from their 1998 article about investor
sentiment offers several insights and paves the way for this first chapter by making the
following statements: First, the opinion of individual investors on the market is
important. Second, they are often wrong. Third, individual investor sentiment may
support market timing decisions. Fourth, none of the above is scientifically proven.
In this chapter, research about retail investor sentiment in general and the research
questions addressed in this thesis in particular are motivated. In addition, the structure
of the work as well as the main contributions and related publications are presented.
1.1. Motivation
The financial crisis of the year 2008 has lead retail investors to increase their trading
activities. As the Financial Times reported, “US retail investors have been trading
stocks and options at record levels in recent months, apparently responding to the
1financial crisis by taking greater control of their own investments” . The reason for this
increased level of trading activity is likely that retail investors want to “take more direct
control of their investing, and make decisions themselves about how to rebalance their
accounts”.
Retail investor trading has become more and more important for financial institutions,
especially during times of crisis: Retail investor orders can provide liquidity to financial
institutions and represent a relatively constant source of income for order flow
providers.
2However, retail investors are often regarded as the “dumb money” , meaning that their
reallocations reduce their wealth on average. The actions of retail investors often serve
as contrary indicators in the sense that trading against these indicators would result in
profit opportunities. In research, however, no unanimous conclusion has been reached

1 Deborah Brewster, “Retail investors trading at record levels”, Financial Times, November 4, 2008
2 see e.g. Frazzini and Lamont (2008), p. 300