Trader Leverage Use and Social Interaction: The Performance Implications of Overconfidence and Social Network Participation on Retail Traders Submitted by John Hall Forman III to the University of Exeter as a thesis for the degree of Doctor of Philosophy in Finance In October 2015 This thesis is available for Library use on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. I certify that all material in this thesis which is not my own work has been identified and that no material has previously been submitted and approved for the award of a degree by this or any other University. Signature: ………………………………………………………….. 1 Abstract Overconfidence and its relationship to investor market participation is well established in the finance literature. The research into investors and social networks is only in its infancy, however. This thesis extends the literature by expanding on both subjects individually, then bringing them together. Empirical work on individual investors in the existing literature links overconfidence and excess trading, resulting in impaired returns. The preferred activity metric, monthly account turnover, encapsulates two separate elements, though. One is trade frequency. The other is leverage use. Chapter 4 of this thesis theorizes based on the existing literature that in fact trade frequency is not a good measure of overconfidence. It then demonstrates through empirical analysis of a group of individual non-professional foreign exchange traders that leverage is much more suitable to that role. Chapter 5 turns the focus to social networks, particularly with respect to information transfer. The literature in finance anticipates that network members benefit from their membership. Further, network position (social capital) enhances that benefit. This thesis challenges that expectation with respect to non-professional investors. Findings based on analysis of members of an online retail foreign exchange trader social network indicate that while there may be an educational benefit accruing to unsophisticated members, for more sophisticated ones membership appears to have a negative effect on returns. One potential explanation for the negative impact of network membership is explored in Chapter 6 in the form of impression management. It is hypothesized that sophisticated investors are influenced in their behaviour by the realization they are being observed, and also the size of their audience. Analysis of foreign exchange traders indicates an increase in leverage use among sophisticated investors as their audience size increases, coinciding with a decline in trade excess returns, making the case for an observation-based rise in overconfidence. 2 Table of Contents 1. Introduction 13 1.1. Motivation and Contributions 13 1.1.1. Leverage and overconfidence 13 1.1.2. Network participation influence on trader performance 15 1.1.3. The influence of observability on trader activity 16 1.1.4. The study group and data source 17 1.2. Thesis Structure 18 2. The Retail Spot Forex Market Structure and Participants 19 2.1. Introduction 19 2.2. Linking Retail Forex to the Inter-Bank Market 22 2.3. Retail Spot Forex Trading Mechanics 25 2.4. Retail Forex as a Zero-sum game 27 2.5. Retail Forex as a Negative-sum game 28 2.6. Participants in the Retail Spot Forex Market 33 2.7. An Adversarial Game 36 2.8. What Makes Them Think They Can Win? 37 2.9. Trade Replication Programmes 40 2.10. Research Potential 42 3. The Data 43 3.1. Introduction 43 3.2. Trade Duplication Service 44 3.3. The Traders 45 3.4. The Brokers 48 3.5. The Transactions 48 3.6. The Daily Returns 50 3.7. The Social Network 51 3.8. Overall Performance 52 3.9. Calculating Member Returns 53 3.10. Conclusion 55 4. Leverage and Overconfidence 75 4.1. Introduction 75 3 4.2. Literature Review and Hypotheses 76 4.2.1. Foundations 76 4.2.2. Overconfidence implications on trading activity 78 4.2.3. Increased focus on speculative activity 81 4.2.4. Retail foreign exchange 81 4.2.5. Overconfidence and increased trading activity 83 4.2.6. Focusing on leverage 84 4.2.7. The influence of trader experience and sophistication 86 4.2.8. Changes in leverage use are uniformly significant 87 4.3. Data & Methodology 88 4.3.1. The data 88 4.3.2. The methodology 91 4.4. Analysis 92 4.4.1. The relationship between turnover and returns 92 4.4.2. The relationships between leverage and returns 93 4.4.3. The impact of experience on overconfidence 95 4.4.4. Sophistication and overconfidence 97 4.4.5. A model of trader returns 97 4.4.6. A model of overconfident trader performance 101 4.4.7. Robustness checks 103 4.5. Further Discussion & Concluding Remarks 104 5. Social Network Participation Influence on Retail Traders 121 5.1. Introduction 121 5.2. Socially Influenced Trading 124 5.2.1. Herding behaviour and peer effects 124 5.2.2. Information transmission 126 5.2.3. Social capital 130 5.2.4. Social network membership influence on performance 132 5.2.5. Network membership influence on trading frequency 136 5.2.6. Overconfidence 138 5.2.7. Social network membership and risk seeking/avoidance 139 5.3. Data & Methodology 140 4 5.3.1. Data and returns 140 5.3.2. Estimated monthly friend connections 141 5.3.3. Deriving social capital metrics 145 5.3.4. Trade excess return 146 5.3.5. Defining the groups for analysis 146 5.4. Analysis 147 5.4.1. Network influence on member returns 147 5.4.2. Does being social increase trading activity? 150 5.4.3. Does social network membership drive overconfidence? 154 5.4.4. Does social network membership impact risk aversion? 157 5.4.5. Robustness checks 160 5.5. Conclusions & Further Discussion 160 6. Observer Effects on Trader Performance 179 6.1. Introduction 179 6.2. Literature Review and Hypotheses 181 6.2.1. Observer effects 181 6.2.2. Impression management 185 6.2.3. Disposition effect 187 6.2.4. Overconfidence 189 6.2.5. Hypothesis development 191 6.3. Data & Methodology 194 6.4. Analysis 196 6.4.1. Does visibility influence trading instrument selection? 196 6.4.2. Does observation encourage more rapid exits? 201 6.4.3. Does observability drive overconfidence? 202 6.4.4. Does an audience alter market timing strategy? 203 6.4.5. Robustness checks 206 6.5. Conclusion & Further Discussion 207 7. Conclusion 221 7.1. General 221 7.2. Caveats 223 7.3. Implications for Future Research 225 5 7.4. Final Thoughts 228 References 229 6 List of Tables and Illustrations Chapter 2: The Retail Spot Forex Market Structure and Participants Figure 2.1 – The primary parties in the retail forex market 20 Figure 2.2 – Net Positions in EUR/USD Over a 12-month Period 23 Figure 2.3 – Structure of a Copy-Trading Platform 41 Chapter 3: The Data Table 3.1 - Top 20 Retail Forex Brokers with Accounts Linked in to the Foreign Exchange Trader Social Network 56 Table 3.2 - Distribution of Trade Volumes, Holding Periods, and Returns 57 Table 3.3 - Currencies Traded by Members of the Social Network 58 Table 3.4 - Top 20 Traded Exchange Rates 59 Table 3.5 - Distribution of Account Balances and Daily Returns 60 Table 3.6 - Distribution of Member “Friend” Connections 61 Table 3.7 - Comparison of Social Network Member Quarterly Profitability Percentages to Broad Averages 62 Figure 3.1 – Growth in Membership of a Trading Social Network 63 Figure 3.2 – Active Members of a Trading Social Network 63 Figure 3.3 – Primary Language of Social Network Members 64 Figure 3.4 – Geographic Region of Social Network Members 65 Figure 3.5 – Primary Trading Style of Social Network Members 66 Figure 3.6 – Average Trades Per Week of Social Network Members 67 Figure 3.7 – Years of Trading Experience of Social Network Members 68 Figure 3.8 – Performance Privacy Choices of Social Network Members 69 Figure 3.9 – Ages at Registration for Members of a Trading Social Network 70 Figure 3.10 – Social Network Information 71 Figure 3.11 – Position Balances Amongst Members 72 7 Figure 3.12 – Sample Exchange Rate Spreads 73 Figure 3.13 – Sample Exchange Rate Spreads 74 Chapter 4: Leverage and Overconfidence Table 4.1 - Descriptive Statistics on Account Balances, Trade Frequency, Transaction Volume, Turnover, Return, Trade Holding Period, and Trade Leverage with Inexperienced and Regional Proportions 107 Table 4.2 - Descriptive Statistics of Trading Activity and Performance Based on Data Provided in User Profiles – Geographic Region 108 Table 4.3 - Descriptive Statistics of Trading Activity and Performance Based on Data Provided in User Profiles – Experience 109 Table 4.4 - Monthly Aggregate Member Mean Returns 110 Table 4.5 - Descriptive Statistics for Returns and Relative Returns for Trader Quintiles Formed on Monthly Turnover 111 Table 4.6 - Descriptive Statistics for Returns for Trader Quintiles Formed on Monthly Trade Frequency and Average Trade Leverage 112 Table 4.7 - Deleveraged Returns Across the Trading Activity Quintiles Derived from Turnover, Monthly Trades, and Average Trade Leverage 113 Table 4.8 - Experience and its Impact on Trading Activity and Returns 114 Table 4.9 - Descriptive Statistics for Returns for Trader Quintiles Formed on Average Monthly Account Balance as a Proxy for Trader Sophistication 115 Table 4.10 - Correlation of Trader Returns, Leverage, Trades, Experience, Account Balance, and Geographic Region 116 Table 4.11 - Regression Model Performance for Leverage, Experience, Trade Frequency, Sophistication, Trader Geographic Region, and Trading Style on Trader Monthly Returns, with Month Fixed Effects 117 Table 4.12 - Trading Activity Influence on Monthly and Mean Trade Returns, with Month and Trader Fixed Effects 118 8 Table 4.13 - Regression Sub-Sample Descriptive Statistics on Account Balances, Trade Frequency, Turnover, Return, Trade Holding Period, and Trade Leverage with Inexperienced and Regional Proportions 119 Chapter 5: Social Network Participation Influence on Retail Traders Figure 5.1 - Friend Estimation 164 Table 5.1 - Descriptive Statistics for Pre-Membership vs.