Are Individual Investors Really Overconfident?

A survey on Taiwan Stock Market

Min-Hua Kuo

Associate Professor, Department of Finance, Shih Hsin University, Taiwanmhkuo@cc.shu.edu.tw

6F, No. 111, Sec. 1, MuCha Rd. Taipei, Taiwan, ROC.TEL: 886-2-22368225 ext6 3435

Nai-Fong Kuo

Associate Professor, Department of Finance, Shih Hsin University, Taiwankkkuuu@cc.shu.edu.tw

6F, No. 111, Lane 17, Sec. 1, MuCha Rd. Taipei, Taiwan, ROC.TEL: 886-2-22368225 ext 63431

Ming-Yau Zhang

Student, Department of Finance, Shih Hsin University, Taiwan

6F, No. 111, Sec. 1, MuCha Rd. Taipei, Taiwan, ROC.TEL: 886-2-22368225 ext 63435

Are Individual Investors Really Overconfident?

A survey on Taiwan Stock Market

Abstract

The idea of human beings are overconfident has earned quite a concordance in the

emerging studies of Behavioral Finance over the past few years. Many scholars find

some anomalies, such as the fact of over-trading, can be explained satisfactorily and

conveniently with the reason of overconfidence. It causes little doubt when one hears

the suggestion that investors are overconfident. However, we may have a second

thought if think it carefully. Investment is highly complicated, filled with uncertainly

and gives quick feedback, is it not more likely that the investors will feel under

confident, instead of overconfident, to win over this game? In this study we present

evidences to show that investors do reveal the disposition of overconfidence in

general cases, however, they turn into diffidence in the situation of investment.

Moreover, we find no consistent evidence to support the argument of overconfidence

leading to overtrading. The trading frequency has nothing to do with confidence.

Whether people tend to over confide seems to depend on, at least partly, the

scenario’s feature. When facing a situation of great uncertainty and complication,

people tend to be under-confident, instead of overconfident. The analysis is based on a

nationwide survey on individual investors in Taiwan stock market. The sampling error

is lower than 3%.

Introduction

That people are inclined to be overconfident has earned quite a concordance in the

fields of Psychology and Behavioral Finance. The measurements of overconfidence

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used in Psychology are multifold, including interview and experiments. The way to

claim confidence in the Behavioral Finance, however, is of indirection. It does not

offer evidences to “prove” that people are overconfident, instead, it borrows this

popular belief to explain why investors over trade. Take the examples of the eminent

series of paper authored by Odean and Barber, among others. They explore

individuals’ investment behaviors by the use of a stock broker’s client accounts. One

of their main suggestions, besides many other valuable insights, is that overconfidence

leads investors to overtrading when they find that overtrading is hazardous to the

investment returns. Male investors trade more frequently than female because they are

more overconfident than female. It causes little doubt when one hears the suggestion

that investors are overconfident, maybe because we are subject to the anchoring effect

(anchored by the popular belief that people are always overconfident) or because most

of us do have the similar experience in daily life. However, we may have a second

thought if think it carefully. Investment is such a knowledge intensive activity and

filled with uncertainly, and feedbacks fast, is it not more likely that the investors will

feel under confident, instead of overconfident, to win over this game? With the fact

that so many potential causes could make an investor trade more (such as investment

strategies, liquidity needs, portfolio balance, or the individual’s personality of

inner/outer control, etc.), what is the solid grounds allowing us to claim that

overconfidence, in stead of diffidence or fear, makes people move? A more refined

research into investors’ attitudes is needed before we are entitled to make any claim

about their over (or under) confidence.

We utilize the national databank of the Investor Sentiment Index in Taiwan made by

Shih Hsin University. It is a nationwide bimonthly survey of the individual stock

investors in Taiwan, with sampling error kept below 3%. In the study, a delicately

2

designed question set is asked to distinguish the self-confidence in different situations.

We endeavor to answer the questions: Are investors really overconfident? Does the

self-confidence vary over different domains (such as in the general situation vs. in the

investment scenario)? Is it appropriate to claim overconfidence by overtrading?

According to our analysis, investors do show the disposition of overconfidence in

general cases, however, they turn into diffidence regarding investment. Moreover,

we find no consistent evidence to support that overconfidence leads to overtrading.

The trading frequency has nothing to do with confidence. Whether people tend to over

confide may depend on the scenario’s feature. When facing a situation of great

uncertainty and complication, people tend to be under-confident, instead of

overconfident.

The article structure is arranged as follows: The first section is introduction,

introducing the research background and the gap remains to fill. Then literature

review follows. The third and fourth sections explain respectively the methodology in

use and the empirical results. Conclusions come in the final section and the

implication of the research is discussed there too.

Literature review

Following the emergence and rapid development of Behavioral Finance, the roles of

inner attitudes have earned great attention. Among them, overconfidence is probably

the one discussed most and debated least [see Thaler, 1995; De Bondt and

Thaler,1990; Daniel, Hirshleifer, Subrahmanyan, 1998; Gervais and Odean, 1998; De

Long, 1993; De Bondt, 1993; Kahneman and Riepe, 1998, etc.]. Most people do show

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overconfident about their own relative abilities, and unreasonably optimistic about

their futures, according to the psychological and experimental economics studies.

When assessing almost any positive traits, a vast majority of people believe they are

above the average, although only half can be (if the trait is symmetrically distributed).

That is, people seem to believe they are more skillful than they really are [e.g.,

Svenson, 1981; Weinstein, 1980; Taylor and Brown, 1988; Lichtenstein, Fischhoff

and Philips, 1982]. By questionnaire survey, Lichtenstein, Fischhoff and Philips

[1982] find that people very often overestimate the probability of correctness of their

answers. even when they are “sure” their answers are correct, as high as 20% of them

are actually wrong. Using games of skill, Camerer and Lovallo [1999] report on

overconfidence in business entry decisions. Asubel [1991] analyzes market data and

indicates that the credit card holders being overconfident about their future ability to

avoid overdrawn accounts. The evidence of overconfidence is abundant.

As for the relation between overconfidence and investment behavior, some

researchers attempt to build theoretical models and others do empirical analysis. For

the former, Daniel, Hirshleifer and Subrahmanyam [1998] propose that individual

investors are overconfident when they overestimate the correctness of their private

information. Odean [1998] proposes a static model and shows that the overconfidence

of investors raises both market trading volume and price volatility, and thus expected

utility are reduced and unnecessary social loss are brought about. When the investors

over estimate the precision of their private information, they tend to overact; the

prices will not back to the equilibrium until the reality reveals. Therefore the market

price volatility and long-term returns are negative related.

Regarding the empirical studies, most papers infer investors to be overconfident

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because the obvious fact of over-trading and the associate negative effects on returns.

For example, Barber and Odean [1999] find that individual investors trade much more

than expected and they suggest it is due to traders’ overconfidence. They also

investigate the trading data from 166 investment clubs in 1991-1997, and find the

investors not only trade very often but prefer high-risk small firms [Barber and

Odean, 2000a]. The returns they get seem not very satisfactory: 60% of them are

below the market average, which the authors believe at least partly thanks to

overconfidence. Furthermore, they examine 35,000 trading accounts from a national

security broker and report that the average turnover of male is higher than female,

causing male’s investment returns less by 2.65% than the gross returns, more than that

of 1.72% of female. Again, the authors suggest it is because male is more

overconfident than female [Barber and Odean, 2000b; Barber and Odean, 2001].

Statman and Thorley [1999] propose that high returns cause overconfidence, which

leads to over-trading, and, it interacts further with disposition effect, bringing about

the Disposition- Overconfidence effect. That is, high volumes are related with the

high returns weeks or months ago, while low volumes with high volatilities weeks or

months ago. Chuang and Lee [2006] build up VAR and GARCH models to propose

that overconfident investors over act on private information but under act on public

information. The overconfident investors trade too much and which leads to over-

volatility: the overconfident investors apt to under estimate risk and thus trade too

much on the risky securities. They are even more overconfident after making profits

and then trade furthermore, in accordance with what Statman and Thorley [1999]

report. Still, Bengtsson [2005] make use of questionnaire to investigate the students of

Stockholm University and compare the optimism and confidence between male and

female. They find that male are more optimistic and confident than female.

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Similar approaches and conclusions are also found in studies on Taiwan market. For

example, Shu, Chiu, Chen, and Yeh [2004] reach the same conclusion on individual

investors as Barber and Odean’s by analyzing the investors’ trading accounts from a

local stock broker in Taiwan.

On the other hand, to the contrary of the viewpoint of seeing overconfidence as

mental bias, some scholars consider the overconfidence to be a natural result of

rational expectation. For example, Hvide [2002] uses a game model incorporating

pragmatic beliefs to explain overconfidence and find that the equilibrium solutions

locate on the region of overconfidence.

We summarize the foregoing findings in literature. With the solid consensus in

Psychology that human tend to be over confident, it seems to be a natural and rational

inference that investors are overconfident, when the significant fact of over trading in

stock market are repeatedly shown [such as Barber and Odean, 1999; Statman and

Thorley, 1999; Shu, et al., 2004, etc.]. However, there are many potential causes could

lead to over trading, such as market atmosphere, unexpected shocks, and liquidity

demand, etc. The suggestion of overconfidence leading to overtrading is not very

much grounded. Both greedy and fear could drive people overtrading. When one fears

or lacks confidence, he/she may prefer quickly close the risk embedded in holding

stocks and thus trade frequently. It may be more likely that fear or diffidence, instead

of overconfidence, dominates individual investors when the situations are highly

uncertained. To claim whether investors are over (under) confident, we need a more

refined research into individuals’ attitudes. This study aims at contrasting the

confidence status when one faces a general situation or an investment condition; the

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latter is known for its complication and uncertainty. Questionnaire survey offers a

more direct measurement on attitudes and is suitable for many issues in the field of

Behavioral Finance [see Shiller et al., 1996; Lenney, 1977; Beyer and Bowden, 1997;

Bengtsson, 2005, etc.].

Methodology

The methodology of questionnaire survey used in this study will be reported as

follows, including the process of sampling, the questions set designed and the analysis

approaches.

1. The data

We use the databank of SHU Sentimental Index, a bimonthly nationwide survey

interviewed through telephone by Opinion Survey Center of Shih Hsin University,

Taiwan. The survey is implemented by a professional group composed of the

professionals of behavioral Finance, psychology and opinion survey. The survey

comprises two main parts: the optimum attitudes toward near future and behavioral

financial issues. The former is a given set of questions similar with those of UBS

Optimism Survey in USA and EU-5, and regularly asked each time to construct the

Sentimental Index for Taiwanese stock market; the latter covers various topics

regarding investment behaviors and attitudes and consists of different questions each

time, depending on the specific issues investigated. The subjects are targeted on the

individual stock investors in Taiwan, that is, the individuals of older than 18 and

having made stock transactions during the past one year. To control the sampling

error no more than 3% with the confidence level of 95%, at least 1068 effective

samples are accomplished each time. The sample number in each district is decided

by weighted sampling. The weight is determined by the proportion of the number of

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security houses in each district over total security houses. That is, more security

houses (more intensive investment) are in a district, more subjects are sampled out

from there. For this study, the survey was made on August, 2005.

2. The question set designed

A delicately designed question set is asked to distinguish the self-confidence status in

different scenarios. Well explain the relevant questions asked in the questionnaire one

by one in this section.

(1) Overconfidence

In order to explore whether the extent of overconfidence varies in different domains,

three questions are queried. To avoid confounding, these questions are spread out in

questionnaire. The first question is about the confidence in general situation,

borrowed from the well structured query pattern used in Psychology when measuring

overconfidence. We use it to serve as a benchmark to make further comparisons. The

other two questions are related to the scenario of investment. One is to ask the

subjects about their subjectively perceived investment performance in comparison

with their peers; the other is to ask whether they have the confidence of beating the

market—comparing their investment performance with the market as a whole. Two

aims are to attain. First, whether the confidence status is different when one faces

different situations. For example, one may reveal significant overconfidence in the

general conditions while exhibit diffidence when facing investment. Second, whether

the confidence statuses in investment are different when comparing with different

benchmarks. For instance, one may be inclined to overconfidence when facing the

peers, while tend to diffidence when referred to the whole market if they believe that

beating the market as a whole is very difficult as the efficient market hypotheses

imply. The three questions are explained respectively as follows.

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Question 1: the overconfidence in the general situations

Suppose that you are related to a group of people who have a similar

background and social status with you. In a general case, when compared

with them, you will most probably feel that you are ________

( 01) better than the average.

( 02) about the same.

( 03) not as good as the average.

( 97) No idea. / No comments.

( 98) Refuse to answer

According to the typical judging criterion used in Psychology: if the proportion

answering “better than the average” is significant higher than that of “not as good as

the average”, then the investors are claimed to be overconfident in the general cases.

Question 2: the overconfidence in investment performance related with peer

Comparing with the investors you acquainted, you believe your investment

performance is _________

(The answer options are the same as Question 1)

Question 3: the overconfidence in investment performance related with the market as

a whole

Considering the coming three months, do you have confidence in beating the

market as a whole?

（01）Yes, very much.

（02）Yes. I have some confidence.

（03）No. I am not quite confident.

（04）No. I have no confidence at all.

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( 97) No idea. / No comments.

( 98) Refuse to answer

For the second and third questions, if the proportions answering “better than the

average” or “yes” are higher than those of “not as good as the average” or “no”, then

the investors are claimed to be overconfident in investment in comparison with the

peers/the market.

(2) Trading turnover

The investment turnover represents investors' frequency of trading. According to

Odean (1998) and many other scholars, when investors are overconfident, they are

inclined to overtrade, leading to lower returns. This research will explore this issue by

observing confidence in different areas. The question regarding trading frequency is

as follows:

Q: Averagely speaking, how many times do you trade stocks per month? ________

If the subjects answer with “No idea./No comments” or refuse to answer, they are

excluded from the analysis.

3. Analysis process

With the data collected, we first report the sample distributions of various variables.

From the distributions of confidence in different situations, we will be entitled to

discuss whether individuals are apt to be overconfident in each situation. Then, we

will analyze the relationships between trading turnover and self-confidence through

test and the tests of inter-group differences in average and median turnover.

Empirical results

1. Sample structures

There are 1,088 samples effectively interviewed in this survey. They are equally

10

distributed in gender; a great of subjects are aging around 40~59 (accounting for

57.6%), having bachelor degrees or above (40.0%), and mostly belonging to middle-

income class with yearly income between NT$200,000 and NT$1,000,000.

(insert Exhibit 1 here)

2. The distributions of self-confidence

(1) Self-confidence in general conditions

When related to the peers with similar backgrounds and social status, most subjects

interviewed consider themselves as “about the same” (69.6%). This high proportion

agrees with the Doctrine of the Mean in Chinese tradition and culture. (According to

the Confucian school in Chinese culture, one should behave and think in the road of

middle, not too high, not to low; not too right, not too left.) What is more valuable

here to mention is that those who self-perceive “better than average” are much more

than those “not as good as the average”, with the proportion of 22.1% versus 8.3%.

This evidence lends a support to the argument of overconfidence. That is, generally

speaking, people are inclined to be overconfident in a general case, in accordance with

the general belief.

(insert Exhibit 2 here)

(2) Self-confidence in investment

The ratios in exhibit 2 show that, in agreement with the above case of general

situations, the majority of investors in Taiwan stock market also view themselves

“about the same” (46.3%). However, to the contrary of the general conditions above

stated, 28.1% of investors interviewed consider themselves “not as good as the

average”, greater than those “better than the average” by 2.5%. It represents that

investors as a whole do not demonstrate significant overconfidence in terms of the

relative investment performance perceived when comparing with peers.

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As for the confidence of beating the market, the subjects answering “no” accounts for

69.9%. That is, nearly 70% of individual investors are diffident or under-confident,

instead of overconfident. According to exhibit 3, the investors do not show significant

evidences on overconfidence, whether it is compared with the peers or the market as a

whole.

(insert Exhibit 3 here)

(3) Cross distributions of self-confidence in general conditions and investment

According to exhibit 2, only 22% of individual investors believe themselves better

than others, while as high as 70% consider themselves “ordinary”(about the average

level). From exhibit 5 we find that the attitudes toward oneself are pretty consistent

for those having confidence and lacking confidence. For example, most subjects who

feel better than (not as good as) others in general cases also tend to feel better (not as

good as others) in investment. However, for those 546 people self-perceiving as

average, only half of them (279) also perceive their investment performance as about

the same as the peer average, around 30% of them (164) believe their performance not

as good as the peer average; only 19% believing themselves better than peers in

investment. In other words, 30% of the self-perceived “mediocre” people in a general

case turn out to be diffident in investment. Likewise, in the group of self-perceiving

better than others in general conditions there is only 45% of them believe themselves

to be able to beat the market. More importantly, 73% of those who view themselves as

average in general cases feel they cannot beat the market. Or from the other

perspective, whether or not the investors are confident to beat the market, most of

them feel better than others in general situations. In a word, one’s self-confidence is

different in different domains. While it is not clear which is more difficult: to beat the

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market or to beat the peers; it is very obvious that subjects do not demonstrate any

significant self-confidence when referring to investment.

(insert exhibit 4 here)

We list the sample numbers in each cell of the 18 combinations (3×3×2) in exhibit 5.

It shows that more investors belonging to the combination of "no×worse" (no

confidence in beating the market and investment performance worse than peers) than

the combination of “yes×better"; they account for 24% and 14% of all effective

samples respectively. The ones lacking confidence are more than the ones having

confidence in investment.

(insert exhibits 5 and 6 here)

In summary of the analysis above, the patterns show that investors do tend to be

overconfident in general cases, but under-confident in investment, whether it is related

to the market or the peers. We reckon several potential reasons. First, investment is a

highly complex activity; winning over the average is not considered an easy job.

Second, the investment performance is subject to objective numbers, instead of

subjective evaluation; and the feedback is hard and fast, leaving little space for

individuals to build up confidence through mentality build-up. The third, the lacking

of confidence may thank to the bear market around the timing of survey. The

databank allows us to check the last possibility because it includes the Question 3

many times, covering both bear and bull market. We find the proportion of being

confident of beating the market is around 35% and never greater than 40%. In a word,

even during a high market, investors tend to be diffident.

3. Self-confidence vs. demographic variables: Chi-square test

Regarding the relationships between self-confidence and demographic variables, we

find that education and income are significantly related with self-confidence. The

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subjects of highly educated and high income are more confident of themselves (see

table 6). What is worthy of noting here is the issue of gender. From the abundant

literature, male is reported more overconfident than female. According to our survey,

however, there is no significant difference between male and female when the

question asked are about the general situations. The percentages of feeling better vs.

feeling worse are 23.0% vs. 9.2% for male, and 20.0% vs. 7.9% for female. Both are

overconfident. On the other hand, male do show more overconfident in investment

than female. For those who answer “better than their peer” and those who answer

“able to beat the market”, male accounts for more than 60%. For those who answer

“worse than their peer” and those who answer “unable to beat the market”, female

accounts for 62.0% and 56.1% respectively. Both p-values of the Chi-square statistics

are 0.000. In a word, in general situations, both genders demonstrate overconfident.

However, in terms of investment, male individuals show significantly more

overconfident; female tend to be under-confident.

4. Self-confidence vs. trading turnover

Finally we will analyze whether the trading turnover is positively related with self-

confidence, in accordance with the findings in literature, so as to judge whether it is

appropriate to suggest that overconfidence is at least one of the reasons leading to

overtrading.

(1) Independence test

According to the independence test, we find that when the subjects are referred to

general cases or to beating the stock market, confidence is not significantly related to

trading turnover. That is, whether the subjects are confident of themselves or not, their

trading frequencies are about the same. But in observing this relationship in terms of

the investment performance compared with peers, we get a Chi-square statistics

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reaching the 5% significant level. More than half of those who believe themselves

having behaved better than the peers trade more than 6 times per month averagely

(52.6%), and 42.5% of those perceiving worse than peers trade above 6 times per

month (see exhibit 8). However, the differences over groups classified by confidence

are trivial (see exhibit 9).

(insert exhibits 7 and 8 here)

(2) The group differences of trading frequencies

The trading frequency distribution is not linear in terms of the general confidence—

the ones who self-perceiving as average trade the least (see exhibit 9). In turn, the

distribution seems to be linear in terms of the investment related to peers: the

confident group trade most and the diffident group trade least, but the group

differences are not statistically significant; all p-values are greater than 10% (see table

9). As for the case related to market as a whole, test results seem to be complicated.

The patterns for average and median are opposite. The frequency average of the group

of “able to beat the market” is less than the group of “unable to beat the market”, but

its frequency median is greater (see exhibit 11). This implies that some of the

investors who feel “unable to beat the market” are extremely active in stock market,

leading to a asymmetrical distribution.

From the findings above, the group difference tests do not consistently support any

significant relationships between confidence and trading frequency. That is, the

average (and median) trading turnover in the group of having confidence in

investment performance related to peers is not significantly different from that in the

group of lacking confidence. In the investment confidence related with market, the

average frequency is even lower in the group of having confidence, contrary to the

argument of most previous paper. Therefore, the viewpoint of overconfidence leading

15

to over-trading is not supported here.

(insert exhibit 10, 11 here)

Conclusions

Using a nationwide survey in Taiwan stock market, we demonstrate that the individual

investors tend to be diffident in investment, although they are overconfident in general

cases. This could be due to the great uncertainty and highly complication embedded in

investment, which makes investors feel very difficulty to win over others. The

confidence differs in different areas. In addition, we find the trading turnover is not

related to confidence. Not any significant evidence supports that overconfidence

leading to over-trading. Furthermore, both male and female are overconfident in

general cases, but female tend to lack confidence in investment. Male is more

overconfident than female in investment.

References

Asubel, L. M., 1991, The Failure of Competition in the Credit Card Market, American

Economic Review 81, 50-81.

Barber, Brad M. and T. Odean, 1999, The Courage of Misguided Convictions,

Financial Analyst Journal 55 (6), Nov/Dec, 41-55.

Barber, Brad M. and T. Odean, 2000, Trading is Hazardous to Your Wealth: The

Common Stock Investment Performance of Individual”, Journal of Finance 105

(2), 773-806.

Barber, Brad M. and T. Odean, 2001, Boy will be boys: Gender, overconfidence and

common stock investment, Quarterly Journal of Economics 116 (1), 261-292.

Camerer, C. and D. Lovallo, 1999, Overconfidence and Excess Entry: An

16

Experimental Approach, American Economic Review 89, 306-318.

Chou, B. H., S. S. Tsr, G. N. Chow, and Y. L. Gong, 2002, Behavioral Finance:

Literature Review and Perspectives, Security Market Development, 54, 1-48. (in

Chinese)

Chuang, Wen-I and Bong-Soo Lee, 2006, An Empirical Evaluation of the

Overconfidence Hypothesis, Journal of Banking and Finance (forthcoming).

Daniel, Kent D., David Hirshleifer, and Avanidhar Subrahmanyam, 1998, Investor

Psychology and Security Market Under and Overreactions, Journal of Finance

53, 1839-1885.

De Bondt, W.M.F. and Richard Thaler, 1995, Financial Decision-making In Markets

and Firms : A Behavioral Perspective, In Robert A. Jarrow, V. Maksimovic,

and W.Z. Ziemba, ed.: Finance, Handbooks in Operations Research and

Management Science 9, 385-410.

De Bondt, Werner F.M. and Richard Thaler, 1985, Does the Stock Market Overreact?

Journal of Finance 40, 793-905.

Gervais, S. and T. Odean, 1999, Learning to Be Overconfidence, working paper,

Wharton School, University of Pennsylvania.

Hvide, Hans K., 2002, Pragmatic Beliefs and Overconfidence, Journal of Economic

Behavior and Organization 48 (1), May, 15-28.

Kahneman, Daniel and Mark W. Riepe, 1998, Aspects of Investor Psychology,

Journal of Portfolio Management 24(4), 52-65.

Kent, Daniel, David Hirshleifer and Avanidhar Subrahmanyam, 1998, A Theory of

Over-confidence, Self-attribution and Security Market over and under

Rreactions, Journal of Finance 53 (5), 1839-1886.

Lichten, S., B. Fischhhoff and L.D. Phillips, 1982, Calibration of Probability: The

17

state of the art to 1980, In Kahneman, D. and A. Tversky (Eds.), Judgment

under Uncertainty: Heuristics and Bias, 306-334, Cambridge University Press.

Odean, T., 1998, Volume, Volatility, Price, and Profit when all Traders Are above

Average, The Journal of Finance 53, 1887-1935.

Shu, Pei-Gi, Yin-Hua Yeh, Shean-Bii Chiu, Hsuan-Chi Chen, 2005, Are Taiwanese

Individual Investors Reluctant to Realize Their Losses? Pacific-Basin Finance

Journal 13 (2), Mar, 201-223.

Statman, M., S. Thorley, and K. Vorkink, 2004, Investor Overconfidence and Trading

Volume, working paper.

Svensson, O., 1981, Are We All Less Risky and More Skillful than Our Fellow

Drivers? Acta Psychologica 47, 143-48.

Taylor, Shelly E. and J. D. Brown, 1988, Illusion and Well-Being: A Social

Psychological Perspective on Mental Health, Psychological Bulletin 103(2)

193-210.

Weinstein, Neil D., 1980, Unrealistic Optimism about Future Life Events, Journal of

Personality and Social Psychology 59(5), 806-20.

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Exhibit 1 sample structure

Variables samples % Variables samples %

gender

Male 525 48.0 Education* Low 373 34.5

Female 569 52.0 Middle 272 25.1

Total 1094 100 High 437 40.4

age

<= 29 97 8.9 Total 1082 100

30~39 263 24.2 income Low 243 25.6

40~49 334 30.7 Middle 532 56.0

50~59 293 26.9 high 175 18.4

>= 60 101 9.3 total 950 100

total 1088 100*The education of low: senior high school or lower, middle: college, high: bachelor or above.

Exhibit 2 The distribution of self-confidence in general conditions

Self-confidence Samples %

“better than average” 173 22.1%

“about the same” 546 69.6%

“not as good as the average” 65 8.3%

total 784 100.0%

Exhibit 3 Self-confidence in investment

Self-confidence Samples %

You believe your investment performance is…

“better than average” 201 25.6%

“about the same” 363 46.3%

“not as good as the average” 220 28.1%

total 784 100%

Do you have confidence in beating the market as a whole?

Yes 236 30.1%

No 548 69.9%

Total 784 100%

Exhibit 4 The distribution of self-confidence in different situations

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Exhibit 5 Cross distributions of self-confidence in general conditions and investment

Self-confidence in general situations

Confidence in investing performance

better average worse total

better samples 92 103 6 201% 53.18% 18.86% 9.23% 25.64%

average sample 67 279 17 363

% 38.73% 51.10% 26.15% 46.30%

worse sample 14 164 42 220

% 8.09% 30.04% 64.62% 28.06%

total sample 173 546 65 784

% 100.00% 100.00% 100.00% 100.00%

Confidence in beating market

better average worse total

yes samples 77 148 11 236% 44.51% 27.11% 16.92% 30.10%

no sample 96 398 54 548

% 55.49% 72.89% 83.08% 69.90%

total sample 173 546 65 784

% 100.00% 100.00% 100.00% 100.00%

Exhibit 6 Cross distributions on the confidence of three situations 　

Beating the market? Return (vs. peers) General cases 　 　

better average worse Total %

yes

Better 54 51 5 110 14.0

average 20 76 2 98 12.5

worse 3 21 4 28 3.6

no

Better 38 52 1 91 11.6

average 47 203 15 265 33.8

worse 11 143 38 192 24.5

　 total 173 546 65 784 100.0

20

Exhbit 7 Self-confidence and demographic variables: dependence test

Confidence in investing performance

Conf. in beating market Self-confidence in general situations

variavbles better average worse total yes no total better average worse total

gend

er

malesample 151 202 97 450 172 305 477 110 324 44 478

% 64.30% 48.40% 38.00% 49.60% 60.10% 43.90% 48.70% 51.90% 46.90% 52.40% 48.40%

femalesample 84 215 158 457 114 389 503 102 367 40 509

% 35.70% 51.60% 62.00% 50.40% 39.90% 56.10% 51.30% 48.10% 53.10% 47.60% 51.60%

totalsample 235 417 255 907 286 694 980 212 691 84 987

% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

2 (P-value) 34.048(0.000)**

*21.255

(0.000)***

2.197 (0.333)

age

<=29samples 26 36 26 88 37 52 89 20 66 10 96

% 11.20% 8.60% 10.20% 9.70% 13.00% 7.50% 9.10% 9.50% 9.60% 12.00% 9.80%

30~39sample 49 109 66 224 67 176 243 39 189 17 245

% 21.00% 26.10% 25.90% 24.80% 23.50% 25.50% 24.90% 18.50% 27.40% 20.50% 24.90%

40~49sample 77 134 78 289 78 227 305 77 212 21 310

% 33.00% 32.10% 30.60% 31.90% 27.40% 32.90% 31.30% 36.50% 30.70% 25.30% 31.50%

50~59sample 60 116 59 235 84 170 254 58 173 26 257

% 25.80% 27.80% 23.10% 26.00% 29.50% 24.70% 26.10% 27.50% 25.10% 31.30% 26.10%

>=60sample 21 22 26 69 19 64 83 17 50 9 76

% 9.00% 5.30% 10.20% 7.60% 6.70% 9.30% 8.50% 8.10% 7.20% 10.80% 7.70%

totalsample 233 417 255 905 285 689 974 211 690 83 984

% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

2 (P-value) 10.221 (0.25) 12.264 (0.015)** 11.745 (0.163)

educ

atio

n

Lowsamples 55 145 103 303 76 246 322 60 223 43 326

% 23.40% 35.10% 40.40% 33.60% 27.00% 35.80% 33.20% 28.40% 32.40% 51.80% 33.20%

Middlesample 56 112 59 227 58 187 245 55 184 16 255

% 23.80% 27.10% 23.10% 25.10% 20.60% 27.20% 25.30% 26.10% 26.70% 19.30% 26.00%

Highsample 124 156 93 373 148 255 403 96 281 24 401

% 52.80% 37.80% 36.50% 41.30% 52.50% 37.10% 41.50% 45.50% 40.80% 28.90% 40.80%

Totalsample 235 413 255 903 282 688 970 211 688 83 982

% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

2 (P-value) 22.44(0.000)**

*19.58

(0.000)***

15.83(0.003)**

*

inco

me

Lowsamples 36 86 68 190 49 157 206 46 135 28 209

% 17.40% 23.80% 28.50% 23.50% 19.80% 25.50% 23.90% 25.40% 22.10% 35.00% 24.00%

middlesample 121 206 138 465 135 358 493 88 364 47 499

% 58.50% 57.10% 57.70% 57.60% 54.40% 58.20% 57.10% 48.60% 59.60% 58.80% 57.20%

highsample 50 69 33 152 64 100 164 47 112 5 164

% 24.20% 19.10% 13.80% 18.80% 25.80% 16.30% 19.00% 26.00% 18.30% 6.30% 18.80%

totalsample 207 361 239 807 248 615 863 181 611 80 872

% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

2 (P-value) 12.162 (0.016)** 11.382(0.003)**

*19.794

(0.001)***

Exhibit 8 Independence test on confidence and trading turnover

Confidence in investing performance Conf. in beating mrkt Self-confidence in general situationsTrading frequency

(per month) better average worse total yes no total better average worse total

0次 samples 7 9 16 32 7 31 38 6 26 3 35

% 4.50% 3.80% 11.50% 6.00% 3.70% 8.00% 6.60% 4.40% 6.70% 6.30% 6.10%

0~5sample 66 110 64 240 82 172 254 53 181 21 255

% 42.90% 46.40% 46.00% 45.30% 43.40% 44.40% 44.10% 39.00% 46.40% 43.80% 44.40%

>=6sample 81 118 59 258 100 184 284 77 183 24 284

% 52.60% 49.79% 42.45% 48.68% 52.90% 47.50% 49.30% 56.62% 46.92% 50.00% 49.48%

21

TTLsample 154 237 139 530 189 387 576 136 390 48 574

% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%

2 (P-value) 11.374 (0.023)** 4.343 (0.114) 4.023 (0.403)

Exhibit 9 The basic statistics of trading frequency over different confidenceTrading frequency (times per month)

Self-confidence average median SD

Investment performance

Better 43.7 9.1 47.3Average 40.7 8.7 46.8worse 38.7 7.7 47.6

Beating the marketYes 40.7 9 46.6no 42.5 8.4 47.7

General situationsBetter 48.9 9.7 48.3

Average 39.6 8.3 46.9worse 42.9 8.8 48.1

Exhibit 10 Tests on inter-group differences of trading turnover: Confidence on investment performance related with the peers

The figures in each cell are the differences of the figures in the first cell of each row minus the figures in the top cell of each column. For example, the average (median) trading frequency in the group of “worse” performance is 38.7 (7.7), which minus the 43.7 (9.1) in the group of “better” performance is -5.0 (-1.4). The figures in ( ) represent the p value of the difference.

Frequency Average Frequency Median

Self-perception

Self-perceive better

Self-perceive average

Self-perceivebetter

Self-perceive average

Average 43.7 40.7 Median 9.1 8.7

Perceive average 40.7 -3(0.340) 8.7 -0.4(0.726)

Perceive worse 38.7 -5(0.785) -1.9(0.556) 7.7 -1.4(0.821) -1(0.565)

Exhibit 11 Tests on inter-group differences of trading turnover: The confidence of beating the marketThe figures in each cell are the differences of the figures in the first cell of each row minus the figures in the top cell of each column. For example, the average (median) trading frequency in the group of believing to beat the market is 40.7 (9), which minus the 42.5 (8.4) in the group of lacking confidence is -1.9 (0.6). The figures in ( ) represent the p value of the difference.

Trading frequencyPerceiving unable to

beat the marketPerceiving able to

beat the marketAverage/median

difference (P value)

Average of frequency 42.5 40.7 -1.9(0.049)**

Median of frequency 8.4 9.0 0.6(0.015)**

22