Determinants of behavior intention to use derivative securities a study on individual investors behaviors in stock market of vietnam

UNIVERSITY OF ECONOMICS HO CHI MINH CITY
International School of Business
------------------------------

Trang Nguyen Thanh Phuong

DETERMINANTS OF BEHAVIOR
INTENTION TO USE DERIVATIVE
SECURITIES. A STUDY ON
INDIVIDUAL INVESTOR'S
BEHAVIORS IN STOCK MARKET
OF VIETNAM

MASTER OF BUSINESS (honours)

Ho Chi Minh City – Year 2018


UNIVERSITY OF ECONOMICS HO CHI MINH CITY
International School of Business
------------------------------

Trang Nguyen Thanh Phuong

DETERMINANTS OF BEHAVIOR
INTENTION TO USE DERIVATIVE
SECURITIES. A STUDY ON
INDIVIDUAL INVESTOR'S
BEHAVIORS IN STOCK MARKET
OF VIETNAM
MASTER OF BUSINESS ADMINISTRATION

SUPERVISOR: DR. Trần Phương Thảo

Ho Chi Minh City – Year 2018


Acknowledgement
I would like to express my sincere thankfulness to my supervisor, Dr. Tran
Phuong Thao, who made me believe in myself and gave me the possibility to
complete the thesis. Her guidance helped me in all the time of research and writing
this thesis. I am sure that this thesis would not have been possible without her
support.
I would like to express my gratitude to all staffs in ISB who supported
necessary materials and helped submit my papers.
My sincere thanks also go to friends and colleagues who participated in the
pilot study that led to the development of the final survey questionnaire and their
support over the time when I was busy to conduct the research.
Especially, I would like to give my special thanks my family for supporting
me spiritually throughout my life.

Trang Nguyen Thanh Phuong


Abstract
This study investigates the determinants of behavior intention to use
derivative securities on individual investor ‘s behaviors in stock markets of
Vietnam. Those determinants include attitude towards behavior, subjective norm,
perceived behavioral control. It also examines the effect of overconfidence,
excessive optimism, herd behavior, risk aversion toward attitude towards behavior.
An empirical test was conducted with a sample of 317 individual investors by

means of structural equation modeling. The results show that perceived behavior
control has the strongest impact on the three main factors affecting behavior
intention to use derivative securities with a coefficient of 0.426. The other two
factors, including attitude towards behavior, subjective norm, have a direct impact
on behavior intention to use derivative securities with coefficients of 0.356 and
0.216 respectively. On the other hand, overconfidence, excessive optimism, herd
behavior and risk aversion have direct effect on attitude towards behavior.
However, herd behavior and aversion effect attitude towards behavior with positive
coefficient while overconfidence, excessive optimism affect with negative
coefficient. Finally, age and education play an important role in behavior intention
to use securities derivatives while there is no difference between men and women
who intend to use derivative securities.

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Table of Contents
Acknowledgement ............................................................................................................. 1
Abstract ............................................................................................................................. 2
List of figures .................................................................................................................... 5
List of tables ...................................................................................................................... 6
List of abbreviations .......................................................................................................... 7
1.

Introduction................................................................................................................ 8

2. Theoretical background and hypotheses ....................................................................... 13
2.1. Foundational Theory ............................................................................................. 13
2.2. Research model and hypotheses ............................................................................ 16
2.2.1. Attitude towards behavior (ATB) .................................................................... 17

2.2.2. Subjective Norm (SN) ..................................................................................... 21
2.2.3 Perceived behavioral control (PBC) ................................................................ 23
2.2.4. Demographic factors .......................................................................................... 24
3. Research methodology ................................................................................................ 26
3.1. Research approach ................................................................................................ 26
3.2. Questionnaire design ............................................................................................. 28
3.3. Data collection ...................................................................................................... 32
3.4. Research Method .................................................................................................. 33
3.4.1. Pilot test ......................................................................................................... 33
3.4.2 Main survey test............................................................................................... 34
4. Data analysis and results .............................................................................................. 37
4.1. Descriptive statistics ............................................................................................. 37
4.2. Reliability Analysis ............................................................................................... 38
4.3. Exploratory Factor Analysis (EFA) ....................................................................... 40
4.4. Confirmatory Factor Analysis (CFA) .................................................................... 43
4.4.1. Composite Reliability...................................................................................... 43
4.4.2.

Convergent Validity of all variables ........................................................... 45

4.4.3.

Discriminant Validity of all variables ......................................................... 46

4.3. Structural Equation Modeling (SEM) .................................................................... 48
4.4. Indirect Effects of Behavior intention to use .......................................................... 49
4.5. Independent Sample T-test and Oneway Anova..................................................... 50
4.5.1 Gender ............................................................................................................ 50
4.5.2 Education ........................................................................................................ 51

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4.5.3 Age .................................................................................................................. 53
4.6. Hypothesis testing results ...................................................................................... 54
5. Discussion & conclusion ............................................................................................. 55
5.1. Discussion............................................................................................................. 55
5.2. Implications for managers..................................................................................... 57
5.3. Conclusion ............................................................................................................ 58
5.4. Limitations and directions for future research ....................................................... 59
REFERENCES................................................................................................................ 60
APPENDICES ................................................................................................................ 63
Questionnaire (English version) ................................................................................... 63
Questionnaire (Vietnamese) ......................................................................................... 67
A. Frequencies .......................................................................................................... 71
C. Reliability ............................................................................................................. 73
D. Factor Analysis ..................................................................................................... 81
E. Confirmatory Factor Analysis ............................................................................... 87
F.

Structural Equation Modeling ............................................................................... 93

4


List of figures
Figure 1. The theory of planned behavior – (Ajzen, 1991) ............................................... 14
Figure 2. Research model ................................................................................................ 17
Figure 3. Main steps of research process .......................................................................... 28
Figure 4. First Measurement Standardized Modelling ...................................................... 47

Figure 5. Structural Equation Model ................................................................................ 48

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List of tables
Table 1. Measurement scale............................................................................................. 30
Table 2. Sample size Criteria (Comfrey & Lee, 1992) ..................................................... 32
Table 3. Criteria for Measurement Model ........................................................................ 35
Table 4. Descriptive statistics .......................................................................................... 37
Table 5. Remiability Test Results .................................................................................... 38
Table 6. KMO and Bartlett's Test .................................................................................... 40
Table 7. Total Variance Explained ................................................................................... 41
Table 8. Pattern Matrix .................................................................................................... 42
Table 9. Value of Composite Reliability .......................................................................... 45
Table 10. Value of Average Variance Extracted .............................................................. 45
Table 11. Discriminant Caculating Result ........................................................................ 46
Table 12. Square root of AVE results .............................................................................. 46
Table 13. Regression Weights of Model .......................................................................... 49
Table 14. Indirect effects on Behavior intention to use .................................................... 50
Table 15. Independent Samples Test ................................................................................ 50
Table 16. Test of Homogeneity of Variances ................................................................... 51
Table 17. Anova tesing result .......................................................................................... 52
Table 18. Descriptives Statistics ...................................................................................... 52
Table 19. Test of Homogeneity of Variances ................................................................... 53
Table 20. Anova tesing result .......................................................................................... 53
Table 21. Descriptives Statistics ...................................................................................... 53

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List of abbreviations
No. Abbreviation
1

Meaning

AVE

Average Variance Extracted

ATB

Attitude Towards Behavior

2

CFA

Confirmatory factor analysis

3

CR

Composite Reliability

5

EFA

Exploratory factor analysis

6

HOSE

Ho Chi Minh City Stock Exchange

7

HNX

Hanoi Stock Exchange

12

TRA

Theory of Reason Action

13

TBC

Perceived Behavioral Control

14

TPB

Theory of Planned Behavior

SN

Subjective Norm

SEM

Structural Equation Modeling

15

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1. Introduction
Derivatives are a valuable financial instrument that depends on the price of
the underlying asset. Basically, derivatives can be understood as a type of contract
for a future but predefined transaction. Derivative instruments are conduct as a tool
used to manage and control risk. Specifically, derivative products are used to
prevent risk when asset values fluctuate. In addition, derivatives are considered as
hedging instruments against volatility of commodity prices. In the derivatives
market, there are two main markets: the financial derivative market and commodity
derivatives market. In this study, the author will focus on the financial derivatives
market on the stock market, exactly the Vietnam stock market.
To date, Vietnam stock market has been established for quite a long time, but
just over 11 years the stock market of Vietnam has a significant development; Two
stock exchanges have been established, namely the Ho Chi Minh City Stock
Exchange (HOSE) and the Hanoi Stock Exchange (HNX), a stock exchange

depository center has been established, nearly 89 securities companies are operating
and more than 700 companies have listed their shares and fund certificates on two
Vietnamese stock exchanges. By 2013, at the Ho Chi Minh City Stock Exchange,
the stock market capitalization has reached over $ 32 billion, equivalent to 25
percent of GDP in 2013, the number of accounts of investors reached over 1.3
million trading accounts, of which foreign investors had about 16,000 accounts,
compared to the end of 2007, the total number of securities trading accounts has
increased by more than 3.5 times and the number of accounts of foreign investors
has nearly doubled, proving that the demand of securities investors has increased
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significantly. The daily trading value of the two exchanges in the market has
reached over 5000 billion.
Although the Vietnam's stock market has been developing for more than 13
years, there is no derivative market based on securities tools to assist investors in
hedging price fluctuations. Macroeconomic uncertainty and severe financial risk
have negatively affected nearly all small investors trust the financial market. There
are only basic investment tools in the market such as stocks, bonds and fund
certificates. After a long period of preparation and completion, the derivatives
market will officially come into operation in the near future with the first derivative
traded futures contract. Although the derivatives market has been formed and
developed for a long time, but for the majority of investors this is still a relatively
new trading form. The emergence of these derivatives will make the stock market
more vibrant and diverse. On the other hand, it helps investors to improve their
knowledge and skills to develop the derivatives market later.
In the body of literature, there are a wide range of studies examined the
behavioral intention of customers including Jeong & Lambert (2001), Burton,
Sheather & Roberts (2003), Liu, Lu, Marchewka & Yu (2004), Amoako &
Gyampah (2007), Gu, Lee & Suh (2009), Han & Kim (2010). In the context of

financial market, the behavioral intentions have been examined in a plenty of
studies such as Berry, Parasuraman & Zeithaml (1996), Athanassopoulos (2000),
Auh, Bell, McLeod & Shih (2007), Keh & Xie (2009), Bolton, Bitner & Mende
(2013), Saeidi, Sofian & Saeidi (2015).

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In the aforementioned studies, the theories of behavioral have suggested the
author to identify and analyze the key factors that capture the behavioral intentions
of investors in Vietnam's derivatives markets. This study of behavioral intention is
conducted by using different approaches. The theory of planned behavior (TPB) has
been proven relatively effective predicting various human behaviors (Sheppard,
Hartwick et al., 1988). Furthermore, the TPB theory has shown to be one of the
strongest theories with multiple implications and it was mentioned in many studies
related to behavioral intention. Therefore, the identification of individual investor
behavior can be examined by the adoption of a behavioral approach to the study of
the financial derivatives market and the level of investor perception of different
derivatives markets.
Derivatives are used by large corporations and companies to manage
exchange rate risk, loans or financial expenses. Based on mentioned studies,
derivatives are very useful in risk management. Through the option call and put
option, market risks are prevented using forward and future contracts. Derivatives
are indispensable products in the deep, broad and diversified development of
financial markets. To date, derivatives have developed rapidly, are strong on a
global scale and play an increasingly important role in the financial and monetary
system. These tools show prominent features in risk prevention, meeting the needs
and interests of many market participants. However, it also shows the complexity
and if not good management can cause economic instability.
In Vietnam, derivative products originating from currencies and commodities

have been in use for many years. On commodity derivatives, the Buon Me Thuot
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coffee trading center was established in 2006 with the main function of organizing
the trading of coffee produced in Vietnam in the form of spot and forward delivery
(Forward contract). To date, the use of currency derivatives has been extended to
many domestic and foreign commercial banks, with a variety of instruments such as
swaps, options, future contract. The financial derivatives market is being prepared
for establishment and development in the near future. In order to help individual
investor familiarize with the new investment instrument, in the first phase of the
market operation, two basic futures contracts will be introduced including futures
on the stock index (VN30 and HNX30) and futures on government bonds. Other
derivative contracts on asset types will be issued later.
In the derivatives market, there are four main contributing factors to the
derivative market: infrastructure, legal framework, products and people (Hull,
2006). In recent years, the government has developed, developed and prepared the
legal framework and technical infrastructure to operate the derivatives market.
However, the government cannot upgrade human factors as they do with
infrastructure, legal framework or technical. There are many models of human
behavior, each of which is applied in different circumstances. Human behavior for
different problems can be predicted very differently. Similarly, in financial
environments, for different financial products, human behavior is also very different
(Mullainathan & Thaler, 2000; LeBaron, 2001; Shiller, 2002). In other words, if
individual investors are not involved in the derivative financial market, this market
will be ineffective and unable to grow in the future. In addition, the internal factors
such as education, experience, gender, culture, individual investors are also
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influenced by a number of psychological factors. Although individual investors
have gradually become more professional in investment, some empirical studies of
market performance show evidence that the VN-Index is not random. One of the
reasons is the existence of psychological factors affecting the behavioral intentions
of individual investors in the stock market (Phan & Chu, 2014). In accordance, the
decision of investors although based on reasonable analysis, is influenced by
psychological factors (Murgea, 2008, Sehgal & Singh, 2012).
Hence, this study is necessary to conduct in the current context of Vietnam to
understand the level of investors toward derivative financial instruments when the
derivative financial market is put into operation. The study also is expected to
identify factors that affect intention of investors in the use of derivative financial
instruments in Vietnam.
The purpose of this study is to explore the factors that influence the decision
to participate in the financial derivative market of the investor in Vietnam. On
August 10, 1977, the Derivative Market was officially opened. The Vietnamese
State Securities Commission has issued certificates of eligibility for trading of
derivative securities to five securities companies including Saigon Securities Inc.
(SSI), Vietnam Prosperity Securities Company (VPBS), Vietnam Securities
Corporation Vietnam Investment and Development (BSC), MB Securities (MBS)
and VNDIRECT Securities (VND). Hence, this study focuses on investors who are
dealing in these five securities companies.
The results of this study will help to learn about the behavior of investors in
the derivative securities market in Vietnam. Determining the level of impact of
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factors on the behavior of individual investors in the derivatives market is
important. It will help to capture the behavior of investors in the new derivative
market as in Vietnam today. This result is very important for both brokers as well as
the State Security Commission of Vietnam. Knowing the behavior of investors can

help them improve the intention to use derivative instruments in securities market to
manage and control risk in investing. This can help to create market liquidity as
well as increase the number of investors in Vietnam's stock market.
2. Theoretical background and hypotheses
2.1. Foundational Theory
The theory of planned behavior (TPB) was developed by Ajzen and Fishbein
in 1980. This theory is considered to be pioneering in the field of psychosocial
research and is widely applied in scientific research to learn about human behavior.
The main content is shown in the studies of Ajzen (1985, 1991, 2002). The
relationship between intention and behavior has been empirically tested in
numerous studies in many areas (Ajzen, 1988; Ajzen & Fishben, 1980; Canary &
Seibold, 1984; Sheppard, Hartwick, and Warshaw, 1988). It was developed from the
theory of reasoned action (TRA) by (Ajzen and Fishbein 1980).
Theory of reasoned action (TRA) focuses on understanding the motivational
factor of personal behavior consisting of two main components: attitude towards
behavior (AT) and subjective norms (SN). Although the TRA is widely accepted in
literature, the theory is still limited. Inability due to lack of opportunities or
resources such as time, capital, skills ...To overcome these limitations, Ajzen (2002)

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added another variable to the original TRA model, perceived behavioral control
(PBC) and this led to the theory of planned behavior (TPB).
Perceived behavioral control reflects the ease or difficulty of performing the
behavior and whether the behavior is controlled or restricted (Ajzen, 1991). The
TPB model is shown in figure 1.

Figure 1. The theory of planned behavior – (Ajzen, 1991)

According to the theory of planned behavior (TPB), behavioral control can
affect behaviors in two ways: PBC may affect intentions of behavior and PBC can
directly influence behavior. Both of these controlling effects may be related to the
course of action of investors. In addition, other factors that affect investors' actions
are internal factors and external factors. Internal factors include feelings, personal
knowledge, experiences and skills. External factors include financial resources, time
or partner (Ajzen, 2005). In TPB theory, the three main factors are behavioral
attitudes, subjective norms, and perceived behavioral control. These factors have
been proven and confirmed in numerous researches.
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Behavioral intentions have been predicted by attitudes, subjective norms,
perceived behavioral control in the past. The theory of plan has been tested for
many years and has been shown to be reliable, effective through numerous
empirical studies. TPB has been widely used in the prediction of human behavior in
business (Krueger & Carsrud, 1993), the study of bad habits (Chang, 1998) or
tobacco control behaviors for adults (Hu & Lanese, 1998). In addition to predicting
and controlling personal behavior, TPB is also used to predict behavior that benefits
the community. For example, research on resource sharing in the organization
(Bolloju, 2005) or decision making in human resource management (Carpenter &
Reimers, 2005). TPB is also analyzing the intention to use a variety of new forms,
such as the use of internet in shopping (Hsieh & Rai, 2008), the intention to use
technology devices in households (Pavlou & Fygenson, 2006), or intention to use
credit cards (Rutherford & DeVaney, 2009).
TPB is widely used in the financial and securities markets (Gopi &
Ramayah, 2007). Gopi and Ramayah (2007) use TPB to study the intent of online
home-based business, or use internet banking for securities trading (Serkan, 2004).
All of the above may indicate that TPB is a good model for predicting behavior. In a
famous study by East (1993), he used TPB to accurately predict the behavior of

securities investors in the short term. According to Ajzen (2005), in the short term,
TPB shows that "people intend to take action when they evaluate it positively, when
they feel social pressure to do it, and when they believe they have the means and the
opportunity to do it”. This view of motivation shows the ability to explain the main
factors that affect individual investment behavior.
15


The stock market in Vietnam has been developing for a long time, however,
very few studies have used TPB to study stock investment behavior. Most of the
previous studies focused on behavior finance theory, financial literacy or
demographic factor to investment behavior. On the other hand, derivative is an
effective risk management tool in securities trading has been recently applied in
Vietnam. This attracted the author to use TPB as a theoretical background for
developing model research and studying the behavior of intention to use derivative
in securities investment in Vietnam.
2.2. Research model and hypotheses
As mentioned above, TPB has many applications in analyzing human
behavior and has been tested in hundreds of studies worldwide. In this section, the
author proposes a research model to test the factors that influence the intention to
use derivative in securities investments. The main purpose is to determine the
factors that influence the intention to use as well as the relationship between factors
in the research model. In addition, the author identifies psychological determinants
that have an indirect effect on intention to use (Phan & Zhou, 2014). The research
model and hypotheses will be presented below:
Behavioral intentions according to the TPB theory are intentions to perform
some behavior, in this study the intention is to use. This makes sense behavior a
dependent variable in many experimental studies using TPB as the theory. Studies
of behavioral intent have been demonstrated and determined through many
empirical studies. According to Ajzen (1991), behavioral intentions have been

strongly influenced by motivation factors (elements in the TPB model). Behavioral
16


intentions imply that people will be willing to act or attempt to do something.
Therefore, the intention to use derivative indicates that investors are likely to use
derivative in securities trading.

Figure 2. Research model

2.2.1. Attitude towards behavior (ATB)
Attitude is described as the impact of each positive or negative emotion on a
particular behavior (Fishbein & Ajzen, 1980). Attitude of an individual is measured
by the belief and appreciation for that behavior. Consequently, attitudes have been
widely used to determine predictions of future behavior. On the other hand,
attitudes have been updated with new definitions as reaction of individual behavior
to different objects (Ajzen & Fishbein, 2000).
In other words, if a person is influenced by attitudes towards a particular
behavior, they will be intent on performing that behavior higher than others. In
contrast, individuals are not attracted by the behavior, they will not intend to do
that. There are many studies examining the impact of attitudes on behavioral
17


intention. The results show that there is a strong relationship between attitude and
behavioral intention. If an individual who has a positive attitude will tend to act. In
contrast, individuals with negative attitudes will have a tendency not to perform
such behavior, even criticize (Gibler & Nelson, 1998). Therefore, attitude is one of
the determinants of personal behavior. On the contrary, individuals with negative
attitude will have a tendency not to perform such behavior, even criticize or obstruct

(Gibler & Nelson, 1998). Therefore, attitude is one of the determinants of personal
behavior.
For the attitude towards behavior, Ajzen and Fishbein (1980) believe that the
attitude toward any concepts is one of the feelings about one's favourableness and
unfavourableness. Thus, attitude towards behavior is only the end result while there
are small factors that affect attitude towards behavior. Phan and Zhou (2004) have
identified four factors that directly affect attitude towards behavior, including
overconfidence, excessive optimism, herd behavior, and risk aversion. Thus,
attitude towards behavior is considered as a dependent variable influenced by four
psychological factors as follows:
Overconfidence is the expression of self-confidence behavior of some
knowledge or decision. Overconfidence has been studied extensively in the stock
market (Barberis & Thaler, 2003). In trading, many investors are confident about
their knowledge, their ability in reality is not so. Transaction results are far from
their confidence. However, they do not see this problem. Mostly, investors are
overconfident believe that they choose the best stock and the best time to sell the
stock for the highest profit.
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Excessive confidence influences their decision. Excessive confidence also
causes them to ignore other useful data in the investment decision that leads to their
erroneous investment decision (Odean, 1998; Wang, 2000; Gervais & Heaton,
2002; Grinblatt & Keloharju, 2009; Montier, 2009). Overconfidence also greatly
influences the use of derivative in securities transactions.
Most investors are overconfident about their ability, so they will not use risk
control measures in their trades, particularly derivative. An over-confident investor
performs high-frequency transactions and thus increases the volume and volatility
of the market while their expected returns decrease (Gervais, Heaton and 2002).
Therefore, the confidence of a person's ability to directly influence the investment

attitude, leading to more frequent transactions.
For the overconfident investor, they are too confident about their investment
information as well as their capabilities. This will cause them not to appreciate the
reality of the market as well as the stock they are holding. Excessive optimism is a
combination that holds overconfidence and over optimism. This is evident in bad
situations, especially when the market is on the decline. They always believe that
bad situations happen only in the short term, so it will not affect their portfolio
much.
Or they believe that their portfolios are very good, will rebound in a short
time so there is no need to sell (Wang, 2001, Gervais & Heaton, 2002; Johnson &
Lindblom, 2002). Excessive optimism also stimulates investors to increase the
number of portfolios because they believe that the market will improve and that
they will achieve high returns in the short run (Johnsson & Lindblom, 2002). The
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use of derivative in trading depends largely on the attitude of the investor. When
they feel optimistic, they will not need to use derivative, otherwise, if their
optimism diminishes, they will use derivative as a hedge.
In stock investment, herd behavior is the behavior of investors acting on the
behavior of others, or when heard from a certain investor, they will immediately
take action. In simple terms, investors copy someone else's transactions based on
the level of success of the other investment performance (Banerjee, 1992;
Bikhchandani & Sharma, 2000; Hwang & Salmon, 2004). If this happens in small
quantities, it will not affect the market.
However, if a large number of investors act according to other reputable
investors, it will affect the market. Stock prices may be overvalued leading to
increased investment risk. Investors of this type are called unreasonable investors.
Dependending too much on the individual or organization will lead to that
organization having a great influence on the market, thereby increasing investment

risk (Barber & Odean, 2009).
Herd behavior can greatly affect the behavior of investors. Investors who
have high herd behavior may not use derivative to manage risk. For investors with
low herd behavior, they will use derivative as a tool to control risk from their
behavior.
Risk in the financial sector is the uncertainty of an unexpected decision or
incident. Tversky and Kahneman (1974) propose prospect theory and reveal that
forecasting and forecasting under uncertainty do not usually follow probability
rules. Risk averse is a factor in prospect theory that determines that people tend to
20


risk averse in the "profitable zone" and risk seeking in the "losing zone" (Tversky &
Kahneman 1992).
Thus, for risk aversion investors, they prefer to look for risk, so they will be
more interested in the market fluctuations and high risk. Conversely, for investors
with low risk aversion, they only trade when they feel safe and secure (Olsen, 2007,
2008). The use of derivative in securities trading is also affected. Risk aversion does
not like derivative because they think that dealing with derivative is too safe and
profit will be low. Conversely, for the volatile market, derivative as a useful tool for
investors with low aversion risk.
H1: Attitude towards behavior positively affects the behavioral intention of
investors in using financial derivative instruments.
H1a: Overconfidence is negatively affects the attitude among individual
investors.
H1b: Excessive optimism is negatively affects the attitude among individual
investors.
H1c: Herd behavior is positively affects the attitude among individual
investors.
H1d: Risk aversion is positively affects the attitude among individual

investors.
2.2.2. Subjective Norm (SN)
One of the two major components of TPB is subjective norm. The subjective
norm is defined as an individual's perception of seeing most important people as
21


friends and family as a determining factor in their behavior. People with high SN
mean that their decision is influenced by the people who are important to them
(Ajzen & Fishbein, 1980). SN plays a very important role in decision making, and is
one of the main players in the TPB model. Specifically, for financial markets, if an
individual investor in the stock market witnessed a more important person than they
thought they should perform that action, they will have more motivation to make a
decision. On the other hand, people often think that when the important people
disagree with these activities, they will not intend to behave. More specifically,
even when a person does not want to do something, they can also be influenced to
do the behavior by the actions of others (Venkatesh & Davis, 2000). Friends,
parents, relatives, brokers or reputable financial experts can influence the decision
of the investor (Kalafatis et al., 1999).
Attitudes of others also influence both intentions and decisions. In particular,
the decision of the investor to choose a derivative financial instrument is affected by
the attitude of others. People who close relationship to the investor have a lot of
impact on the behavior of that investor. This means when others think that negative
for the tools, investor will be more likely to adjust their intentions of use. On the
contrary, the intention of an investor would increase if they were interested in the
financial instrument (Kotler & Keller, 2006; Rivis & Sheeran; 2003).
However, there are also studies that give different results in predicting the
effect of subjective norm on intention. The problem is that the causal relationship
between subjective norms and behavioral intentions is evidenced in various studies
(Teo & Lee, 2010). On the other hand, this relationship was also denied by other

22


studies (Lewis et al., 2003). Moreover, recent studies have also shown that
subjectivity is a different predictor of subjective norms for investors' intentions in
different regions (Wu et al., 2011).
However, despite different conclusions about the role of subjective norms
with behavioral intention, it may be possible to show a significant association
between subjective norms and behavioral intention. It can be predicted that if an
individual investor is affected by subjective norms, they may intend to use more of
those who do not suffer the same pressure.
H2: Subject norm positively affects the behavioral intention of investors in
using financial derivative instruments.
H3: Subject norm positively affects the attitude among individual investors.
2.2.3 Perceived behavioral control (PBC)
Perceived behavioral control is a complementary factor to overcome the
constraint on the TPB model, which is applicable in the case of individuals affected
by external factors (SN). Thus, individuals will feel more active in their decision by
reducing the pressure from SN (Ajzen, 2002). PBC is defined as perceived by
individuals as easy or difficult to carry out specific behaviors (Ajzen, 2005). In
other words, if the investor's PBC are stronger, they will be motivated more to
perform this behavior (Ajzen, 2005). In addition, perceived behavioral control is
defined as the degree to which he or she has control of internal and external factors
that facilitate or limit behavioral activity.
In addition, Ajzen (1991) built the PBC based on research and synthesis of
various historical data. Specifically, information is collected through personal
23