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1 Influence of Investor s Personality Traits and Demographics on Overconfidence Bias Farheen Btool Zaidi Lecturer in Finance Institute of Business & Information Technology (IBIT) University of the Punjab, Quaid-e-Azam Campus, Lahore, Pakistan Abstract Muhammad Zubair Tauni Graduate Student of MBIT (Specialization in Finance) Session Institute of Business & Information Technology (IBIT) University of the Punjab, Quaid-e-Azam Campus, Lahore, Pakistan This research was conducted in the field of Behavioral Finance, the purpose of which is to identify the relationship between Investor s Personality Traits, Demographics and Overconfidence Bias in Lahore Stock Exchange (LSE). To achieve the purpose, survey methodology was used and a questionnaire was distributed among 200 randomly selected investors out of which 170 questionnaires were used for analysis and rests were discarded due to incomplete or non serious response. The data collected was processed into SPSS 19.0 and different statistical tools were applied to obtain the results of study. Findings showed that there is a positive relationship between overconfidence bias and Agreeableness, Extroversion & Consciousness; and negative relationship between Overconfidence bias and Neuroticism. The results also showed that there is an association between investment experience and overconfidence bias. Hence, it was concluded that investor s of Lahore Stock Exchange (LSE) are not purely rational and the explanations provided by traditional financial theory do not hold true. Keywords: Behavioral Finance, Demographics, Personality Traits, Overconfidence Bias, Irrational Behavior, Lahore Stock Exchange 1. Introduction According to conventional financial theory, individual investors are perfectly rational and wealth maximizers in financial decisions. However the idea of fully rational investors that have perfect control on their decisions to maximize their utility is becoming less popular. In efficient markets investors are considered as rational, unbiased and consistent who make optimal investment decisions without the effects of psyche and emotions (Hayat, Bukhari, & Ghufran, 2006). COPY RIGHT 2012 Institute of Interdisciplinary Business Research 730

2 However sometimes emotions and psyche influence their decisions, causing them to behave in an irrational way. Behavioral Finance provides the explanation for this phenomenon. Behavioral finance is an emerging field that combines the Behavioral or Psychological aspects with conventional economic and financial theories to provide explanation of why people make irrational financial decisions (Phung, 2008). Behavioral finance explains the irrational behavior of investors that can affect the security market prices. It examines how cognitive and emotional errors influence investor s decision making process. The contribution of this field does not mean that it has completely neglected or it lessens the importance of the fundamental work and the proponents of efficient market hypothesis. Rather it tries to eliminate the unrealistic assumptions of traditional economic and financial theories in decision making process to make it more realistic. Without this certain aspects of financial markets cannot be understood (Hayat, Bukhari, & Ghufran, 2006). The behavioral finance study falls into two subtopics: Behavioral Finance Micro (BFMI) and Behavioral Finance Macro (BFMA). BFMI examines individual behavior but BFMA focuses on the stock market behavior as a whole. In BFMI, we examine behaviors or biases of individual investors and compare irrational investors to rational investors, as described in classical economic theory, also known as homo economics, or rational economic man. In BFMA, we detect and describe anomalies in the markets which are against the efficient markets. Efficient Market Hypothesis (EMH) states that markets are always efficient, but in reality markets are not always efficient. An abnormal market behavior can occur, such as the January effect, Monday effect, which means that human behavior influences securities prices and, therefore, markets (Pompian, Behavioral Finance and Wealth Management, 2006). This research has focused on BFMI, i.e. the study of individual investor behavior. The present study assumes that investors of specific personality traits of Lahore Stock Exchange (LSE) can fall prey to behavioral biases such as overconfidence bias. Lahore stock exchange (LSE) is seemed to be highly volatile and sensitive to incorporate unanticipated news and shocks to impact trading activities and at the same time it can recover after these shocks. Psychology of investors of Lahore Stock Exchange can also play important role in their investment decisions and this is motive behind this study. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 731

3 2. Literature Review Much of the literature provides the evidence of how financial markets function and how individual investors make decisions in the financial markets. First established in Homo economics is a simple model of human behavior stated that humans are perfectly rational in their economic decisions (Simon, 1955). However, many psychologists believe that human are not perfectly rational and human behavior is less governed by rationality than subjective emotions such as love, fear, hate, pleasure and pain. Thus, perfect rationality is only a theoretical concept (Pompian, Behavioral Finance and Wealth Management, 2006). 2.1 Standard Finance During 1970s standard finance theory of market efficiency became the accepted model for the market behavior. Standard finance is the body of knowledge built on the pillars of the arbitrage principles of Miller and Modigliani, the portfolio principles of Markowitz, the capital asset pricing theory of Sharpe, Lintner, and Black, and the option-pricing theory of Black, Scholes, and Merton (Statman, 1992). Standard finance approach is based on the assumptions that cannot be applied in reality. It is based on rules that address how investors should behave rather than describing how they behave in reality (Pompian, Behavioral Finance and Wealth Management, 2006). Standard finance theories explain the financial market using models in which participants are considered to be purely rational. When participants receive new information they update their beliefs and choose alternatives that are normatively acceptable. Unfortunately, with the passage of time some market behaviors could not be explained under this framework and it was argued that some market behaviors can be explained better using those models in which participants behave irrationally (Barberis & Thaler, 2002) 2.2 Behavioral Finance In 1980s a new field was emerged known as Behavioral Finance that combines the psychological and behavioral theories with traditional financial theories to provide the explanations of why people make irrational decisions (Phung, 2008). Efficient Market Hypothesis provides the explanation of how people should make investment decisions but how people actually behave in stock market in the subject of behavioral finance (Peter, 1996). People in standard finance are rational. People in behavioral finance are normal. Investors are affected by their behavior and psychology in the risk assessment and issue of framing in financial decisions (Statman M., 1995). People do not use rational judgment while making financial decisions. Behavioral finance COPY RIGHT 2012 Institute of Interdisciplinary Business Research 732

4 describes why people deviate from optimal investment decisions by incorporating aspects of human nature in financial models (Barber & Odeab, 1999). Kahneman and Tversky contributed a lot in the field of behavioral finance with their work on prospect theory. Earlier it was believed that when people make choices they see the combined net effect of gains and losses for over all evolution of each choice. Researcher used utility concept as the satisfaction for each choices and said that people choose those choices that maximize their utility. But prospect theory showed that people value gain and losses differently and make choices on the basis of perceived gains or perceived losses rather than actual gains or actual losses (Phung, 2008). Behavioral Finance explains the cognitive and emotional factors that influence the decision making process of individual, groups and organizations (Ricciardi & Simon, 2011). Gradually Behavioral Finance become a widely adopted filed within finance and acknowledge by many scholars. (Bernéus, Sandberg, & Wahlbeck, 2008). 2.3 Overconfidence Bias Overconfidence in its simplest way could be defined as an inopportune belief toward a witnessed reasoning, judgment and the person's cognitive abilities (Sadi, Ghalibaf, Rostami, Gholipour, & Gholipour, 2011). Sometimes investors defined very narrow confidence intervals in their prediction, which is known as Predication Overconfidence whereas investors consider themselves very certain in their judgments which is called Certainty Overconfidence. The people susceptible to prediction overconfidence ignore risks associated with their investments while those who are susceptible to certainty overconfidence trade too much and maintain undiversified portfolio (Pompian, Behavioral Finance and Wealth Management, 2006). Many investors perceive themselves better than others and this tendency to think them as above average can be resulted in overconfidence bias that can ultimately lead to trade excessively (Hayat, Bukhari, & Ghufran, 2006). During the technological bubble of 1990s investor traded too much in technological stock due to overconfidence. Investors were sure that they will be able to get super return by holding concentrated position in the technological stocks. But when this bubble burst all the gains went down (Pompian, Behavioral Finance and Wealth Management, 2006). Investors tend to be overconfident in picking stocks. This results in excessive trading volume. Investors who conduct more trades receive lower yields than the average return (Odean, 2002). People due to overconfidence bias overestimate their knowledge, underestimate risk and exaggerate their ability to control events (Nofsinger, 2002). Investors take bad bets due to COPY RIGHT 2012 Institute of Interdisciplinary Business Research 733

5 overconfidence bias because they overestimate their knowledge and tend to trade excessively than otherwise. Overconfidence leads them to trade high volume. Investors overestimate their self ability in predicting the trend accurately that result in bad forecasting (Shefrin, 2000). 2.4 Investor s Personality Traits Psychographic factors play an important role in determining behavior of investors. These factors include gender, investor-life-cycle-stage, age, income and likewise. One of the important factors that play significant role in determining investor behavior is his or her personality (Sadi, Ghalibaf, Rostami, Gholipour, & Gholipour, 2011). Marilyn MacGruder Barnewall distinguished investors into two simple types to help investment advisors to understand the nature of their clients. These include Active Investors and Passive Investors. Passive investors are those who became passively without great efforts. They became wealthy by inheriting the wealth of their parents or by risking the capital of others rather than their own. In contrast Active investors are those who earned their own wealth by risking their own capital. Passive investors need high security while Active investors have more tolerance for risk (Barnewall, 1987). Bailard, Biehl and Kaiser (BB&K) developed Five-Way Model by adding more dimensions in Barnewall s model for better analysis of investor s personality. They classified investors along two dimensions: Level of confidence and Method of action. First dimension describes whether investor confidently approaches to different aspects of life or he or she is anxious in his approach. Second dimension describes whether investor is careful, methodical and analytical in his approach or he or she is impetuous, emotional and intuitive. Based on these two axes the authors identified five investor s personality types named as Adventure, Celebrity, Individualistic, Guardian and Straight Arrow (Bailard, Biehli, & Kaiser, 1986). Another popular psychographic model is the Myers-Briggs Type Indicator (MBTI) instrument test developed by Isabel Briggs Myers and her mother, Katherine Briggs. MBTI elaborated different personality types based on certain aspects of human psychology (Pompian & Longo, 2004). According to the theory every person has innate preferences that define how he or she will behave in a certain situation (Pittenger, 1993). Psychological as well as external factors can affect human behavior (Endler & Magnusson, 1976). Personality traits have significant affect on investor s behavior (Maital, Filer, & Simon, 1986). During 2000s Michael M. Pompian and John M. Longo used Myers-Briggs Type Indicator personality test and found that investors of different gender and personality types can COPY RIGHT 2012 Institute of Interdisciplinary Business Research 734

6 fall prey to various investment biases like overconfidence bias. They also suggested that investment advisors should consider gender and investor personality type as an important factor in client profiling and they should use these factors in creating investment programs that can minimize the ill effects of investment biases (Pompian & Longo, 2004). Huei-Wen Lin used big five model to examine the relationship between investor s personality traits and behavioral biases. According to him certain personality traits and demographics are significantly correlated. He found that neuroticism has positive relationship with disposition effect and herding while it has no relationship with overconfidence bias. Extroversion, openness and conscientiousness have positive relationship with disposition effect and overconfidence bias while it has no relationship with herding behavior. Finally agreeable were not susceptible to any behavioral bias (Lin, 2011). In another research Sadi, Ghalibaf, Rostami, and Gholipour correlate the behavioral biases with investor s personality traits in Tehran s Stock Market by using big five model of personality. Their findings showed that extroversion has positive relationship with hindsight bias and consciousness has negative relationship with randomness bias. There was a positive relationship between neuroticism and randomness bias, escalation of commitment & availability bias. Openness has positive relationship with hindsight bias and overconfidence bias while it has negative relationship with availability bias. Finally agreeableness has no relationship with any perceptual error. (Sadi, Ghalibaf, Rostami, Gholipour, & Gholipour, 2011). 3. Research Methodology The type of study was explanatory, the objective of which was to find out the relationship between investor s personality traits, demographics and overconfidence bias. Unit of analysis and unit of observation were individual. The study was cross sectional because the effect of independent variable had already taken place. 3.1 Target Population Target population was all individual investors associated with Lahore Stock Exchange (LSE). Sample size was 200 and all respondents were randomly selected from Lahore Stock Exchange (LSE). The sampling category was probability sampling and the unit of sampling was primary and it was single staged. 3.2 Data Collection Tool This study has used survey as a mode of observation and questionnaire was used as data collection tool. The questionnaire was divided into three sections as shown in Appendix 1. The COPY RIGHT 2012 Institute of Interdisciplinary Business Research 735

7 first section includes the questions related to demography of respondents in which gender, age, educational background and investment experience of investor were asked. The second section contains the questions used to measure overconfidence bias. These questions were taken from Michael M. Pompian s book Behavioral Finance & Wealth Management which is an internationally recognized book in the field of behavioral finance (Pompian, Behavioral Finance and Wealth Management, 2006). More ever the questions taken from this book were relevant easy to understand. The last section contained the questions for measuring investor s personality traits. Researchers have used various models for the measurement of investor s personality traits but this study has used Big Five Personality model because this is the most common used model now a days. The instrument for measuring personality traits was The Big Five Inventory (BFI) developed by John, Donahue, and Kentle (1991). There are 44 items in this inventory which was created using short phrases to facilitate efficient and flexible assessment of five dimensions as Short scales not only save testing time, but also avoid subject boredom and fatigue, there are subjects, from whom you won t get any response if the test looks too long (Burisch, 1984) (p.219) 3.3 Pilot Testing Before collecting actual data from target population pilot testing of questionnaire was done. The sample selected for pilot testing was having similar characteristics as target population. For this purpose 20 investors from Lahore Stock Exchange (LSE) were selected randomly. 3.4 Data Collection Procedure 200 questionnaires were distributed among the investors of Lahore Stock Exchange (LSE) and frequent reminders were sent to fill out these questionnaires. Out of 200 questionnaires 30 were discarded due to non serious or blank responses and remaining 170 questionnaires were used for data analysis. All data received through questionnaire was processed through Statistical Package for Social Sciences (SPSS) 19.0 and MS Excel Relevant statistics like t-test, Pearson s correlation test and Person s chi-square test were applied. 4. Research Findings And Interpretations To check normality of sample population, one sample Kolmogorov Smirnov test was applied as shown in Table 1 of Appendix 2. The Kolmogorov-Smirnov values for Openness, Consciousness, Extroversion, Agreeableness and Neuroticism were 1.049, 0.917, 1.077, COPY RIGHT 2012 Institute of Interdisciplinary Business Research 736

8 and at significance level greater than 0.01 or 0.05 respectively which means that sample population was normally distributed and parametric tests can be applied on this data. 4.1 Demographic Variables and Overconfidence Bias Table 2 shows the results of cross tabulation for demographic variables and overconfidence bias. Pearson Chi-Square test for independence was applied to check the association between these variables. The hypothesis formed to check the association between demographic variables and overconfidence bias is given below: Hypothesis 1: There is a relationship between Demographic variables and Overconfidence bias in Lahore Stock Exchange (LSE). The results showed that there is no significant relationship between age and overconfidence as the value Person s Chi-square was at of significance level, which mean that investor s level of age has no effect on overconfidence bias. Similarly the Person s Chi-square value for education and overconfidence bias is at of significance level, which means that education and overconfidence bias are independent and the level of education does not have any effect on overconfidence bias. Finally, the value of Person s Chi-square for investment experience and overconfidence bias is equal to at significance level of which means that there is significant association between investment experience and overconfidence bias. Hence the higher the level of investment experience, the greater the investor is overconfident. 4.2 Investor s Personality Traits and Overconfidence Bias Table 3 shows the results of Pearson s correlation between investor s personality traits and overconfidence bias. The hypothesis formed is given below: Hypothesis 2: There is a relationship between investor s personality traits and Overconfidence bias in Lahore Stock Exchange (LSE). The value of Pearson s correlation between openness and overconfidence bias is at of significance level which means that there is no correlation between openness and overconfidence bias. Pearson s correlation value between consciousness and overconfidence bias is.184 at of significance level which means that there is a positive relationship between consciousness and overconfidence bias. Hence the investors who are highly disciplined, organized, dutiful and responsible for their work can be susceptible to overconfidence bias. There is a positive correlation between extroversion and overconfidence bias as the value of Person s correlation is at of significance level. It means that the investors with COPY RIGHT 2012 Institute of Interdisciplinary Business Research 737

9 higher positive emotions, excitements, full of energy tend to be overconfident than others. Similarly a positive correlation was emerged between agreeableness and overconfidence as the value Person s correlation value at 0.05 of significance level is which means that investors who are friendly, kind, generous, helpful, who like to compromise and co-operate with others can have overconfidence bias. Lastly there was a negative correlation between neuroticism and overconfidence bias as the value of Person s correlation is equal to at 0.48 of significance level. Hence it was concluded that the investors, who are usually depressed, emotionally suffered, tensed and have worries are less overconfident than others. 5. Discussion The results of this study show that the value of correlation coefficient between consciousness and overconfidence bias is at significant level of Huei-Wen Lin also found same result using t-test where the value of t was 2.43 and the p value was less than 0.05 (Lin, 2011). Similarly, the value of correlation coefficient between extroversion and overconfidence is at the significance level of 0.42 which is less than Again, Huei-Wen concluded same result using t-test where the value of t was 2.36 at significant level less than 0.05 (Lin, 2011). In this research, no significant relationship is emerged between openness and overconfidence bias. In contrast Huei-Wen Lin found positive relationship between openness and overconfidence bias where the value of t was 2.82 at p value of less than 0.05 (Lin, 2011). Sadi and his coresearchers also found the same result as Lin in their research at Tehran stock market where positive correlation was emerged between openness and overconfidence bias. Here the value of correlation coefficient was at 0.05 significance level (Sadi, Ghalibaf, Rostami, Gholipour, & Gholipour, 2011). Similarly, the result of this study showed that there is a positive relationship between consciousness, extraversion, agreeableness and overconfidence bias and negative relationship between neuroticism and overconfidence bias. But these results were different from Sadi and his co-researchers where no relationship was emerged between these variables (Sadi, Ghalibaf, Rostami, Gholipour, & Gholipour, 2011). Similarly Huei-Wen Lin found no relationship between agreeableness and overconfidence (Lin, 2011). The result of this research showed that there is a negative relationship between neuroticism and overconfidence bias where the value of correlation is at significance level of In contrast, Huei-Wen Lin found no relationship between neuroticism and overconfidence bias COPY RIGHT 2012 Institute of Interdisciplinary Business Research 738

10 (Lin, 2011). Sadi and his co-researchers also found no relationship between these two variables (Sadi, Ghalibaf, Rostami, Gholipour, & Gholipour, 2011). The findings might be different due the demographical, cultural, social, and political differences across countries and other factors such as size of market and other economical factors that can significantly affect investors psyche (Masomi & Ghayekhloo, 2011) 6. Suggestion, Limitations and Recommendation for future work When investors behave irrationally, they may fall prey to different investment biases, one of which is overconfidence bias and hence they fail to achieve their investment objectives. It is suggested that investors should get the knowledge of these investment biases and should avoid them while making any investment decisions. Investors can also take help from Information Technology (IT) where they can use different tools and software packages to avoid these investment biases. Investor advisors should also help the investors in this regard and they should organize different training programs to minimize these biases. Investor advisors should also consider investment biases and personality traits as important factors in designing investment programs so that the desired investment objectives can be achieved. There are also some limitations for this research. This study could not be conducted on a very large scale due to the lack of resources and time, It was very difficult to locate large number of investors. To avoid this problem researcher also ed questionnaires to investors but they were not willing to respond. This research was conducted when stock market was in slump. The conditions of market can change from time to time so does the response of investors. This research has only focused on overconfidence bias while there are many other investment biases that are not considered in this research and these can be incorporated for further researches in future. This research has only considered investor s personality traits but other psychographic measures such as gender, marital status, saving behavior, income, and occupation can be considered for further researches. This research was based on cross sectional data while the response of the investors can be changed with the passage of time due to the difference in market conditions. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 739

11 References Bailard, Biehli, & Kaiser. (1986). Personal Money Management. Chicago: Science Research Associates Inc. Barber, B. M., & Odean, T. (2001). Boys will be Boys:Gender, Overconfidence, and Common Stock Investment. Graduate School of Management University of California, Davis. Barber, B., & Odeab, T. (1999). The Courage of Misguided. Financial Analysts Journal, Barberis, N., & Thaler, R. (2002). A SURVEY OF BEHAVIORAL FINANCE. NATIONAL BUREAU OF ECONOMIC RESEARCH. Barnewall, M. M. (1987). Psychological Characteristics of the Individual Investor. In W. Droms, Asset Allocation for the Individual Investor. Charlottsville: The Institute of Chartered Financial Analysts. Bernéus, H., Sandberg, C., & Wahlbeck, D. (2008). Behavioral Finance Investor s Rationality. Endler, & Magnusson. (1976). Toward an interactional psychology and personality. Psychol. Bul, Fama, E. F. (1969). Efficient Capital Markets: A Review of theory and Emperical Work. Journal of Finance, Hayat, M. A., Bukhari, K. S., & Ghufran, B. (2006). UNDERSTANDING INVESTMENT BEHAVIOR OF INDIVIDUAL INVESTORS: HOW THEY HANDLE INVESTMENT DECISIONS? DO THEY ACT RATIONALLY? Hirishleifer. (2001). Investor psychology and Asset Pricing. Journal of Finance. Investopedia. (n.d.). Behavioral Finance. Retrieved November 30, 2011, from Investopedia: John, O. P., & Srivastava, S. The Big-Five Trait Taxonomy:History, Measurement, and Theoretical Perspectives. In L. Pervin, & O. P. John, Handbook of personality: Theory and research. New York: Guilford (in press). Lin, H.-W. (2011). Elucidating the Influence of Demographics and Psychological Traits on Investment Biases. World Academy of Science, Engineering and Technology. Maital, Filer, & Simon. (1986). What do people bring to the stock market (beside money)? The Economic Psychology of Stock Market Behavior. In Gilad, & Kais, Handbook of Behavioral Economics Behavioral Macroeconomics (Vol. vol. B, pp ). Greenwich, Connecticut, JAI Press Inc. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 740

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13 Shefrin, H. (2000). Beyond Greed and Fear. Harvard Business School Press. Shiller, R. (2005). Irrational Exuberance. Prinetion University Press. Simon, H. (1955). A Behavioral Model of Rational Choice. Qurtetly Journal of Economices, Statman, M. (1995). Behavioral Finance Vs. Standard Finance. Behavioral finance and decision theory in investend management, Statman, M. (1992). Behavioral Finance: Past Battles and Future Engagement. Financial Analysts Journal. Thaler, R. H. (1999). Mental Accounting Matter. Journal of Behavioral, Tversky, A., & Kahneman, D. (1986). Rational Choice and the Framing of Decisions. Journal of Business, Wang, C., Sun, Q., & Chee, S. L. (2005, January). The Behavior and Performance of Individual Investors in China. Singapure. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 742

14 Appendix: 1 Questionnaire Dear respondent This research is being conducted by a Master s Student of the IBIT Punjab University Lahore, Pakistan to better understand the field of Behavioral Finance. You would be appreciated for completing this questionnaire and returning it to the researcher This Questionnaire will take approximately 10 to 15 minutes to complete. You don t need to disclose your identity while answering the questionnaire. Please be sure that your response will be held in strict confidence. Thank You!! Gender: Male Female Age (In years) less than or more Level of education: Below Matriculation Matriculation Intermediate Bachelor Masters or Above Investment Experience in Stocks: Less than 5 years 5-10 years years Above 20 years PLEASE SIGNIFY YOUR LEVEL OF AGREEMENT WITH THE FOLLOWING STATEMENTS ON THE SCALE RANGING FROM 5 TO 1 WHERE 5 REPRESENTS STRONGLY AGREE AND 1 REPRESENTS STRONGLY DISAGREE. No. I see Myself as Someone Who... Strongly Agree Neutral Disagree Strongly Agree Disagree 1. Is talkative Tends to find fault with others Does a thorough job Is depressed Is original, comes up with new ideas Is reserved Is helpful and unselfish with others COPY RIGHT 2012 Institute of Interdisciplinary Business Research 743

15 8. Can be somewhat careless Is relaxed, handles stress well Is curious about many different things Is full of energy Starts fighting with others Is a reliable worker Can be tensed Is clever, a deep thinker Is Passionate in nature Has a forgiving nature Tends to be disorganized Worries a lot Has an active imagination Tends to be quiet Is generally trusting Tends to be lazy Is emotionally stable, not easily upset Is inventive Has a self-confident personality Can be cold and unfriendly Work hard until the task is finished Can be moody Gives value to aesthetic experiences Is sometimes shy Is caring and kind to almost everyone Does things efficiently Remains calm in tense situations Likes routine work Is outgoing, sociable Is sometimes rude to others Makes plans and follows them COPY RIGHT 2012 Institute of Interdisciplinary Business Research 744

16 39. Gets nervous easily Likes to reflect, play with ideas Has few inventive interests Likes to cooperate with others Is easily distracted from work Seeks interest in art, music, or literature PLEASE SELECT ONE OPTION FROM THE QUESTIONS GIVEN BELOW. 1. Suppose that from 1960 to 2000, the annual return for equity investments was 10.4 percent. How much return could you earn if you invested during the same period? A. Below or equal to10.4 percent. B. Above 10.4 percent. 2. In your opinion how much control do you have in selecting investments that will outperform the market? A. Absolutely no control. B. Full control 3. Do you have complete knowledge of stock market? A. Yes B. No 4. Relative to other investors, how good investors are you? A. Below average B. Above average 5. My past investment successes were only due to my own specific skills only? A. Yes B. No COPY RIGHT 2012 Institute of Interdisciplinary Business Research 745

17 Appendix: 2 Table 1: One-Sample Kolmogorov-Smirnov Test Openness Consciousness Extroversion Agreeableness Neuroticism N Normal Mean Parameters (a,b) Std. Deviation Most Absolute Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymp. Sig. (2-tailed) a Test distribution is Normal. b Calculated from data Table 2: Chi-Square between Demographic Variables and Overconfidence Bias Demographic Variables Pearson Chi-Square Df Value Gender Age Education Investment Experience * *Significant Relationship Exists Overconfidence Bias Significance Level Table 3: Correlation between Investor s Personality Traits and Overconfidence bias Investor s Personality Trait Correlation Coefficient ( r ) Significance Level ( α ) Correlation Exists or Not Openness No Correlation Exits Overconfidence Consciousness.184*.017 Positive Correlation Bias Extraversion.156*.042 Positive Correlation Agreeableness.183*.017 Positive Correlation Neuroticism -.152*.048 Negative Correlation *Significant Relationship Exists COPY RIGHT 2012 Institute of Interdisciplinary Business Research 746