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INFLUENCE of SOCIOECONOMIC and DEMOGRAPHIC CHARACTERISTICS OVER HERDING in ESTONIAN STOCK MARKET Master’S Thesis

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INFLUENCE of SOCIOECONOMIC and DEMOGRAPHIC CHARACTERISTICS OVER HERDING in ESTONIAN STOCK MARKET Master’S Thesis TALLINN UNIVERSITY OF TECHNOLOGY School of Business and Governance Department of Economics and Finance . Gaganmeet Singh Dhir INFLUENCE OF SOCIOECONOMIC AND DEMOGRAPHIC CHARACTERISTICS OVER HERDING IN ESTONIAN STOCK MARKET Master’s Thesis Supervisor: Associate Professor Tõnn Talpsepp Tallinn 2017 I declare I have written the master’s thesis independently. All works and major viewpoints of the other authors, data from the other sources of literature and elsewhere used for writing the paper have been referenced. Gaganmeet Singh Dhir .................................... (signature, date) Student’s code: 156480 Student’s e-mail address: [email protected] Supervisor: Associate Professor Tõnn Talpsepp The thesis conforms to the requirements set for the master’s theses .............................................................. (signature, date) Chairman of defence committee: Permitted to defence .............................................................. (Title, name, signature, date) TABLE OF CONTENTS ABSTRACT........................................................................................................................ 4 INTRODUCTION............................................................................................................. 5 1. LITERATURE............................................................................................................... 8 1.1. Traditional versus Behavioural Finance...................................................................... 8 1.2. Herd Behaviour in Financial Markets......................................................................... 10 1.3. Previous literature on Demographic and Socio-Economic herding........................... 12 2. METHODOLOGY AND DATA............................................................................. 18 2.1. Prior models to detect herding.................................................................................... 18 2.2. Research Design......................................................................................................... 20 2.3. Data and descriptive statistics..................................................................................... 21 2.3.1. Data.................................................................................................................... 21 2.3.2. Descriptive statistics.......................................................................................... 22 3. EMPIRICAL RESULTS............................................................................................ 28 3.1. Herding by Gender..................................................................................................... 28 3.2. Herding by Age.......................................................................................................... 32 3.3. Herding by Education................................................................................................. 34 3.3.1. Herding by level of degree.................................................................................. 34 3.3.2. Herding by type of degree................................................................................... 37 3.3.3. Herding by grade in mathematics....................................................................... 39 3.3.4. Herding by grade in English language................................................................ 41 3.3.5. Herding by grade in Native language.................................................................. 42 3.4. Discussion................................................................................................................... 44 CONCLUSION................................................................................................................. 47 REFERENCES.................................................................................................................. 50 APPENDICES................................................................................................................... 56 2 Appendix A: Tables........................................................................................................... 56 Table 1: T-test of gender influence.............................................................................. 56 Table 2: ANOVA single factor test for age influence................................................. 57 Table 3: ANOVA single factor test of level of degree influence................................ 58 Table 4: ANOVA single factor test of degree type influence..................................... 59 Table 5: ANOVA single factor test of Mathematics influence................................... 60 Table 6: ANOVA single factor test of English language influence............................ 61 Table 7: ANOVA single factor test of Native language influence.............................. 62 Table 8: Descriptive analysis of stocks (Gender influence) ....................................... 63 Table 9: Descriptive analysis of market (Gender influence) ...................................... 63 Table 10: Descriptive analysis of stocks (Age influence) .......................................... 64 Table 11: Descriptive analysis of market (Age influence) ......................................... 64 Table 12: Descriptive analysis of stocks (Degree level influence) ............................ 65 Table 13: Descriptive analysis of market (Degree level influence) ........................... 65 Table 14: Descriptive analysis of stocks (Degree type influence) ............................. 66 Table 15: Descriptive analysis of market (Degree type influence) ............................ 66 Table 16: Descriptive analysis of stocks (Mathematics influence) ............................ 67 Table 17: Descriptive analysis of market (Mathematics influence) ........................... 67 Table 18: Descriptive analysis of stocks (English language influence) ..................... 68 Table 19: Descriptive analysis of market (English language influence) .................... 68 Table 20: Descriptive analysis of stocks (Native language influence) ....................... 69 Table 21: Descriptive analysis of market (Native language influence) ...................... 69 3 ABSTRACT The study investigates the influence of demographics (educational background) and socioeconomic personality traits (age and gender) on the herding behaviour of individual investors in Estonian stock market. The study is deemed to be extremely beneficial for the individual investors along with financial advisors. The study would help financial advisors to know the extent of behavioural bias (herding) present in the Estonian stock market and they could advise the investors in a better manner to mitigate the tendency to herd. The study is based on the quarterly stock transactions of Estonian investors from January 2004 to December 2012. To measure the extent of herding the study follows Frey, Herbst and Walter (2007) (FHW indicator) that measures herding as the excessive dispersion of the transactions (Buying/Selling) on the similar side for the stocks. The herding measures are calculated for each stock as well as for the whole market for all the 36 quarters. The stock wide herding measures suggest that there is a clear difference in the attitudes of gender groups towards different stocks and industries. Other than that for most of the stocks, people with age group of 30 to 40 herd less than the other age groups in the study. There is also a significant influence of educational parameters (level of degree, type of degree, grades in Mathematics, grades in English language and grades in Native language) on the herding behaviour of groups for each stock. Furthermore, the market wide results show the degree of relative difference in the herding measures of the groups which is analysed through statistical tests. It also shows the influence of 2007-2008 financial crises on the herding behaviour of Estonian investors. The analysis put forward interesting observations that serves as an asset to the existing literature in Behavioural finance. Keywords: Behavioural Finance, Herd Behaviour, Demographic Characteristics, Socioeconomic Characteristics, FHW herding measure, Tallinn (Estonian) Stock Exchange. 4 INTRODUCTION Human behaviour is a result of psychological and external factors (Endler and Magnusson, 1976). Maital in 1986 suggested that individual traits, risk tolerance, return, information perception and sentiments affect the behaviour of investors. According to the prospect theory given by Kahneman and Tversky in 1979, the decisions of an investor gets affected by the introduction of uncertain conditions. In the quest of generating profit, they start looking out for information from other sources or follow the advice of a professional investor. The prospect theory says that the investors tend to vary their actual decisions from rationality because of the changing psychological mind-set of the investor. Behavioural finance names one such behavioural bias of the investors as herding. Herding behaviour is understood as an act of irrational decision making by an investor where the individual follows a group of investors and values the group’s decision more over the available information. This often leads to extreme fluctuation in the stock market. Herding has a tendency to drive away the prices from their actual values. The herding behaviour is known to happen because of investors abandoning their own private information and following the action of others. Herding is seen
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