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INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS

COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 730

OCTOBER 2012

VOL 4, NO 6

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

Muhammad Zubair Tauni

Graduate Student of MBIT (Specialization in Finance) Session 2008-2012

Institute of Business & Information Technology (IBIT)

University of the Punjab, Quaid-e-Azam Campus, Lahore, Pakistan

Abstract

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).

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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.

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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

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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

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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

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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

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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 2007. 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, 1.045

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and 0.898 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 1.714 at 0.424 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 1.306 at 0.860 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 17.561 at significance level of 0.001 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 -0.023 at 0.762

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 0.017 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 0.156 at 0.042 of significance level. It means that the investors with

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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 0.170 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 -0.152 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 0.184 at significant level of 0.17. 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 0.156

at the significance level of 0.42 which is less than 0.05. 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 co-

researchers 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 0.441 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 -0.23 at significance level of 0.48. In

contrast, Huei-Wen Lin found no relationship between neuroticism and overconfidence bias

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(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 e-mailed 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.

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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 30

30 - 50

50 or more

Level of education: Below Matriculation

Matriculation

Intermediate

Bachelor

Masters or Above

Investment Experience in

Stocks: Less than 5 years

5- 10 years

10- 20 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

Agree Neutral Disagree Strongly

Disagree

1. Is talkative 5 4 3 2 1

2. Tends to find fault with others 5 4 3 2 1

3. Does a thorough job 5 4 3 2 1

4. Is depressed 5 4 3 2 1

5. Is original, comes up with new ideas 5 4 3 2 1

6. Is reserved 5 4 3 2 1

7. Is helpful and unselfish with others 5 4 3 2 1

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8. Can be somewhat careless 5 4 3 2 1

9. Is relaxed, handles stress well 5 4 3 2 1

10. Is curious about many different things 5 4 3 2 1

11. Is full of energy 5 4 3 2 1

12. Starts fighting with others 5 4 3 2 1

13. Is a reliable worker 5 4 3 2 1

14. Can be tensed 5 4 3 2 1

15. Is clever, a deep thinker 5 4 3 2 1

16. Is Passionate in nature 5 4 3 2 1

17. Has a forgiving nature 5 4 3 2 1

18. Tends to be disorganized 5 4 3 2 1

19. Worries a lot 5 4 3 2 1

20. Has an active imagination 5 4 3 2 1

21. Tends to be quiet 5 4 3 2 1

22. Is generally trusting 5 4 3 2 1

23. Tends to be lazy 5 4 3 2 1

24. Is emotionally stable, not easily upset 5 4 3 2 1

25. Is inventive 5 4 3 2 1

26. Has a self-confident personality 5 4 3 2 1

27. Can be cold and unfriendly 5 4 3 2 1

28. Work hard until the task is finished 5 4 3 2 1

29. Can be moody 5 4 3 2 1

30. Gives value to aesthetic experiences 5 4 3 2 1

31. Is sometimes shy 5 4 3 2 1

32. Is caring and kind to almost everyone 5 4 3 2 1

33. Does things efficiently 5 4 3 2 1

34. Remains calm in tense situations 5 4 3 2 1

35. Likes routine work 5 4 3 2 1

36. Is outgoing, sociable 5 4 3 2 1

37. Is sometimes rude to others 5 4 3 2 1

38. Makes plans and follows them 5 4 3 2 1

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OCTOBER 2012

VOL 4, NO 6

39. Gets nervous easily 5 4 3 2 1

40. Likes to reflect, play with ideas 5 4 3 2 1

41. Has few inventive interests 5 4 3 2 1

42. Likes to cooperate with others 5 4 3 2 1

43. Is easily distracted from work 5 4 3 2 1

44. Seeks interest in art, music, or literature 5 4 3 2 1

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

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OCTOBER 2012

VOL 4, NO 6

Appendix: 2

Table 1: One-Sample Kolmogorov-Smirnov Test

Openness Consciousness Extroversion Agreeableness Neuroticism

N 170 170 170 170 170

Normal

Parameters

(a,b)

Mean

3.5813 3.9536 3.4750 3.8327 2.6816

Std.

Deviation .42437 .57445 .52040 .49855 .62494

Most

Extreme

Differences

Absolute

.080 .070 .083 .080 .069

Positive .060 .056 .063 .043 .063

Negative -.080 -.070 -.083 -.080 -.069

Kolmogorov-Smirnov Z 1.049 .917 1.077 1.045 .898

Asymp. Sig. (2-tailed) .221 .370 .196 .224 .395

a Test distribution is Normal.

b Calculated from data

Table 2: Chi-Square between Demographic Variables and Overconfidence Bias

Overconfidence

Bias

Demographic Variables Pearson Chi-Square

Value

Df Significance

Level

Gender - - -

Age 1.714 2 .424

Education 1.306 4 .860

Investment Experience 17.561* 3 .001

*Significant Relationship Exists

Table 3: Correlation between Investor’s Personality Traits and Overconfidence bias

Overconfidence

Bias

Investor’s

Personality Trait

Correlation

Coefficient ( r )

Significance

Level ( α )

Correlation Exists or

Not

Openness -0.23 .762 No Correlation Exits

Consciousness .184* .017 Positive Correlation

Extraversion .156* .042 Positive Correlation

Agreeableness .183* .017 Positive Correlation

Neuroticism -.152* .048 Negative Correlation

*Significant Relationship Exists

ijcrb.webs.com O INTERDISCIPLINARY JOURNAL F O ... · economics is a simple model of human behavior stated that humans are perfectly rational in their economic decisions (Simon, 1955).

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