Prelims

Understanding the Investor: A Maltese Study of Risk and Behavior in Financial Investment Decisions

ISBN: 978-1-78973-706-6, eISBN: 978-1-78973-705-9

Publication date: 19 June 2019

Citation

Bonello, A. (2019), "Prelims", Grima, S. and Spiteri, J. (Ed.) Understanding the Investor: A Maltese Study of Risk and Behavior in Financial Investment Decisions, Emerald Publishing Limited, Bingley, pp. i-xxiii. https://doi.org/10.1108/978-1-78973-705-920191008

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Emerald Publishing Limited

Copyright © 2019 Emerald Publishing Limited


Half Title Page

Understanding the Investor

Title Page

Understanding the Investor: A Maltese Study of Risk and Behavior in Financial Investment Decisions

By Antonietta Bonello

Edited By Simon Grima & Jonathan Spiteri

United Kingdom – North America – Japan India – Malaysia – China

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Emerald Publishing Limited

Howard House, Wagon Lane, Bingley BD16 1WA, UK

First edition 2019

Copyright © 2019 Emerald Publishing Limited

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British Library Cataloguing in Publication Data

A catalogue record for this book is available from the British Library

ISBN: 978-1-78973-706-6 (Print)

ISBN: 978-1-78973-705-9 (Online)

ISBN: 978-1-78973-707-3 (Epub)

Dedication

Dedicated to the individual investor.

Contents

List of figures xi
List of tables xiii
List of abbreviations xix
Preface xxi
Acknowledgments xxiii
1. An Introduction 1
Background to the book 1
The reasons behind researching the Maltese investor trading on the Malta Stock Exchange 3
Statement of the problem 4
Aim and objectives of the book 5
The research questions 5
Propositions 5
Conceptual framework 6
Significance of the study 7
Contents 8
2. Literature Review 9
Introduction 9
The market 10
Investment 11
Financial investment in Malta 12
The investor 15
Risk, risk tolerance, and risk appetite 17
Expectations and performance 20
Trading and investor behavior 21
Disposition and risk aversion 23
Behavioral bias 24
Overconfidence 25
Information 28
Financial literacy 29
The financial advisor 29
Other factors 31
3. Methodology 43
Research design 43
Participant selection 44
Data collection methods 47
Instrumentation 48
Logistics of data collection 52
Ethics 54
Data analysis 54
Summarizing the tests 58
Limitations of the methodology 60
4. Analysis 67
Demographics 67
Proposition 1: Initially Maltese investors have high expectations in terms of financial returns while returns are lower than what was expected 79
Proposition 2A: Investors sell winners and retain losers 86
Proposition 2B: Investors are risk averse in cases of gain but risk takers in cases of loss 117
Proposition 2C: Overconfident investors trade more and earn less 133
Proposition 3A: Information at the hand of investors is mostly promotional 147
Proposition 3B: Investors do not know their investments 152
Proposition 3C: Knowledge is positively related to maturity and confidence 162
Other factors – Advice received 170
Other factors – Familiarity 181
Other factors – Herding 185
Other factors – Investor’s fear 189
Other factors – Past experiences 193
193Other factors – Costs 199
5. Conclusion 205
Summary of the salient findings 205
Answers to research questions 207
Conclusion on propositions 209
Discussion 213
Limitations of the study and mitigation 217
Further research 218
Significance and originality of findings 219
Recommendations 219
Overall conclusion 221
Appendices 223
Appendix 1: Other findings: By descriptives 223
Appendix 2: Questionnaire 234
Appendix 3: Layout of analysis 255
Appendix 4: Interview questions 262
Appendix 5: Interview questionnaire results 264
Appendix 6: Annex to proposition 2C – Exploring the traits to the composite of overconfidence 269
References 279
Index 295

List of figures

Fig. 2.1. The different players in the financial market. 9
Fig. 2.2. Narrowing down the unit of study. 10
Fig. 2.3. The efficient frontier. 11
Fig. 2.4. Asymmetrical value function. 23
Fig. 3.1. Mean score for composite of overconfidence. 57
Fig. 3.2. Coefficient correlation between composite of overconfidence and that of overtrading. 58
Fig. 4.1. Composition of sample size by age and gender. 70
Fig. 4.2. Mean score for the composite of risk aversion. 125
Fig. 4.3. Mean score for the composite of loss aversion. 130
Fig. 4.4. Mean score for composite of overconfidence. 137
Fig. 4.5. Mean score for the composite of overtrading. 142
Fig. 4.6. Correlation between overconfidence and that of overtrading. 144
Fig. 4.7. Mean score for the composite “not keeping track of own investments.” 158
Fig. 4.8. Mean score for the composite of maturity. 163
Fig. 4.9. Correlation between the composite of overconfidence and that of maturity. 164
Fig. 4.10. Mean score for the composite of confidence. 166
Fig. 4.11. Pearson’s correlation for the composite of overconfidence and that of confidence. 167
Fig. 4.12. Mean score for the composite of advice. 171
Fig. 4.13. Histogram for the composite of familiarity. 183
Fig. 4.14. Mean score for the composite of herding. 186
Fig. 4.15. Mean score for the composite of fear. 191
Fig. 4.16. Mean score for the composite of learning from the past experiences. 196
Fig. 4.17. Mean score for the composite of costs. 200
Fig. 5.1. Every investment is an opportunity. 208
Fig. 5.2. An insight into the different considerations behind the investor’s decision. 208
Fig. 5.3. A simplified version of the investment decision process. 208

List of tables

Table 2.1. Funds uncovered by various investment registration schemes. 14
Table 2.2. Deposits kept at Maltese banks for the years 2000–2017 (october). 15
Table 2.3. Market share for Maltese residents (individual investors). 16
Table 2.4. Value investing versus growth investing. 17
Table 2.5. Differences and similarities of marital status and gender vis-à-vis investment trading. 33
Table 3.1. Description of statistical tests used depending on the type of variable. 59
Table 4.1. Response breakdown for each phase in data collection from the survey. 67
Table 4.2. Breakdown of the 990 database responses. 68
Table 4.3. Percentage of age composition using the entrop et al. (2016) Model. 69
Table 4.4. Age by gender using a wider range of age groups. 69
Table 4.5. Age composition sample versus NSO data. 71
Table 4.6. Gender composition. 72
Table 4.7. Employment by gender. 73
Table 4.8. Occupation by original classification. 73
Table 4.9. Main occupation by survey and by NSO statistics. 75
Table 4.10. Occupation reclassified. 76
Table 4.11. Marital status by gender. 76
Table 4.12. Cross-tabulation of dependents by gender. 77
Table 4.13. Frequency of home ownership. 77
Table 4.14. Frequency of income. 78
Table 4.15. Cross-tabulation of income by gender. 79
Table 4.16. Frequency of investors’ expected rates of returns. 79
Table 4.17. Cross-tabulation of the expected rate of return and age. 80
Table 4.18. Frequency of perceived earnings for the last 12 months. 81
Table 4.19. Cross-tabulation of perceived earnings from trade (last 12 months). 81
Table 4.20. Breakdown of monetary earnings in relation to perceived outcome 82
Table 4.21. Cross-tabulation of satisfaction of perceived earnings by trade in the last 12 months. 83
Table 4.22. Advisors’ replies on the investor’s expectations of returns. 84
Table 4.23. Frequency and mean for survey question 19. 87
Table 4.24. Significant associations for survey question 19 with demographic variables. 87
Table 4.25. Cross-tabulation for survey question 19a with gender. 88
Table 4.26. Cross-tabulation for question 19b with age. 89
Table 4.27. Cross-tabulation of survey question 19c with gender. 90
Table 4.28. Cross-tabulation for survey question 19c with age. 91
Table 4.29. Cross-tabulation of survey question 19c with income. 92
Table 4.30. Cross-tabulation of survey question 19c with occupation. 93
Table 4.31. Frequency for survey questions 19e and 19f. 94
Table 4.32. Cross-tabulation for survey question 19e with age. 94
Table 4.33. Cross-tabulation of survey question 19f with age. 95
Table 4.34. Cross-tabulation of survey question 19c with survey question 19a. 96
Table 4.35. Cross-tabulation of survey question 19c with survey question 19b. 97
Table 4.36. Cross-tabulation with survey question 19c with survey question 19e. 98
Table 4.37. Cross-tabulation of survey question 19g with gender. 99
Table 4.38. Cross-tabulation of survey question 19g with income. 100
Table 4.39. Frequency for survey question 20. 102
Table 4.40. Significant association of statements in Q20 with demographic variables. 102
Table 4.41. Cross-tabulation of survey question 20a with age. 103
Table 4.42. Cross-tabulation of survey question 20b with age. 104
Table 4.43. Cross-tabulation of survey question 20c with age. 105
Table 4.44. Cross-tabulation of survey question 20c with income. 106
Table 4.45. Cross-tabulation of survey question 20d with age. 107
Table 4.46. Cross-tabulation with survey question 20d with income. 108
Table 4.47. Cross-tabulation of survey question 20e with gender. 109
Table 4.48. Cross-tabulation of survey question 20e with occupation. 110
Table 4.49. Cross-tabulation of survey question 20e with 20a. 111
Table 4.50. Cross-tabulation of survey question 20f with gender. 112
Table 4.51. Cross-tabulation of survey question 20f with income. 113
Table 4.52. Advisors’ replies: disposition effect in case of gains. 114
Table 4.53. Advisors’ replies: disposition effect in case of losses. 115
Table 4.54. Probability of gain. 118
Table 4.55. Probability of loss. 118
Table 4.56. Cross-tabulation of probability of gain with age. 119
Table 4.57. Cross-tabulation of probability of gain with perceived earnings. 119
Table 4.58. Cross-tabulation of probability of loss with age. 120
Table 4.59. Cross-tabulation of probability of loss with income. 120
Table 4.60. Frequency of survey question 33b. 121
Table 4.61. Frequency of survey question 33c. 121
Table 4.62. Cross-tabulation of risk with gender. 122
Table 4.63. Cross-tabulation of risk with income. 122
Table 4.64. Cross-tabulation of loss with gender. 123
Table 4.65. Cross-tabulation of loss with age. 124
Table 4.66. Frequency for composite of risk aversion. 125
Table 4.67. Mean score of risk aversion by gender. 126
Table 4.68. Mean score of risk aversion by income. 127
Table 4.69. Advisors’ replies: investors’ risk pattern by income. 127
Table 4.70. Mean score of risk aversion by age. 128
Table 4.71. Frequency for the composite of loss aversion. 129
Table 4.72. Mean score for loss aversion by gender. 130
Table 4.73. Mean score for loss aversion by occupation. 131
Table 4.74. Mean score for loss aversion by income. 131
Table 4.75. Advisors’ replies on investors’ risk tolerance. 132
Table 4.76. Advisors’ replies on investors’ greatest risk. 132
Table 4.77. Advisors’ replies on investors’ biggest fear. 132
Table 4.78. Traits for the composite of overconfidence. 134
Table 4.79. Frequency for composite of overconfidence. 135
Table 4.80. Associations of the composite of overconfidence with demographic variables. 136
Table 4.81. Mean score for the composite of overconfidence by gender. 138
Table 4.82. Mean score for the composite of overconfidence by occupation. 138
Table 4.83. Mean score for the composite of overconfidence by income. 139
Table 4.84. Frequency for survey question 17. 139
Table 4.85. Cross-tabulation of trading frequency by gender. 140
Table 4.86. Mean for overconfidence and frequency of trades. 140
Table 4.87. Traits for the composite for overtrading. 141
Table 4.88. Frequency for the composite of overtrading. 141
Table 4.89. Mean score for the composite of overtrading by income. 142
Table 4.90. Mean score for the composite of overtrading by earnings. 143
Table 4.91. Mean score for the composite of overtrading with perceived earnings. 143
Table 4.92. Mean score of the composite of overconfidence by perceived earnings. 144
Table 4.93. Advisors’ replies of overconfidence and overtrading by investors. 145
Table 4.94. Frequency for indicator variables of promotional sources (0.00). 147
Table 4.95. Frequency of exposure to non-promotional sources of information (1.00). 148
Table 4.96. Frequency to survey question 35. 148
Table 4.97. Cross-tabulation of promotional sources by gender. 149
Table 4.98. Advisors’ replies on information at the hands of investors. 149
Table 4.99. Advisors’ replies on the influence of media. 150
Table 4.100. Frequency of investors’ knowledge on investments. 152
Table 4.101. Advisors’ replies on investors’ knowledge on investments. 153
Table 4.102. Ranking of investor’s considerations prior to investing. 153
Table 4.103. Investors’ considerations prior to investing by percentages. 154
Table 4.104. Cross-tabulation of considerations prior to investing by income. 154
Table 4.105. Associations for information on issuing companies by demographics. 155
Table 4.106. Cross-tabulation of considerations of management policies by age. 155
Table 4.107. Frequency for the composite “not keeping track of own investments.” 157
Table 4.108. Mean score for the composite “not keeping track of own investments” by gender. 158
Table 4.109. Mean score for the composite “not keeping track of own investments” by occupation. 159
Table 4.110. Advisors’ replies: investor’s keeping track of own investments. 159
Table 4.111. Frequency for the composite of maturity. 162
Table 4.112. Mean score for the composite of maturity by status. 163
Table 4.113. Pearson correlation coefficient of the composite of overconfidence and that of maturity. 164
Table 4.114. Means score for the composite of maturity by seeking advice. 165
Table 4.115. Frequency for the composite of confidence. 165
Table 4.116. Pearson’s correlation for the composite of overconfidence and that of confidence. 167
Table 4.117. Mean score of the composite of confidence by income. 168
Table 4.118. Mean score for the composite of confidence by knowledge. 168
Table 4.119. Mean score for the composite of maturity by knowledge. 169
Table 4.120. Advisors’ replies: investor’s confidence by gender. 169
Table 4.121. Advisors’ replies: effect of knowledge on investor’s maturity on investments. 169
Table 4.122. Traits for the composite of how investors relate to advice received. 171
Table 4.123. Mean score for the composite of advice by gender. 172
Table 4.124. Mean score for the composite of advice by occupation. 172
Table 4.125. Mean score for the composite of advice by income. 172
Table 4.126. Expectations of investors in relation to financial advisors. 173
Table 4.127. Ranking of the expectations of investors in relation to financial advisors. 174
Table 4.128. Traits of financial advisors as perceived by investors. 174
Table 4.129. Ranking of the traits of financial advisors as perceived by investors. 175
Table 4.130. Advisors’ replies of investors’ preference to seek advice prior to investing. 175
Table 4.131. Advisors’ replies on how they perceive investors’ view the advice given. 176
Table 4.132. Effect of advice on behavioral traits. 178
Table 4.133. Frequency for the investors preference between local and foreign investments. 182
Table 4.134. Traits for the composite of familiarity. 182
Table 4.135. Mean score for the composite of familiarity by gender. 183
Table 4.136. Mean score for the composite of familiarity by income. 184
Table 4.137. Mean score for the composite of familiarity by age. 184
Table 4.138. Mean score for the composite of familiarity by status. 184
Table 4.139. Mean score for the composite of familiarity in relation to issuing companies. 185
Table 4.140. Traits for the composite of herding. 186
Table 4.141. Mean score for the composite of herding by gender. 187
Table 4.142. Mean score for the composite of herding by occupation. 187
Table 4.143. Mean score for the composite of herding by income. 187
Table 4.144. Mean score of the composite of herding by investors fear of making a bad decision. 188
Table 4.145. Advisors’ replies: influence by family and friends. 188
Table 4.146. Frequency for the fears experienced by investors. 190
Table 4.147. Ranking for the fears experienced by investors. 190
Table 4.148. Mean score for the composite of fear by gender. 191
Table 4.149. Mean score for the composite of fear by income. 192
Table 4.150. Mean score of the composite of fear by perceived earnings. 192
Table 4.151. Advisors’ replies: investor’s fear. 192
Table 4.152. Frequency for lessons learnt by investors. 194
Table 4.153. Advisors’ replies on investors’ risk tolerance. 194
Table 4.154. Ranking for the frequency for lessons learnt by investors. 195
Table 4.155. Number of lessons learnt from past experiences. 197
Table 4.156. Mean score for the composite of learning from past experiences by gender. 197
Table 4.157. Associations of the composite of learning from past experiences with other composites. 198
Table 4.158. Advisors’ replies in relation to the importance of past experiences for the investor. 198
Table 4.159. Frequency to statements related to the composite of transaction costs and commissions. 200
Table 4.160. Advisors’ replies on how they perceive investors consider costs. 201
Table 5.1. Summary of results of propositions. 209
Table 5.2. Acceptance or refusal of propositions. 215
Table A1. Breakdown of investors’ expenditure. 223
Table A2. Investors’ preference for form of payment received. 223
Table A3. Frequency showing the investors’ preferred source of finance. 224
Table A4. Ranking showing investor’s preferred source of finance 225
Table A5. Investor’s reasons to invest. 225
Table A6. Ranking for the investors’ reasons to invest. 226
Table A7. Frequency of investors’ concerns in relation to different risks 226
Table A8. Ranking for the frequency of investors’ concerns in relation to different risks. 227
Table A9. Composition of portfolio of respondents’ investments. 228
Table A10. Investors’ considerations prior to investing. 229
Table A11. Range of amounts invested. 230
Table A12. Frequency for follow-up actions after trading. 231
Table A13. Ranking for the frequency for follow-up actions after trading. 232
Table A14. Investor’s considerations on the MSE. 233
Table A15. Ranking of the investors’ considerations on the MSE. 233

List of abbreviations

AGH Attention Grabbing Hypothesis
BOV Bank of Valletta
CAPM Capital Asset Price Model
CBM Central Bank of Malta
DWDTI Different ways to disseminate information
FA Financial Advisor
GDP Gross Domestic Product
IDH Information Dissemination Hypothesis
ISO International Standard Organisation
MIFID Markets in Financial Instruments Directive
MFSA Malta Financial Services Authority
MGS Malta Government Stock
MMA Mixed Method Approach
MRS Mean Rating Score
MSE Malta Stock Exchange
NSO National Office of Statistics
p. Page
PPH Price Pressure Hypothesis
Q. Question
SPSS Statistical Package for the Social Sciences
SR Standard Residual

Preface

Dear Reader,

I would like to thank you for taking the interest and the time to read through this book. Writing it was a most exciting and inspiring experience. What started as a requirement for a Masters by Research degree, turned into a much needed deep and compelling investigation.

If you are an investor, interested in financial investment or come in contact with investors on a regular basis, then, this book should be an interesting read to you. This is because it delves into the realm of stocks and shares, exploring different scenarios, and analyzing alternative possibilities and outcomes: all embedded in the ever present element of risk.

The biggest impediment of this study was brought about by unexpected financial and political scandals which led to all gatekeepers closing ranks in an effort to safeguard customer data protection. This limitation was circumvented by the use of social media and the help of newly made connections with financial institutions.

Replies from online and paper surveys were compared to those from semi-structured interviews with financial advisors, to extract the realities of the Maltese financial market. The book sheds light onto the fears, concerns, habits, and choices of the Maltese financial investor with the purpose of understanding the investor better. Unfortunately, it also uncovers some harsh unspoken truths, for which I make no apologies, as I believe that it is important to face a shortcoming in order to improve.

Despite the structure of the study, each chapter can be read in isolation. However, reading it in its entirety will give you a better understanding of the profile of the Maltese investor. A glimpse into the appendix is also encouraged as it offers a databank of information most useful to those interested in the field.

I appeal to you, managing authorities and financial advisers to use this book as a tool by which to enhance the services offered, and to you, investors, to learn from it and improve your trading performance. Whatever the use you make of this book, I sincerely hope it appeals to you and instigates more research on financial trading and financial investors.

Antonietta Bonello.

20-09-2018

Acknowledgments

No work is done alone, and I certainly required the contribution of hundreds in the completion of this book.

I, therefore, would like to take the opportunity to reflect on those kind-hearted people who have somehow shown support, all those who reached out to help me, and/or contributed in some way to this study. To all those individual investors who took the time to patiently and selflessly, answer the questionnaire.

I would also thank all those who contributed to the distribution of the questionnaire and to all those talented financial advisors who have accepted to sit for an interview and shared their experiences. Thank you all, your help is greatly appreciated.

My gratitude accompanied by many hugs goes to my husband and children for always being there for me. Thank you for making do, and for the many and much needed cups of tea that came my way.

Appreciation also goes to my tutor and co-editor, Dr Simon Grima, for his valuable advice, constant support. and unwavering encouragement. Sincere thanks to you, Dr Grima.

Lastly, my thanks goes to my publisher and her team for their attention to detail and publishing advice.

A renewed “thank you” to all, as without you this book would not have been possible.