Psychology Factors Influencing Investment Decision and Investment Performance A Study on Individual Investors in Vietnam.pdf

Master Thesis
Psychology Factors Influencing Investment
Decision and Investment Performance: A Study
on Individual Investors in Vietnam
Ho Minh Phuc
Mbus 3.2
Supervisor: Dr. Thao P.Tran

ACKNOWLEDGEMENT
First of all, this thesis appears in its current form due to the assistance and guidance of
several people. I would therefore like to offer my sincere thanks to all of them who made this
thesis possible and an unforgettable experience for my studying.
Furthermore, I want to express my deep thanks to my supervisor, Dr. Tran Phuong Thao for
the trust, the insightful discussion, offering valuable advice, for her support during the whole
period of the study, and especially for her patience and guidance during the time of researching
and writing of the thesis process.
Besides my supervisor, I would also like to thank the ISB research committee for their
encouragement, insightful comments in my study.
Last but not the least, I would like to thank my family for their material and spiritual
support in all aspects of my study.
Ho Chi Minh City, December 1st, 2014
HO MINH PHUC

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December, 2014
TABLE OF CONTENTS
ACKNOWLEDGEMENT ................................................................................................................................... iii
ABSTRACT .......................................................................................................................................................... iii
LIST OF FIGURE................................................................................................................................................ iv
LIST OF TABLE.................................................................................................................................................. iv
CHAPTER 1: INTRODUCTION .........................................................................................................................1
1.1 Background of the research...................................................................................................................1
1.2 Problem Statement .................................................................................................................................3
1.3 Research Objectives and Questions ......................................................................................................5
1.4 Research Scope .......................................................................................................................................5
1.5 Research Structure.................................................................................................................................6
CHAPTER 2: LITERATURE REVIEW, HYPOTHESES AND CONCEPTUAL MODEL..........................7
2.1 Theoretical background on psychology factors ...................................................................................7
2.2 An overview of psychology factors on the stock market...................................................................11
2.2.1 Overconfidence............................................................................................................................... 12
2.2.2 Excessive Optimism......................................................................................................................... 15
2.2.3 Herding Behavior............................................................................................................................. 17
2.2.4 Risk attitude .................................................................................................................................... 19
2.3 Hypotheses development......................................................................................................................20
2.3.1 Psychology factors and investment decisions.....................................................................................20
2.3.2 Investment decision and investment performance ............................................................................23
2.4 Conceptual model .................................................................................................................................25
2.5 Chapter summary.................................................................................................................................26
CHAPTER 3: RESEARCH METHODOLOGY...............................................................................................27
3.1 Research Process ..................................................................................................................................27
3.2 Research design ....................................................................................................................................28
3.2.1 Questionnaire design:...........................................................................................................................28
3.2.2 Measurement of variables.............................................................................................................. 29
3.3 Pilot Study.............................................................................................................................................31
3.4 Main survey...........................................................................................................................................32

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3.4.1 Sampling................................................................................................................................................32
3.4.2 Data analysis method............................................................................................................................32
3.5 Chapter summary.................................................................................................................................35
CHAPTER 4: EMPIRICAL RESULTS.............................................................................................................36
4.1 Data analysis ...............................................................................................................................................36
4.2 Reliability Test using Cronbach’s Alpha............................................................................................39
4.3 Factor analysis ......................................................................................................................................41
4.4 Testing for regression assumptions.....................................................................................................43
4.4.1 Influences of Psychology Factors on the Individual Investment Decision.......................................45
4.4.2 Influences of the investment decision on the Individual Investment Performance. .......................47
4.5 Chapter summary.................................................................................................................................49
CHAPTER 5: CONCLUSION, IMPLICATIONS AND DIRECTION FOR FURTHER STUDIES ..........51
5. 1 Key findings of the thesis ..........................................................................................................................51
5.2 Managerial Implication of the study.........................................................................................................55
5.3 Limitation and direction for further studies............................................................................................56
Reference...............................................................................................................................................................58
Apendix 4.1 Questionnaire ( English version)...............................................................................................65
Apendix 4.2 Questionnaire ( Vietnamese version)........................................................................................70
Apendix 4.3: Cronbach’s Alpha Test for items of factors ................................................................................75
Apendix 4.4: Factor analysis for psychology variables and investment performance ...................................79
Apendix 4.5: Testing for regression assumptions..............................................................................................81

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ABSTRACT
The aim of this thesis is to investigate and determine the relationship between psychology
factors including overconfidence, excessive optimism, herding behavior and risk attitude which
influence investment decision and investment performance of the individual investors in
Vietnam. This research model was developed by different author who suggested various
behavioral factors which may affect the investors‟ decision-making process and the investment
performance such as Bondt (1985), Odean (1999), Bikhchandani and Sharma (2001)…
Specifically, the thesis employs a survey approach by distributing questionnaire in Ho Chi
Minh City stock exchange. Sample size of this research is 200 respondents. The 7-point
measurements are tested for their consistency and reliability by Factor Analysis and
Cronbach‟s Alpha, which prove that behavioral finance can be used for Vietnam stock market.
The findings indicated that, three of four factors have direct effects on investment decisions,
in which they explained 63.1% of the variance of investment performance of respondents. With
the method analysis of exploratory factor analysis, the research shows that the strong
relationship between psychology factors. Future researches are encouraged to improve the
financial knowledge scale to get better and accurate results. Despite of some limitations, this
study also has some significations for individual investors, financial education institutions or
government agency. Discussion and implications of the findings are delineated at the end of the
study.

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LIST OF FIGURE
Firgure 1.1 The movement of VN Index from 2000 to 6/2014 ………...……………4
Firgure 2.1: Prospect Theory…………………………………………………………11
Firgure 2.2: Conceptual model………………………………………………………..26
Firgure 3.1: Conceptual model………………………………………………………..28
LIST OF TABLE
Table 3.3: Cronbach‟s Alpha Reliability Coefficient……………………………......34
Table 4.0: Number of questionnaires of 8 securities companies in Ho Chi Minh City.37
Table 4.1: Data description …………………………………………………........38-39
Table 4.2: Cronbach‟s Alpha Test for items of factors................................................41
Table 4.3: KMO and Bartlett‟s Test.............................................................................43
Table 4.4: Factor loadings............................................................................................44
Table 4.5: Correlations ………………………………………………………………45
Table 4.6: Regression testing of psychology factor and the investment decisions…..46
Table 4.7: Summary of the relationship between psychological factors and investment
decisions 47
Table 4.8: Regression testing of investment decisions and investment performance...49
Table 4.9: Summary of the relationship between investment decision and investment
performance……………………………………………………………………………50

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CHAPTER 1: INTRODUCTION
This chapter introduces the background of the behavior finance as well as the status of
psychology factors. After that, problem statement is discussed in Vietnamese stock market to
have the general picture about the stock market. The research questions and objectives are
proposed to explore the factors determining investment decision and investment performance.
Based on these, research scope is proposed and thesis structure is presented.
1.1Background of the research
Theories of human behavior from psychology, sociology, and anthropology have motivated
much recent empirical research on the behavior of financial markets. They attempts to explain
human behaviors‟ in markets, importing theories of human behavior from the social sciences
(Shiller, 1999) to explain why and how financial markets might be inefficient (Sewell, 2007).
It could be seen that the term “behavioral finance” has been emerged since 1896 when le
Bon (1896) wrote a book “The Crowd: A Study of the Popular Mind”. It is one of the greatest
and most influential books of social psychology ever written. Later, the second-most cited
paper ever to appear in Econometrical in 1979, the prestigious academic journal of economics,
was written by two psychologists Kahneman and Tversky who proposed the prospect theory
(Kahneman and Tversky 1979). Then, Plous (1993) wrote The Psychology of Judgment and
Decision Making which gives a comprehensive introduction to the field with a strong focus on
the social aspects of decision making processes.
A wide range of behavior is taken into account when investigating investor psychology in
finance. Tversky and Kahneman (1994) confirmed a distinctive fourfold pattern of risk
attitudes: risk aversion for gains and risk seeking for losses of high probability; risk seeking for
gains and risk aversion for losses of low probability. Later, Odean (1999) demonstrated that
overall trading volume in equity markets is excessive, and one possible explanation is
overconfidence. He also found evidence of the disposition effect which leads to profitable
stocks being sold too soon and losing stocks being held for too long. Psychological research
has established that men are more prone to overconfidence than women (especially in male-

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dominated areas such as finance) whilst theoretical models predict that overconfident investors
trade excessively. Barber and Odean (2001) found that men trade 45 percent more than women
and thereby reduce their returns more so than do women and conclude that this is due to
overconfidence.
In recent years, behavioral finance issues are widely studying. Under the light of
behavioral finance, investors can be affected by psychological factors (emotional and cognitive
factors) which are the so-called behavioral biases in their decision-making process. Behavioral
biases are abstractly defined the same way as systematic errors in judgment (Pompian, 2006).
In fact, many phenomenon and individual investor‟s behaviors in the Vietnamese stock market
cannot be explained by standard finance, which based on the efficient market hypothesis.
Through the studies, it is found that there are a great number of psychological factors having a
significant influence on the behavior of investors. Among them, four common psychological
factors that exist in almost every human being are (1) overconfidence, (2) excessive optimism,
(3) attitude towards risk and (4) herd behavior. Up to now, there have been numerous studies
related to these above psychological forms of individual investors in the world such as as
Debond (1985), Odean (1999); Bikhchandani and Sharma (2001).
A study by Lakonishok, Shleifer and Vishny (1994) postulate that value strategies produce
superior returns because of investors consistently overestimate future growth rates of glamour
stocks relative to value stocks. The essence of this argument is that investors are excessively
optimistic about value (glamour) stocks because they tie their expectations of future growth in
earnings to past bad (good) earnings.
Prior studies shows that behavioral finance studies have been carried out popularly in
developed markets of Europe and the United States (Caparrelli, Arcangelis & Cassuto, 2004,
p.222–230) as well as in emerging and frontier markets (Lai, 2001, p.210–215 ; Waweru et al.,
2008, p.24-41). Among these studies, Odean (2001) indicates behavior factors existing in
developed markets while using behavioral finance for frontier and emerging markets is much
fewer than for developed markets (Waweru et al., 2008). As such, understanding behavioral
factors particularly psychology factors are important in emerging markets like Vietnam.

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With the development of the science, technology and the economy, it is possible to consider
stock market as the yardstick for economic strength and development. Therefore, the
movement of stock market trend represents the economic health of an economy. The
development of theories and models is try to attempt and explain the way how stock price goes
up and down. From the developed stock markets such as the USA, the UK, Japan.. which have
strong impacts on global security markets (Reza, Zamri & Tajul, 2009) to the emerging and the
frontier or pre emerging such as Vietnam, Kenya, the psychology of human being is
complicated and cannot be predicted. From that, researchers and investors show that to
understand people‟ activities and behavior or psychology factors is necessary.
1.2Problem Statement
In Vietnam, there are two stock exchanges. The first Vietnamese stock exchange, known as
the Ho Chi Minh Stock Trading Center (HOSTC) has been launched since 2000 and the
second, known as the Ha Noi Stock Trading Center (HASTC) has been established since 2005.
At the beginning, the market size was quite small and thin with only 2 listed companies and 4
security companies; however, the market has been developed significantly in recent years. By
December 2013, there were more than 300 listed companies on the Ho Chi Minh Stock
Exchange (HOSE), the later name of the HOSTC, with market value was 949,000 billion VND,
increased 184,000 billion VND in comparison with 2012, accounting for approximately 31%
GDP. In addition, the second stock Exchange also had significant growth as given in Huong
(2014).
Between the two markets, the Ho Chi Minh stock market has been developed significantly
in the number of listed stocks and transaction value for 14 years (Mieu, 2014), the price
movement seems to fluctuate unpredictably over different periods (Graph 1.1). However, this
market index is often used for doing research and studying in Vietnam such as Ly (2010), Chi
(2007).

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Firgure 1.1 The movement of VN Index from 2000 to 6/2014
It is commonly known that a stock market is efficient when price of the stocks is
reflected by information of the economy and the enterprises. However, the story in Vietnamese
stock market is different. In fact, in some the periods of time, the aggregate market index of
HOSE, VNIndex, increased significantly although no good information had been informed. In
contract, VNIndex went down dramatically in spite of no bad information. Some author used
behavior finance to explain behavior of the investors such as Chi (2007), Tho and Tuan (2007),
and Ly (2010), etc... These studies, however, have mainly focused on explaining the market
behavior. Additionally, different investment environment may affect the psychology of
investors unalike. In fact, the Vietnamese stock market widely differs from that of other
countries in the region as well as in over the world. According to Yates et al., (1997), cultural
difference, more specifically, life experiences and education, can affect behaviors when they
found some evidences that Asian people exhibit more behavioral biases than people raised in
Western countries or the United States. Similarly, when comparing between Western cultures
and Asian ones, Kim & Nofsinger (2008) show that the existence of culture differences can
affect the behaviors and decisions on investment. Thus, psychology factors of individual
investors in Vietnam may also differ from those of other markets.
In the literature, research associated with investors in Vietnam may be considered as in the
initial stages of development in research; therefore, there is a need to study and understand the
behavioral factors in order to identify the biases affecting their investment and effects on the
investment performance of individual investors. On the other hand, previous researches for this

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topic in Vietnam are so limited and narrow (Ly, 2010). As such, this study aims to investigate
factors affecting the investment decision and investment performance of the individual
investors. Findings of this study can help the investors in the securities business sector can
understand clearly about the problems of psychology and improve their profits in the future.
1.3Research Objectives and Questions
The research aims to examine psychological factors of individual investors influencing
investment decision and investment performance in the Vietnamese stock market. In the thesis,
several factors, including overconfident, excessive optimism, attitude towards risk and herding,
will be taken into consideration to understand how they affect the investment decision as well
as the relationship between that factor and investment performance of individual investors.
More specifically, two research questions are given as follow:
- Question 1: Do psychological factors namely overconfident, excessive optimism,
attitude towards risk and herding and affect investment decisions of individual investors
in Vietnam?
- Question 2: Does a strong tendency of investment decision have positive effect on the
investment performance of individual investors in Vietnam?
1.4Research Scope
Among behavioral factors, the thesis takes four psychology factors namely overconfidence,
excessive optimism, herding effect and risk attitude to do research. These are factors mentioned
in several studies in the behavioral financial discipline, however, they have not yet researched
widely in not only developed stock markets but also frontier markets like Vietnam, so that
investigate those four factors in Vietnamese stock market is very important to understand the
psychology of individual investors.
This study is conduct in Ho Chi Minh City, one of the biggest economic centers of
Vietnam. It is because HOSE is also known as the largest market in the country. HOSE is also
the selected market of many studies conducted in Vietnam recently such as Chi (2007), Tho
and Tuan (2007), and Ly (2010), etc… Thus, a study will be conducted in the context of the Ho

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Chi Minh City with as sample size about 200 investors who has many experienced years in the
stock market, investigated in many securities companies. The result of research in this city, in
some levels can represented for Viet Nam in general and can be use as a reference.
1.5Research Structure
This thesis will include five chapters as follows:
Chapter 1: is an introduction chapter. Furthermore, this chapter describes the overview of
research background, research problem, and objective. Hence, the scope of research,
implications, and structure of thesis are also present. The chapter discusses the background, the
research objectives as well as the scope of the thesis.
Chapter 2: demonstrates a Literature Review to present theories of psychology factors. This
chapter explains the history and development of Behavior factors. And then, the Hypotheses
and Research model to be given to test psychology factors in Vietnamese stock market. This
chapter is concentrated on explaining each variable in the model, and reasons for choosing
them to be include in the research model.
Chapter 3: is Research Methodology. It presents the research design, development of survey
questionnaire, qualitative study, and main survey. This chapter also defines how to collect data
and analyze the data collected to test the research hypotheses proposed in chapter 2.
Chapter 4: is Findings and Discussion to summarize the research results, provide the findings
and recommendations. This chapter explains the empirical part of the study. This part discusses
the method for collecting data used to test the hypothesis, and it analyses the data received, its
reliability and multiple regression.
Chapter 5: discusses about Conclusion, Implication and Further Studies from this research.

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CHAPTER 2: LITERATURE REVIEW, HYPOTHESES AND
CONCEPTUAL MODEL
This chapter aims at reviewing the related literatures of psychology finance. Firstly,
some backgrounds of psychology factors are presented such as a comparison between
traditional finance and behavioral finance. Secondly, the important theories of psychology
finance (Overconfidence, Excessive optimism, Herding behavior, Risk Attitude) are included to
have an overall picture of this field and its impacts on the investment decisions as well as the
impact of the investment decisions on investment performance. Finally, a research model with
hypotheses is proposed in conceptual model.
2.1Theoretical background on psychology factors
In the financial market, investor behavior is often known as an interesting topic for a
number of researchers (Waweru et al., 2008; Odean, 2001; Ly, 2010). It could be seen that
human behavior in the financial world is a fairly new research discipline. Thus, behavioral
finance theories which are based on psychology, trying to understand how emotions and
cognitive errors influence behavior of individual investors have been discussed recently.
According to Ritter (2003), behavioral finance is based on psychology which suggests that
human decision processes are subject to several cognitive illusions. In the stock market,
investors do not always make the decisions and actions based on reason, but they are driven by
psychological factors. When they have good mentality, they become more optimistic in
assessment process (Waweru et al., 2008). Nevertheless they become more pessimistic if their
mentality is not good. A such ﬁnance fails to explain determinants of investment performance.
The reason for this failure can be found with the assumption which is usually taken by
traditionalists: investors‟ rationality in decision-making process (Suto and Toshino, 2005).
Unfortunately, in real life, investors do not always make their decision rationally. Empirical

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research has shown that, when selecting a portfolio, investors not only consider statistical
measures such as risk and return, but also psychological factors such as sentiment,
overconfidence and overreaction.
The behavioral finance ideas started emerging in the early 1990s opposing the Efficient
Market Hypothesis (EMH) with research based on the judgment and decision makes process of
the participants of the financial markets. The efficient market hypothesis has been the key
proposition of traditional (neoclassical) finance for almost forty years. In his classic paper,
Fama (1970) defined an efficient market as one in which “security prices always fully reflect
the available information”. In other words, if the EMH holds, the market always truly knows
best. In the traditional framework where agents are rational and there are no frictions, a
security‟s price equals its “fundamental value” (Harris and Stulz, 2003). This is the discounted
sum of expected future cash flows, where in forming expectations, investors correctly process
all available information, and where the discount rate is consistent with a normatively
acceptable preference specification. The hypothesis that actual prices reflect fundamental
values is the EMH. Put simply, under this hypothesis, “prices are right”, in that they are set by
agents who understand Bayes‟ law and have sensible preferences (Bekaert and Urias, 1997). In
an efficient market, there is “no free lunch”: no investment strategy can earn excess risk-
adjusted average returns, or average returns greater than are warranted for its risk.
Behavioral finance is a new approach to financial markets that has emerged, at least in
part, in response to the difficulties faced by the traditional paradigm. In broad terms, it argues
that some financial phenomena can be better understood using models in which some agents
are not fully rational. Thaler (1999) called behavioral finance as “simply open-minded
finance". What makes behavioral finance theory different from the classical finance is that it is
not only based only on mathematical calculus, but it applies all other social sciences as
psychology, sociology, anthropology, political science or, since recently, neuroscience.
Behavioral Finance is the application of psychology to financial behavior; i.e. it is the behavior
of practitioners. According to Behavioral finance, investors are rational, but not in the linear
and mathematical sense based on the mean and variance of returns. Instead, investors respond

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to natural psychological factors such as fear, hope, optimism and pessimism. As a result, asset
values may deviate from their fundamental value and the theory of market efficiency suffers (
Shiller and Pound, 1989).
Due to the fact that people are not always rational, their financial decisions may be
driven by behavioral preconceptions. Thus, studying behavioral finance plays an important role
in finance, in which cognitive psychology is employed to understand human behaviors. In case
the decisions of people do not follow rational thinking, effects of behavioral biases should be
identified. It will be more important if their cognitive errors affect prices and are not arbitraged
away easily (Kim and Nofsinger, 2008, p.2). The mid-1980s is considered as the beginning of
this research area. Stock market is proved to overreact to information by DeBondt and Thaler
(1985, p.392-393). Moreover, Shefrin and Statman (1985, p.777) assert that stockholders tend
to be more willing to sell their winning stocks rather than loosing ones even when putting these
losers on sale is the best choice. If these studies are the genesis of behavioral finance, this area
has over two decade‟s development. It‟s clear that investors are not rational, and they don‟t
make consistent and independent decisions. Empirical research has shown that these behavioral
factors do exist and that they are, in fact, considered by the market. Thus, this may imply that
the market goes beyond the traditional theory of finance.
One of the foundational theories used to explain irrational behavior of investors is known
as the Prospect theory suggested by Tversky and Kahneman (1974). According to the theory,
people tend to be risk aversion in gain area or when things are going well and be risk-seeking
in loss. The theory describes some states of mind affecting an individual‟s decision-making
processes including regret aversion, loss aversion and mental accounting (Waweru et al., 2003,
p.28). More specifically, the theory demonstrates that risk aversion is the relatively steep slope
of the value function for losses compared to gains. The steeper slope of the value function for
losses means that the value curve is essentially concave downwards in the neighborhood of the
origin. This means that for mixed prospects, involving potential gains and losses
simultaneously, risk aversion should be observed.

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Firgure 2.1: Prospect Theory
In fact, human beings and financial markets do not posses all of these capabilities and
characteristics. For example, people fail to update beliefs correctly (Tversky and Kahneman,
1974) and have preferences that differ from rational agents (Kahneman and Tversky, 1979).
People have limitations on their capacity to process information, and have bounds on
capabilities to solve complex problems (Simon, 1957). Moreover, people have limitations in
their attention capabilities (Kahneman, 1973), and care about social considerations (e.g. by
deciding not to invest in tobacco companies). In addition, rational traders are bounded in their
possibilities such that markets will not always correct “non-rational” behavior (Barberis and
Thaler, 2003). Barberis and Thaler (2003, p.1063) are considered as one of the famous writers
who provide an excellent study about various types of behavioral biases that affect decision
making as well as financial markets.
Behavioral finance papers are mainly based on the data of stocks that do not match well
with the theories of market efficiency and asset pricing model. Many researchers consider
behavioral finance as good theory to explain psychology factors affecting investment decision
making (Waweru et al., 2008, p.25). The author believes that the study of social sciences such
as psychology can help to reveal the behaviors of stock market (Gao and Schmidt, 2005).

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There are two reasons why behavioral finance is important and interesting to be applied
for Vietnam stock market. Firstly, behavioral finance is still a new topic for study. Until
recently, it is accepted as a model to explain how investors of financial markets make decisions
and then these decisions influence the investment performance (Kim and Nofsinger, 2008).
Secondly, it is concluded that Asian investors, included Vietnamese, usually suffer from
cognitive biases more than people from other cultures (Kim and Nofsinger, 2008, p.1). Kim
and Nofsinger (2008, p.2-5) explains the differences among cultures through an individualism-
collectivism continuum. Asian cultures are supposed to belong to socially collective paradigm,
which has been argued for causing investors‟ overconfident resulting in behavioral bias.
Cultural difference, more specifically, life experiences and education can affect behaviors, thus,
it is believed that behavioral inclinations can differ among different cultures. Some evidences
have been found to prove that Asian people exhibit more behavioral biases than people raised
in Western countries or the United States (Yates et al., 1997). When comparing between
Western cultures and Asian ones, evidence shows that the existance of culture differences
which affect the behaviors and decisions on investment such as e (Kim and Nofsinger, 2008).
According to Weber and Hsee (2000, p.34), the bottom line is that the topic of culture
and decision making has not received much attention from either decision researchers or cross-
cultural psychologists. In addition, a systematic literature about behaviors of Asian people and
their effects on investment decision making is provided by Chen, Kim, Nofsinger and Rui
(2007). Vietnam is an emerging economy in Asian with many cultural characteristics similar to
other Asian countries. Therefore, to understand clearly about the characteristics and behaviors
of human being to apply them into stock market is very important. With the development of the
stock market, this article will find out the psychology factors, which affect the investment
decisions and the performance when trading stocks in Vietnamese market.
2.2An overview of psychology factors on the stock market
Behavioral finance is a new paradigm of finance and still is a controversial topic,
seeking to supplement the mordern finance by introducing aspects to the decision-making

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process. Behavioral finance applies psychology, sociology, anthropology theories to understand
the behaviors of financial market. According to Ritter (2003, p.429), behavioral finance is
based on psychology which suggests that human decision processes are subject to several
cognitive illusions. Many authors suggested various behavioral factors which may affect the
investors‟ decision-making process and the investment performance such as Bondt (1985),
Odean (1999), Bikhchandani and Sharma (2001)… Among the studies, four factors that are
commonly discussed namely overconfidence, excessive optimism, risk attitude, and herding.
2.2.1 Overconfidence
There are a lot of studies showing that people are so confident in their skills ability, they
often think they know more than they do. Overconfidence is the belief that one‟s personal
qualities are better than they really are. An overconfident individual also does not fully
recognize and adjust for his own limitations. Overconfidence is just a matter of the serious
issue of an investor, not only involves in setting up a too high proportion for private
information and overconfidence in personal skills but also makes damage the investment
method in the long term (Bondt, 1985). Overconfidence helps explain excessive activism in
regulatory strategies, just as it has been found to explain excessively active trading strategies
(Odean 1999). From the beginning of the stage, overconfidence comes from hueristic, Waweru
et al. list two factors named Gambler‟s fallacy and Overconfidence into heuristic theory
(Waweru et al., 2008, p.27).
Investors are usually overconfident about their abilities to complete difficult tasks
successfully. They believe that their knowledge is more accurate than others and their forecasts
are more precise than their experience validated. Overconfidence is believed to improve
persistence and determination, mental facility, and risk tolerance. In other words,
overconfidence can help to promote professional performance. It is also noted that
overconfidence can enhance other‟s perception of one‟s abilities, which may help to achieve
faster promotion and greater investment duration (Oberlechner & Osler, 2004). Belsky and
Gilovich (1999) referred to overconfidence as the ego trap and note that overconfidence is

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pervasive. When people overestimate the reliability of their knowledge and skills, it is the
manifestation of overconfidence (DeBondt & Thaler, 1995, p. 389, Hvide, 2002, p. 15). Many
studies show that excessive trading is one effect of investors. For example, investors and
analysts are often overconfident in areas that they have knowledge (Evans, 2006, p. 20). It also
to note that overconfidence can enhance other‟s perception of one‟s abilities, which may help
to achieve faster promotion and greater investment duration (Oberlechner & Osler, 2004).
According to Odean (1998) overconfidence is a characteristic of people, not of markets,
and some measures of the market, such as trading volume, are affected similarly by the
overconfidence of different market participants. However, other measures, such as market
efficiency, are affected in different ways but different market participants. One of the most
important factors that determine how financial markets are affected by overconfidence is how
information is distributed in a market and who is overconfident. It makes investors more
overconfident about themselves understanding about clearly the market (Waweru et al., 2008).
Barber and Odean (1999) describe how investors overestimate the precision of their
information and exhibit biases in their interpretation of that information.
Psychological studies have found that people tend to overestimate the precision of their
knowledge (Lichtenstein, Fischhoff and Philips, 1980), and this can be found in many
professional fields. They also found that people overestimate their ability to do well on tasks
and these overestimates increase with the personal importance of the task (Frank, 1935).
Additionally, most people see themselves as better than the average person and most
individuals see themselves better than others see them (Taylor and Brown,1988). Odean (1998)
examined how markets were affected by studying overconfidence in three types of traders: (i)
price-taking traders in markets where information was broadly disseminated; (ii) strategic-
trading insider in markets with concentrated information; and (iii) risk-averse market makers.
As a consequence, overconfidence increased market depth. When an individual investor was
overconfident, he traded more aggressively for any given signal. The market maker adjusted for
this additional trading by increasing market depth. Furthermore, Barber and Odean (1999) also
believe that high levels of trading in financial markets are due to overconfidence. They sustain

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that overconfidence increases trading activity because it causes investors to be too certain about
their own opinions and to not consider sufficiently the opinion of others. Overconfident
investors also perceive their actions to be less risky than generally proves to be the case.
Besides, overconfident investors believe more strongly in their valuation of stocks and
concern themselves less about their belief. Several studies analyzing the effect of gender on
overconfident level proved that both female and male showed their overconfidence, but this
level of male was higher than that of female. Barber and Odean (2001) found that men will be
more confident than women in investing, leading to higher trading. Barber and Odean report
that single men have higher risk porforlios followed by married men, married women and
single women. Besides, female seem to create investment achievements of separated shares
better than that of male (Wu, Jonhson and Sung, 2008).
The role of overconfidence in the trading tendency of stock has been studied by
Grinblatt, Keloharju and Linnainmaa (2012). They analyzed and found that overconfident
investors tend to trade more frequently. In regards to financial markets, when people are
overconfident, they set overly narrow confidence bands. Research of Gervais and Odean (2001)
which get conclusion that a trader‟s expected level of overconfidence increases in the early
stages of his career. Then, with more experience, he comes to better recognize his own ability.
An overconfident trader trades too aggressively, thereby increasing trading volume and market
volatility while lowering his own expected profits. Overconfidence can lead to more
transactions but can damage the investment achievements because of costs, taxes… As the
result, overconfidence make individual investors more optimism about the future of the stocks
in up trend market, however in the down trend one, it make people get loses in trading because
they are absolutely believe in their abilities in investing but nothing is exception in stock
market especially in the emerging market like Vietnam where psychological factors affect
strongly the investment decisions. The excessive confidence has led to the wrong decision
when they focus too much on good news of companies and ignore negative information, which
makes them think that stocks being invested are good stocks. And thus, they tend to invest

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15
much in a familiar stock or securities of the company they work, and become less diversified
their portfolio.
2.2.2 Excessive Optimism
Another psychology factor that may affect the investment decision is optimism. A
related branch of the self-enhancement literature documents the tendency of individuals to be
too optimistic about their own future prospects (Weinstein et al., 1980; Kunda, 1987; Weinstein
and Klein, 2002). After the crisis of 2008, many investors fail in the stock market but
individuals are the most optimistic about outcomes which they believe are under their control
(Langer, 1975) Furthermore, excessive optimism stems from overconﬁdence; and trust related
to the events happening in the future will be more beautiful and positive than those of in the
reality.
Optimism is measured using analyst forecasts. Analysts are important for several
reasons: they are professional market watchers, and their judgments of stock and earnings
performance are followed closely by investors (Givoly and Lakonishok, 1979). Optimism is
determined concurrently with returns. Although the measure cannot predict returns ex ante, it
does indicate the extent to which optimism is impounded in stock prices. Behavioral models of
tock returns allow for optimistic expectations (Barberis, Shleifer, and Vishny, 1998; and
Daniel, Hirshleifer and Subrahmanyam, 1998). Investors are thought to sometimes
overestimate growth prospects, thus inflating stock prices. As the optimistic expectations are
not fulfilled, the returns of these stocks are low.
Another evidence is given by Gervais, Heaton and Odean (2002) showed that excessive
optimism usually results in positive impact because it encourages to do the investment. This
effect seems to be positive because the fear of risk may have a negative impact on the value of
the companies. However, it can cause more harm than good, especially excessive optimism can
cause a negative effect because this may lead the companies or investors to accept the
opportunities to invest in the negative net present value or in the highly risky assets such as
debt, low return rate but high price by Ly (2010).

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16
Previous studies do not use a direct measure of optimism. For example, Ackert and
Athanassakos (1997) and Dieter, Malloy, and Scherbina (2002) relate forecast optimism to the
dispersion of analyst forecasts and show that the dispersion is related to stock returns. Other
studies use either time series earnings estimates or analysts‟ forecasts of earnings growth rates
(e.g., Lakonishok, Shleifer, and Vishny, 1994; Chan, Jegadeesh, and Lakonishok, 1996;
LaPorta and Remiddi, 1996).
Investors finally realized that there had been excessive optimism make the crashes and
bubbles. The wave turned into one of excessive pessimism (De Grauwe, 2008). Fundamentals
like productivity growth increased at their normal rate. The only reasonable answer is that there
was excessive optimism about the future not only of the one country‟s economy but also the
world. Investors were caught by a wave of optimism that made them believe that the economy
was on a new and permanent growth path for the indefinite future. Such beliefs of future
wonders can be found in almost all bubbles in history.
According to Johnsson et al. (2002), a research investigates factors inﬂuencing
investment decision making of individual and institutional investors in Sweden. Author finds
that optimism stands for 39% behavioral biases of individual. Miller (1977) argues that
optimism enters into stock prices because pessimistic investors are reluctant to sell short.
Highly dispersed analyst earnings forecasts characterize firms having large differences in future
expectations. Thus, these firms have some investors who believe that future prospects are good,
the optimists, and some investors who believe that future prospects are poor, the pessimists.
Consistent with Miller (1977), pessimistic investors avoid such firms due to the risks or
difficulties of short selling. Thus, optimistic investors drive the stock prices of firms with
highly dispersed forecasts. Ackert and Athanasakkos (1997) and Dieter, Malloy, and Scherbina
(2002) provide support for this theory when they find that high earnings forecast dispersion is
associated with lower stock returns.
As a consequence, Vietnamese investors sometimes have exvessive optimism about the
the economy and the future growth market although Vietnam is developing to become one of
the most attractive countries in Asia, however it is too optimic if consider Vietnamese stock

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market is a destination. Obviously, with difficulty of infrastruction and capital, Vietnam need
more than that to attract the investors, so that understand the optimism in Vietnamese stock
market also plays an important role in investment.
2.2.3 Herding Behavior
Herding effect in financial market is identified as tendency of investors‟ behaviors to
follow the others‟ actions (Bikhchandani and Sharma, 2001; Banerjee, 1992). Based on the
observed actions of others, the individuals create the behavior; or in other words that are
imitative actions of others (Hwang and Salmon, 2004). In the perspective of behavior, herding
can cause some emotional biases, including conformity, congruity and cognitive conflict etc…
Many researchers also pay their attention to herding; because its impacts on stock price
changes can influence the attributes of risk and return models and this has impacts on the
viewpoints of asset pricing theories (Tan, Chiang, Mason & Nelling, 2008). Herding investors
base their investment decisions on the masses decisions of buying or selling stocks. Waweru et
al. (2008) report that investment decisions that investors can be affected by the others: buying,
selling, stock choices, length of time to hold stock, and volume of stock traded. In contrast,
informed and rational investors usually ignore following the flow of masses, and this makes the
market efficient. Waweru et al.(2008) conclude that buying and selling decisions of an investor
are significantly impacted by others‟ decisions, and herding behavior helps investors to have a
sense of regret aversion for their decisions. In the security market, herding investors base their
investment decisions on the masses‟ decisions of buying or selling stocks. In contrast, informed
and rational investors usually ignore following the flow of masses, and this makes the market
efficient. Herding in the opposite causes a state of inefficient market, which is usually
recognized by speculative bubbles.
Generally, herding investors act the same ways as prehistoric men who had a little
knowledge and information of the surrounding environment and gathered in groups to support
each other and get safety (Caparrelli et al., 2004, p. 223). The more confident the investors are,
the more they rely on their private information for the investment decisions. In this case,

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investors seem to be less interested in herding behaviors. When the investors put a large
amount of capital into their investment, they tend to follow the others‟ actions to reduce the
risks, at least in the way they feel. Besides, the preference of herding also depends on types of
investors, for example, individual investors have tendency to follow the crowds in making
investment decision more than institutional investors (Goodfellow, Bohl & Gebka, 2009,
p.213).
On the one hand, Waweru et al. (2008, p.31) propose that herding can drive stock
trading and create the momentum for stock trading. However, the impact of herding can break
down when it reaches a certain level because the cost to follow the herd may increase to get the
increasing abnormal returns. Waweru et al. (2008, p.37) identify stock investment decisions
that an investor can be impacted by the others: buying, selling, choice of stock, length of time
to hold stock, and volume of stock to trade. Waweru et al. conclude that buying and selling
decisions of an investor are significantly impacted by others‟ decisions, and herding behavior
helps investors to have a sense of regret aversion for their decisions. For other decisions: choice
of stock, length of time to hold stock, and volume of stock to trade, investors seem to be less
impacted by herding behavior.
On the other hand, herd behavior can also be generated from the rational views.
Devenow and Welch (1996) find that herd behavior may be caused by the wise consideration,
if that behavior was based on the information of results of other individuals. This considering
can happen in 4 cases: (a) individuals do not own any particular information, (b) have the
private information, but the information is uncertain due to the low quality of information, (c)
not confident in the ability of processing their information, (d) believe others to possess better
information. This comes from the asymmetric information in the market. The more
disproportional information the markets have, the more popular herd mentality is.
However, these conclusions are given to the case of institutional investors; thus, the
result can be different in the case of individual investors because, as mentioned above,
individuals tend to herd in their investment more than institutional investors. Therefore, this

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research will explore the influences of herding on individual investment decision making at the
Vietnamese Stock Exchange to assess the impact level of this factor on their decisions.
2.2.4 Risk attitude
Nowadays, researchers not only concern about the stock fundamental and technical
analysis but also focus on the risk attitude of individual investors to investigate how they trade
stocks in the market exchange. In the ﬁnancial sector, risk is still a controversial concept. The
risk associated with decision alternatives and attitude of the decision-maker toward risk are two
important factors that should be considered in forest planning. One important open question
concerns the determinants of individual differences in risk attitudes. Risk and uncertainty play
a role in almost every important economic decision. As a consequence, understanding
individual attitudes towards risk is intimately linked to the goal of understanding and predicting
economic behavior. A growing literature has made progress on developing empirical measures
of individual risk attitudes, with the aim of capturing this important component of individual
heterogeneity (see, e.g., Bruhin et al., 2007), but many questions remain unresolved.
There are many different measure methods of risk due to the existence of numerous
definitions of risk while stocks have historically performed well over the long term, there's no
guarantee that make money on a stock at any given point in time. Previous studies measure risk
attitudes using survey questions, and found mixed evidence on determinants, for example
gender (Barsky et al., 1997). Although a number of factors can help investors make decision on
a stock, no one can predict exactly how a stock will perform in the future. There's no guarantee
prices will go up or that the company will pay dividends (Alhakam & Slovic, 1994). Or that a
company will even stay in business. However, most of arguments stated that risk is an
unexpected result and closely connect with uncertainty. Nowadays, there are always ups and
downs in the stock market. This makes a stock more risky, volatility is measured in very
precise ways (such as variance, standard deviation, and beta (Ly, 2010). The hypothesis of
instrinsic risk attitude states that an individual‟s preference for risk choice alternatives is a
combination of: the strength of preference the individual feels for the outcomes and his attitude
towards risk by Bell and Raiffia (1982).

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One theoretical issue relevant to defining and measuring investment risk tolerance is the
generality of attitudes towards risk. Traditionally, some have researchers argue that people
show general traits of risk-seeking or risk-avoidance (Eysenck & Eysenck, 1978; Zuckerman,
1983; Horvath & Zuckerman, 1993). But others have argued that risk tolerance is situation
specific, with little consistency shown across tasks and domains (e.g., Slovic, 1964; Kogan &
Wallach, 1964). Weber, Blais & Betz (2002) argue that risk preferences show consistency
across application domains, but that people‟s perceptions of risk vary considerably across
domains. Risk attitudes and perceptions are shown to vary cross-culturally (e.g., Weber &
Hsee, 1998; Hsee & Weber, 1999).
In behavioral decision making research, an important distinction has been made between
decision behavior under risk and under uncertainty. In the present and prior papers, the term
“risk” is used to denote situations in which the probabilities of outcomes are known or at least
made explicit, and “uncertainty” to denote situations in which the probabilities of outcome are
unknown. It is also presented by Knight (1921) is one of the first researchers to point out that
risk and uncertainty are different. The Ellsberg paradox (Ellsberg, 1961) is a compelling
demonstration of one source of risk aversion in investment decision making: the fact that
people show what can be described as uncertainty aversion which cannot be known in the
future with risk.
The Prospect theory is often used to explain the risk attitude of investors. Weber, Blais,
and Betz (2002), who support for the Prospect Theory, show that people are fond of risk when
facing the losses. Specifically, they usually keep the stocks when getting losses and rarely keep
those stocks too much in the portfolios when price is going up.
2.3Hypotheses development
2.3.1 Psychology factors and investment decisions
Investment decision is a complex process which includes analysis of several factors and
following various steps. It could be defined as the process of choosing a particular alternative
from a number of alternatives. It is an activity that follows after proper evaluation of all the

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alternatives by Kengatharan and Kengatharan (2014). Investors‟ decisions are derived from
complex models of finance based on the relationship between expected risk and return. But
nowadays, investment decision is not only based on the personal resources and complex
modelsKengatharan and Kengatharan (2014) states that to make appropriate decision, one
needs to analyze the variables of the problem by mediating them applying cognitive
psychology. As mentioned in previous sections, there are several psychological factors
affecting investment decisions such as overconfidence, excessive optimism, herd behavior, and
risk attitude.
Overconfidence and investment decision
To begin with people overestimate the reliability of their knowledge and skills; it is the
manifestation of overconfidence (DeBondt & Thaler, 1995, p. 389, Hvide, 2002). Many studies
show that excessive trading is one effect of investors. overconﬁdence can lead to more
transactions but can damage the investment achievements. Overconﬁdence causes investors
trade too much and take too much risk. As a consequence, investors pay too much in
commissions, pay too much in taxes, and are susceptible to big loses. It could be seen in study
by Waweru et al. (2008), Debondt (1985), Odean (2001)... Overconfidence makes damage the
investment method in the long term (Debond, 1985). In Vietnam, Ly (2010) also find out the
effect of overconfidence in behavior finance, however that is not strong enough with the
significant meaning nearly 10%. Therefore, the thesis suggests the first hypothesis in the
Vietnamese stock market:
Hypothesis 1(H1): There is a significant negative relationship between overconfidence
and investment decisions of individual investors in Vietnam.
Excessive optimism and the investment decisions
Gervais, Heaton and Odean (2002) show that excessive optimism usually results in
positive impact because it encourages the investors to do the investment. Investors finally
realized that there had been excessive optimism make the crashes and bubbles. The wave
turned into one of excessive pessimism (De Grauwe, 2008). Fundamentals like productivity
growth increased at their normal rate. According to Johnsson et al. (2002), a research

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investigates factors inﬂuencing investment decision making of individual and institutional
investors in Sweden. Miller (1977) argues that optimism enters into stock prices because
pessimistic investors are reluctant to sell short. Highly dispersed analyst earnings forecasts
characterize firms having large differences in future expectations.
In fact, excessive optimism can lead investors believe in the economy better in the future
like Vietnam economy next many years, expected to develop to one of the most developing in
the Asia (Ly, 2010). Ly (2010) also find the impact of optimism in Vietnam but it is not
significant. Hence, this paper tests again that factor by suggesting the hypothesis 2 as follow:
Hypothesis 2 (H2): There is a significant positive relationship between excessive
optimism and investment decision of individual investors in Vietnam.
Herd behavior and investment decisions
In the security market, herding investors base their investment decisions on the masses‟
decisions of buying or selling stocks. In this case, herding can contribute to the evaluation of
professional performance because low-ability ones may mimic the behavior of their high-
ability peers in order to develop their professional reputation (Kallinterakis, Munir &
Markovic, 2010, p.306). Another study by Waweru et al. (2008, p.31) indicates that herding
can drive stock trading and create the momentum for stock trading. In the movement of
Vietnamese stock market, there is several evidence showing that the market was influenced by
the herding behavior in previous researches such as Ly (2010), Chi (2007), Farber, Nguyen and
Vuong (2006, p.17) and Tran (2007, p.23-25), which suggest that the herding effect in Vietnam
stock market is very strong, especially toward positive return of the market. Based on the above
arguments, one hypothesis is given as follow:
Hypothesis 3(H3): There is a significant positive relationship between herd behavior
and the investment decisions of individual investors in Vietnam.
Risk attitude and the investment decisions
According to Theory of Prospect by Tversky and Kahneman (1974), risk attitude of
individual investors is totally different. There is great need for a scale that assesses individual

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differences in attitude towards risk. It is obvious that people differ in the way they resolve
work-related or personal decisions that involve risk and uncertainty. Such differences are often
described or explained by differences in risk attitude. In many situations people are selected
based on their purported risk attitudes by Weber, Blais, Betz (2002), Alhakam & Slovic (1994)
or Slovic (1964). Risk attitudes and perceptions have also been shown to vary cross-culturally
(e.g., Weber & Hsee, 1998; Hsee & Weber, 1999). In Vietnamese market, people tend to take
more risk to get higher benefit (Ly, 2010). However, that factor is not popular in Vietnamese
stock market and needs to do research more. There are two types of risk attitude: risk seeking
and risk avoidance. Thus, while the risk avoidance is reversed, the risk seeking can be
mentioned to be a fourth factor for the hypothesis is suggested that:
Hypothesis 4(H4): There is a significant positive relationship between risk attitude and
the investment decisions of individual investors in Vietnam.
2.3.2 Investment decision and investment performance
Some researchers believe that overconfident investors who have the extreme trading
behavior could benefit with elevated results in comparision to the bad performance of irrational
investors can remove them from the security market (Anderson, Henker and Owen, 2005,
p.72). In the balanced condition, the overconfident investors trade much higher than their
rational opponent, and expect a higher investment profit over the long term. Wang (2001,
p.138) recognizes that under-confidence and high overconfidence are not likely to exist in the
long term, but moderate overconfidence can endure and dominate the rational behavior. Kim
and Nofsinger (2003, p.2) claim that stocks experiencing the greatest increase in individual
possession can earn a negative abnormal return during the year; whereas, stocks that experience
the most decrease in individual ownership may earn a positive abnormal return. Besides, they
are also surprised to explore that investors to be pre-disposed to selling their winners and
holding their losers. It is reasonable to understand that rate of return of investors requirement is
recently equal to or higher than the average return rate of the market but the fact does not like
that by Kengatharan and Kengatharan (2014). People rarely take profits too much because they

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are afraid of losing that profit, they are willing to sell stocks easily meanwhile they will take
stocks which make them loose for a long time even price will go down.
Besides, Oberlechner and Osler (2004, p.1-33) identify level impacts of overconfidence
of the investment decision‟s effect on the investment performance which is measured by
investment return rate and trading experience. Oberlechner and Osler also believe that
investment return rate (or profit) presents the investment performance objectively. The return
rate is evaluated by the investors in comparison to their peers‟ profit rates. The prior author
mainly use the secondary data of investors‟ results in the security markets to measure the stock
investment performance such as Lin and Swanson (2003), Kim and Nofsinger (2003).
However, this research asks the investors to evaluate their own investment performance, so that
the measurements of investment performance follow the research of Oberlechner and Osler
(2004) for the investment return rate. Therefore, the return rate of their recent stock investment
meets their expectation, for example, to repay the interest payment if they make a loan by
Waweru et al. (2008) and Qureshi (2013). As a matter of fact, many individual investors in
Vietnamese stock market make a loan from the bank to invest in stock market, it means that
they expect the investment performance or the investment return rate with the optimism about
the future of the economy as well as the stock market make them more confident or optimism
in the investment decision.
In more details, the return rate of stock investment is evaluated by objective and
subjective viewpoints of individual investors. The subjective assessment of investors is made
by asking them to compare their currently real return rates to their expected return rates while
the objective evaluation is done by the comparison between the real return rates and the
average return rate of the security market by Kengatharan and Kengatharan (2014). Besides,
the satisfaction level of investment decisions is proposed in this research as a criterion to
measure the investment performance. In reality, there are investors felling satisfied with their
own investment performance even if their investment profits are not high; in contrast, other
investors do not feel satisfied with their investments even when their profits are relative high.
Therefore, the satisfaction levels of investment decisions together with investment return rate

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25
are proposed as measurements for the investment performance in this research, followed by
Kengatharan and Kengatharan (2014).
Based on previous theories and researches such as Kengatharan and Kengatharan (2014)
and Waweru et al. (2008), there is existence strongly between investment decision and
investment performance, therefore, this research is suggested to test the relationship
Vietnamese stock market as mentioned in the following hypothesis.
Hypothesis 5(H5): Investment decisions have positive impacts on the investment
performance of individual investors in Vietnam.
2.4Conceptual model
Based on the literature review and the above arguments, this research proposes the
research model indicated, including the four factors that have impact on intention to the
investors‟ decision and investment performance. These behavior biases namely
Overconfidence, Excessive optimism, Herd behavior and Risk attitude are presented in the
following research model.
Firgure 2.2: Conceptual model

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Hypothesis 1(H1): There is a significant negative relationship between overconfidence
and investment decisions of individual investors in Vietnam.
Hypothesis 2(H2): There is a significant positive relationship between excessive
optimism and investment decisions of individual investors in Vietnam.
Hypothesis 3(H3): There is a significant positive relationship between herd behavior
and the investment decisions of individual investors in Vietnam.
Hypothesis 4(H4): There is a significant positive relationship between risk attitude and
investment decisions of individual investors in Vietnam.
Hypothesis 5(H5): Investment decisions have positive impacts on investment
performance of individual investors in Vietnam..
2.5Chapter summary
In this chapter, with the theoretical background of psychology factors, this chapter
illustrates the overview of those factors in prior researches not only in the world but also in
Vietnam with some papers researched with different results however, those factors are not
investigated in Vietnam too much and it is also fresh in some papers. This chapter also shows
the relationships between psychology factors and investment decisions as well as the
investment decision and investment performance. Then, this chapter shows the conceptual
model and hypotheses which need to be analyzed in the next chapters. Furthermore, articles of
Vietnamese authors are often not cited accurately and lack of supportive empirical evidences or
deep analysis, which makes us difficult to find credible information. In addition, it is important
to note that although this research aims at finding the correlation between behavioral factors
and investment performance, there are very few studies about this relationship can be found.

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CHAPTER 3: RESEARCH METHODOLOGY
This chapter introduces research methodology that is used to test the Research framework
developed in previous session. It will present research process, research design, how to
generate surveyed questionnaires, how to survey for research data, how to access this data set
to know if it is reliable and analyze the data from pilot survey by reliability and factor analysis
and how to conduct the final survey to collect the data for analysis.
3.1Research Process
This study used two research methods. The first phase, pilot test build models, factors,
suitable measurement variables for research in HCMC. Specifically, through the previous
relevant researches, the questionnaire built then running the pilot test for checking the
efficiency and the meaning of the questions. The pilot test is purposed to explore and define the
relevant items and building a completed questionnaire.
With the initial goal of identifying which psychological aspects of investors in Vietnam
stock market affect the behavioral factors on their investment, the main survey of research
approach was employed for this study. Firstly, based on the theories and previous studies,
document research technique is conducted to build main psychological factors which inﬂuence
the investment decision of individual investors. The second phase, main survey is the main
approach of this study. The goal is to identify the factors affecting investment decisions and
investment performance. Research process includes the steps as illustrated in:

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Figure 3.1: Research process
3.2Research design
3.2.1 Questionnaire design:
Based on the literature given in the Chapter 2, the thesis designs a questionnaire to
investigate psychological factors affecting investment decisions and the impact of the
investment decision on investment performance. More specifically, the questionnaire consists
of two main parts:
- Part 1: General information to get information about the respondent‟s stock
transaction. This information helps select the decision respondent to study. In this step, the
official questionnaire is finalized following the findings from the pilot survey. The official
questionnaire is made in both English and Vietnamese version given the targeted respondents
are all investors‟ levels who should have a deep view on the questions asked.
- Part 2: The main information includes statements (questions) are based on a scale of
measurement was proposed for the research. The items were measured on the Likert 7-point
scale from 1 to 7 (strongly disagree, disagree, neutral, agree, and strongly agree).

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3.2.2 Measurement of variables
The measurement scales used in this study way multi-item 7 point Likert scales, which
developed and validated by previous researches.
Psychology factors namely confidence, excessive optimism, herding effect and risk
attitude is researched in many studies. Four factors discussed by Waweru et al. (2008), Tversky
and Kahneman (1974), Olsen (1998), Johnsson et al. (2002), Ly (2010), Kengatharan and
Kengatharan (2014). The author takes questionnaire based on:
Construct
Coding of
Variables Items Source
Overconfidence
(OVC)
OVC1
Investors believe that they can choose stocks
better than others
Waweru et al.
(2008), Odean
(1999)
OVC2
Investors definitely control their investment
activities
OVC3
Almost investment success depends on their
their skills
OVC4 Investors understand clearly the market
Excessive
Optimism
(EO)
EO1
Investors continue to invest in the down -trend
market
Odean (2002),
Johnsson et al.
(2002), Ly
(2010)
EO2 Investors will add more capitals in the market
EO3
Investors believes that the market trend will go
up next year
EO4
If Vn Index goes down 4%, investors believe
that the market will recover
Herd Behavior
(HB) HB1
Other investors' decisions of choosing stock
types have impact on your investment
decisions.

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Construct
Coding of
Herd Behavior
(HB)
HB2
If investors have their own information which
is different to the market, you will make the
decisions or follow the market.
(Bikhchandani
and Sharma,
2001), Waweru
et al. (2008), Ly
(2010), Olsen
(1998),
Kengatharan and
Kengatharan
(2014).
HB3
Investors look at the volume on the Vn Index to
make the investment decisions to buy or sell.
HB4
You usually react quickly to the changes of
other investors' decisions and follow their
reactions to the stock market.
Risk attitude
(PR)
PR1
Investors like big price fluctuation to get the
high profit Tversky and
Kahneman
(1974), Ly
(2010), Waweru
et al. (2008)
PR2
Investors like to invest the companies which
they knows clearly
PR3
When price goes down, the investors often keep
the stocks longer to wait the price go up
PR4
Investors like to invest the companies which
have the stable dividend
Investment decision mentioned in many previous studies such as Qureshi (2013), Coval
and Shumway (2000, p.3), Kengatharan and Kengatharan (2014).
Construct Coding of Variables Items Source
Investment
Decisions
(ID)
ID1
Our investment in stocks has a high degree of
safety
Qureshi (2013),
Coval and
Shumway (2000,
p.3) Kengatharan
and Kengatharan
(2014).
ID2
Our investment has the ability to meet interest
payment
ID3
Our investment has a lower risk compared to
the market in general

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Investment performance is the factor combination between the satisfaction levels of
investment decisions together and investment return rate are proposed as measurements by
Kengatharan and Kengatharan (2014). The questionnaire is suggested by Waweru et al. (2008),
Kengatharan and Kengatharan (2014), Oberlechner and Osler (2004).
Construct
Coding of
Investment
performance
(IP)
IP1
The return rate of your recent stock investment
meets your expectation. Waweru et al.
(2008),
Kengatharan and
Kengatharan
(2014),
Oberlechner and
Osler (2004).
IP2
Your rate of return is recently equal to or higher
than the average return rate of the market.
IP3
You feel satisfied with your investment
decisions in the last many years (including
selling, buying, choosing stocks, and deciding
the stock volumes).
3.3Pilot Study
Due to the scale of research are adopt from the scales of the previous researches. These
researches were conduct in different culture, the level of economic development and selected
respondents. Therefore, a pilot study was conduct through qualitative research method. The
purpose is to gather information, and adjust variables in these scales. The wording Vietnamese
language for these scales is also doing to study so that, respondents can understand the
question, to avoid confusion.
To begin with, questionnaires are sent to brokers working in Securities Companies in
Vietnam, specific in Ho Chi Minh City and they are responsible for sending to individual
investors. Because brokers have strong relationship with investors, the response rate is
expected to be high. Although questionnaire distributions done by intermediate people may
result some biases due to the lack control over the respondent selection process, some actions
are done to minize the negative impact on the data quality. Firstly, brokers are explained clearly

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what is random sampling and how to choose respondent randomly. Secondly, they commit
following instructions completely.
After collecting and analyzing the data collected through questionnaires, semi-structured
interviews are employed to expand the scope of the research. Interviews with experts in
security field provide deeper understanding about the results as well as their experiences about
financial behaviors of Vietnamese individual investors in stock market. With 30 individual
investors for pilot study is investigated first. After draft questionnaires, pilot study is proceed
and do reliability analysis and factor analysis to make the final questionaire.
3.4Main survey
3.4.1 Sampling
In factor analysis, the sample size should be as large as possible with the minimum
should be at least five times as many observations as the number of factors to be analyzed and
preferably not less than 100. As there are 22 variables used for the factors analysis, the
minimum sample size should be 110 (20x5). In addition, for the multi regression model,
minimum sample size should be equal to n=50+8m, which m are number of independent
variables (Tabachnick and Fidell, 1996). With the initial research model, there are 5
independent variables; minimum sample size for this should be 200 (50+8x19). In light of the
above two requirements, this research choose the biggest sample size. Therefore, sample size
used for this research should be 200.
3.4.2 Data analysis method
In the data analysis, the reliability and exploratory factor analysis will be applied.
Specifically:
Reliability test using Cronbach’s Alpha
Reliability frequently refers to the consistency of a measure of concept, that is to say, if
the research is carried out in the other similar context and the similar results can be obtained,
the research is highly reliable (Saunders et al, 2007, p.149). Reliability is considered through
three prominent factors namely stability, internal reliability and inter-observer consistency

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(Bryman & Bell, 2011, p.158). According to George and Malley (2003), “Cronbach‟s alpha is
used as only one criterion for judging instruments or scales. It only indicates if the items “hang
together”; it does not determine if they are measuring attribute. Therefore, scales also should be
judged on their content and construct validity”. As Cronbach‟s Alpha calculates the average of
all split-half reliability coefficients, it can totally answer the question of internal reliability that
whether or not the indicators that make up the scale or index are consistent (Bryman & Bell,
2011, p.159). As many writers suggest the acceptable factor loading is 0.6 and above (Shelby,
2010, p.143), so that all achieved scores for this study need to be more than 0.6 shows high
level of internal reliability.
Table 3.3 Cronbach’s Alpha Reliability Coefficient
Source: George and Malley (2003)
Exploratory Factor Analysis (EFA)
Norris and Lecavalier (2010, p.9) supposed that “EFA is based upon a testable model
and can be evaluated in terms of its fit to the hypothesized population model; fit indices can be
generated to help with model interpretation”. EFA helps to analyze the structure of correlations
among many variables by identifying a set of core dimensions, called factors (Ghauri,
Gronhaug and Kristinslund, 2010, p.189). In this study, EFA is used to explore the factors that
the variables of behavioral finance and investment performance of the questionnaire belong to.
EFA is used to reduce the number of items in the questionnaire that do not meet the criteria of
the analysis (O‟brien, 2007).
In this research, the following criteria of the EFA analysis are applied: Factor loadings,
Kaiser-Meyer Olkin Measure of Sampling Adequacy (KMO), Total variance explained. In

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specific, factor loadings are defined as correlations of each item with the factor that it belongs
to. Besides, factor loadings of the items on a factor are greater than 0.5 (with the sample size is
100) ensure that EFA has a practical significance to the analyzed data (Hair et al., 1998). The
KMO presents the level of suitability of using EFA for the collected data. The KMO should be
between 0.5 and 1.0 (significant level less than 0.005) to make sure that factor analysis is
suitable for the data (Ali, Zairi & Mahat, 2006). Furthermore, total variance explained is used
to identify the number of retained factors in which factors can be retained until the last factor
represents a small proportion of the explained variance. The total variance explained is
suggested to be more than 50% (Hair et al., 1998).
Multiple regression analysis. Hair et al. (2010, p. 156) claimed that there is the
difference between the actual and predicted values of dependent variable. That means the
random error will occur when predicting sample data. It is called the residual (ε or e). Based on
these studies, the multiple regression formula will be
Y 1= a + β1X1 + β2X2 + … + βnXn + ε
Where in Y1: is the dependent variable (investment decisions)
a: is constant
β: is called beta weight, standardized regression coefficient, or beta coefficient
X: is the independent variables (overconfidence, excessive optimism, herd behavior,
risk attitude).
ε: is the residual
and Y 2= a + β1X1+ ε
Where in Y2: is the dependent variable ( investment performance)
X: is the independent variable ( investment decisions)
Moreover, Meyers, Gamst, and Guarino (2006, p. 161) introduced the value of R2
indicating how much variance of the dependent variable is accounted for by the full regression
model. Therefore, the higher the value of R2, the greater the explanatory power of the
regression equation (Hair et al., 2010).

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3.5 Chapter summary
This chapter presented the research methodology for conducting the study. There are
three main phases of the study. The first phase was conducted via literature reviews and
interviews in stock companies. As a result, the purpose of this phase was to assess the content
and applicability of each measure was specified based on the literature. Also, the interviews
helped identify key informants for the research. Second, a pilot survey was conducted with 30
potential respondents came from Vietnamese companies in Ho Chi Minh City, to refine the
measures. With the pilot study, final questionnaire is made with the high significant. Most of
the constructs used were measured by multiple-items and were refined via reliability analysis
and factor analysis. Besides, modification of the measures after the refining process was also
undertaken. In summary, the results of the preliminary assessment revealed that the scales used
to measure the theoretical constructs in the study had acceptable levels of reliability. The next
chapters will present the data analysis of main survey and explain the statistical results of the
hypothesis testing.

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CHAPTER 4: EMPIRICAL RESULTS
This chapter presents the descriptive of collected data. The reliability and validity of data
will be assessed by using Cronbach‟s alpha and EFA. After that, the hypotheses and the effect
of demographic variables on shopper loyalty will be tested by the collected data. Consequently,
this chapter includes four parts: descriptive analysis, measurement assessment, hypotheses
testing, and testing the effect of demographic.
4.1 Data analysis
The collected data are processed and analyzed by SPSS. 200 questionnaires delivered to
individual investors at the Ho Chi Minh Stock Exchange. At first, the data are cleaned by
removing the questionnaire. Then, statistical techniques, which are used for the data to achieve
the research objectives, include Descriptive Statistics, Factor Analysis, and Multiple
Regression Analysis. In the main survey, the questionnaires were sent to brokers at eight
leading securities firms in the Vietnamese stock market. The numbers of questionnaires sent to
the firms are given in the following table:
No. Number of questionnaires
1 Saigon Securities Incorporation 25
2 Military Securities Joint Stock Company 86
3 Ho Chi Minh Securities Corporation 19
4 Sacombank Securities Joint Stock Company 5
5 ACB Securities Company Ltd. 18
6 FPT Securities Joint Stock Company 12
7 Bao Viet Securities Joint Stock Company 27
8 VNDirect Securities Corporation 8
Table 4.0 Number of questionnaires of 8 securities companies in Ho Chi Minh City

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Title Category Number %
Gender Male 176 88.0%
Female 24 12.0%
Age 18-25 36 18.0%
26-35 93 46.5%
36-45 45 22.5%
46-55 18 9.0%
Over 55 8 4.0%
Marital Status Single 87 43.5%
Married 113 56.5%
Divorced
Education Qualification
High school &
Lower 43 21.5%
Undergraduate 52 26.0%
Bachelor 39 19.5%
Masters 15 7.5%
Ph D -
Others 51 25.5%

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Title Category Number %
Time of Trading Stocks
Under 5 yearss 147 73.5%
5-10 years 38 19.0%
Over 10 years 15 7.5%
Amount of Investment last year
(VND)
Under 50 million 31 15.5%
50-200 million 56 28.0%
200-500 million 67 33.5%
500m - 1 billion 28 14.0%
Over 1 billion 18 9.0%
Table 4.1: Data description
Table 4.1 shows that the numbers of female and male investors in the sample are not equal
(male about 88%, and female about 12%) because Vietnamese stock market is just
approximately 14 years and Female does not have much chances to attend. The stock investors
are mainly at the ages from 26 to 35 (93 investors that accounts for 46.5% of the total sample),
while 22.5% of the respondents being at the age-range of 36-45, 9% of the age from 46-55, and
18% of the sample having the young ages of 18-25. This sample reflects the fact that a high
proportion of individual investors at the HOSE are younger than 35, and this research may
highly reflect the investment behaviors of these investors. The Table also presents that a large
proportion of the sample are investors who have attended the stock market for the duration less
than 5 years (73.5% of respondents having attended from 1 to less than 5 years). 19% of
respondents have attended the stock market for more than 5 years and less than 10 years;
whereas, only 15 stock holders, accounting for about 7.5%, have participated the security
market for more than 10 years. This statistical numbers show that the sample reflects suitably
the population of the stockholders at the HOSE because the HOSE has just existed for nearly
14 years. Most of individuals have just paid their attention to stock market in the recent years.
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When it comes to amount of investment last year, the higher percentages of individual
investors in the surveyed sample invest with ranges from 200-500 million VND: 33.5%
respondents investing, 28% investing from 50-200 million VND, meanwhile 14% investing
from 500-1000 million VND and 15.5% investing from under 50 million VND. Besides, there
are 9% of the sample investing with the relatively large amount of money (over one billion
VND) last year.
In total, the respondents are the stock investors with the higher proportion of the ages from
26 to 35, and generally newcomers of stock exchange. This is easy to acknowledge because the
HOSE is the new stock exchange and Vietnam stock market is just considered as a pre-
emerging market as mentioned in Chapter 1. The sample also consists of investors who are
members of a diversity of security companies and cover the large ranges of investment amount
last year. Besides, most of them already take course of stock exchange and have knowledge at
certain level of their investment field.
4.2 Reliability Test using Cronbach’s Alpha
In this part, Cronbach‟s Alpha is used to test the reliability of items included in the factors,
which are identified in the factor analysis. This test is done to make sure that the measurements
are reliable for further uses. The results of Cronbach‟s alpha test are shown in the Table 4.2
below
Factors Variables
Cronbach's
Alpha
Corrected
item-total
Correlation
Cronbach's
Alpha If
item deleted
Overconfidence
OVC1
0.759
0.585 0.689
OVC2 0.507 0.733
OVC3 0.576 0.692
OVC4 0.566 0.698
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Factors Variables
Cronbach's
Alpha
Corrected
item-total
Correlation
Cronbach's
Alpha If
item deleted
Excessive
Optimism
EO1
0.762
0.599 0.691
EO2 0.605 0.684
EO3 0.499 0.747
EO4 0.462 0.705
Herding Behavior
HB1
0.791
0.624 0.728
HB2 0.596 0.742
HB3 0.582 0.749
HB4 0.601 0.74
Risk Attitude
PR1
0.768
0.547 0.723
PR2 0.55 0.722
PR3 0.572 0.71
PR4 0.605 0.692
Investment
Decisions
ID1
0.761
0.542 0.733
ID2 0.615 0.652
ID3 0.618 0.648
Investment
Performance
IP1
0.737
0.563 0.649
IP2 0.512 0.706
IP3 0.61 0.591
Table 4.2: Cronbach’s Alpha Test for items of factors
The table presents that Cronbach‟s Alpha indexes of all factors are greater 0.6, and the
corrected item-total correlation of all items are more than 0.30. The internal consistency of the

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items used to measure each factor was calculated using Cronbach‟s alpha, which is the
procedure of choice for investigating the internal consistency of items using Likert-type scale
(Walsh & Betz, 1995). Besides, Cronbach‟s alpha of each factor if its any item is deleted is less
than the factor‟s Cronbach‟s Alpha. Therefore the results of reliability analysis confirmed that
consistency is at an acceptable level for each factor ( see more in Apendix 4.2).
4.3 Factor analysis
The 22 questions of the questionnaire are designed to explore the levels of psychology
variables‟ influence on the individual investment decisions at the HOSE. Whereas, three
questions are created to identify the evaluation of investors about their own investment
performance.
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy.
.873
Bartlett‟s Test of
Sphericity
Approx. Chi-Square 1.515E3
df 231
Sig. .000
Table 4.3: KMO and Bartlett’s Test
The exploratory factor analysis (EFA) is used for the behavioral variables and investment
decision as well as investment performance to identify the factors which these variables belong
to. Here Bartlett‟s test of Sphericity and the Kaiser-Meyer-Olkin measure of sampling
adequacy (George & Mallery, 2003) are used. A measure of sampling adequacy of 0.873 with a
value of Bartlett‟s test with a high significant level (P <0.000), indicates the suitability of factor
analysis and the results is presented in table. These indexes prove that factor analysis for these
variables is totally suitable and accepted ( see more in Appendix 4.3).
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