1. UNDERSTANDING INVESTMENT BEHAVIOR OF INDIVIDUAL INVESTORS: HOW
THEY HANDLE INVESTMENT DECISIONS? DO THEY ACT RATIONALLY?
a
b
Hayat, M. Awan
Khuram Bukhari
c
Bushra Ghufran
khurambukhari@bzu.edu.pk
a, b,c Institute of Management Sciences
Bahauddin Zakariya University, Multan.
ABSTRACT
Efficient market hypothesis states that the recent stocks prices reflect all the available information, so the proponents of EMH
suggest a passive investment tactic of indexing that makes no attempt to beat the market. While there are investors who have
doubts about the existence of efficient markets and they believe that they can beat the market returns by adopting certain
strategies and tactics. This research examines the investment behavior of individual investors. We specifically look into the
determinants of investment behavior of individual investors and their relative importance in shaping overall investment behavior.
The impact of investment behavior on investment decisions is also studied. We collected data by obtaining direct responses from
246 individual investors having their brokerage accounts maintained with brokers listed with KSE. We also obtained responses
from 28 brokers listed with KSE. We developed two separate research instruments administered at individual investors and
brokers selected using random sampling technique from four cities: Lahore, Islamabad, Karachi and Multan. We categorized
individual investors on the basis of demographics, level of investment and investment objectives and conducted analysis of
variance among responses. Responses obtained from individual investors based on structured questionnaire were analyzed
quantitatively while responses of brokers based on open ended questions are analyzed qualitatively. Different statistical tools e.g.
AHP, ANOVA, Means, Cross tabulation, Frequencies and Regression are used to obtain the results of the study. The software
packages used are SPSS 17.0, and Spread sheet. When we fitted regression model to study the impact of investment behavior on
decision making process of individual investor we found a significant relationship between the two. Findings suggest that
behavioral dimensions of investor involvement and overconfidence are significantly related to market sentiments. Findings reveal
that the behavioral trait of involvement is most significantly related to technical analysis We also found that behavioral
dimensions of risk attitude and overconfidence are significantly associated with fundamental analysis.
Key Words: Behavioral Finance, Investor Behavior, Technical analysis, fundamental analysis, Market sentiments
INTRODUCTION
Market participants have for a long time relied on the notion of efficient markets and rational investor
behavior when making financial decisions. However, the idea of fully rational investors who always
maximize their utility and demonstrate perfect self-control is becoming inadequate. In an efficient market,
investors would be rational, unbiased and consistent. They would make investment decision without
emotion or passion. Their choices would be based on a single goal of maximizing their expected utility.
However decision makers do not act the way traditional economic models assume. Contemporary
researches reveal the aspect that the investment selection process is more human than analytical. Feeling
of loss, pride and regret often override rationality. Finance research has often ignored the individual
investor‟s decision making process while taking financial investment decisions current study attempts to
understand the issue in hand.
Behavioral finance is an emerging science, a relatively new and developing field of academic study that
exploits the irrational nature of investors. In contrast to market efficiency theory, that suggests that the
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2. security prices incorporate all available information about the company and economy, and prices can be
regarded as the best estimates of accurate investment value at all times in the market, the base of
behavioral finance is that humans often depart from rationality in a consistent manner. Most of our
investment decisions are influenced to some extent by our prejudices and perceptions that do not meet the
criteria of rationality.
Behavioral finance concentrates on irrational behavior that can affect investment decisions and market
prices. It attempts to better understand and explain how emotions and cognitive errors influence investors
and the decision-making process. Many researchers believe that the study of psychology and other social
sciences shed considerable light on the efficiency of financial markets as well as help explain stock
market volatility and other anomalies. In global financial markets the use of approaches based on perfect
predictions, completely flexible prices, and the complete knowledge of the all the decisions of all other
players in the market are increasingly unrealistic. The contribution of behavioral finance is not to
diminish the fundamental work that has been done by proponents of efficient market hypothesis. Rather,
it is to examine the importance of relaxing unrealistic behavioral assumptions and make it more realistic.
It does this by adding more individual aspects of the decision-making process in financial markets.
Without these contributions of behavioral finance, certain aspects of financial markets cannot be
understood. Despite the importance of individuals‟ investment decisions, however, we know little about
the factors that influence them. Finance research has often ignored the individual investor‟s decision
making process while taking financial investment decisions hence there is research gap in this area. There
is need to develop behavioral paradigm to probe into the determinants of investor behavior and their
impact on individual investor‟s financial decision making process. The current study addresses the issue.
In developing countries stock markets do offer the opportunity for substantial profits to financial investors
and that some of these are beginning to assume a major role in the flow of savings, however their
operation and the nature of their stock price behavior needs to be more fully understood. In our study out
of three Pakistani Stock Markets we have picked the Karachi Stock Market, because it is the oldest and
the most developed market among all three and moreover the KSE remains the main centre of activity and
focus of attention because 75 to 80 percent of current trading takes place here. There are different types of
investors; two major categories are individual and Institutional investors. This study is particularly
focused on the individual investor‟s of Karachi Stock market and later the impact of individual investor‟s
investment decisions is analyzed. Pakistani stock market is considered to be highly volatile as it is highly
sensitive and reactive to unanticipated shocks and news and it takes no time to impact the market
activities. However at the same time Pakistani stock market is resilient, and that recovers soon after
shocks. Psychology of local investors is also critical. As some say, it is 90 percent psychology and 10
percent fundamentals. That is the reason that served as basic motivation behind the present study.
The research problem in hand is that what are the determinants of investment behavior of individual
investors? What is their relative importance in shaping investment behavior of individual investor? What
are the decision making tools and techniques used by individual investor? What is the impact of
determinants of investment behavior on individual investor‟s decision making process? Answering to
these questions is where the role of behavioral finance comes in as the modern finance theory fail to
explain the phenomenon.
This research is an attempt to understand the investment behavior of individual investor by identifying the
determinants of investment behavior. It not only seeks to identify but also to define the relative
importance of determinants of behavior in shaping the investment behavior of individual investor. This
research also attempts to understand the investment decision making process of individual investors by
identifying different tools and techniques of investment decision. Research also seeks to define the
relative importance of determinants of investment decision in reaching an investment decision.
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3. Furthermore present research identifies the impact of investment behavior of individual investor on
decision making process by validating the relationship between the two.
The prime objectives of the study are,
To identify the determinants of investment behavior and their relative importance in shaping the
behavior of individual investors
To study the impact of the determinants of investor behavior on investment decisions
In the light of these objectives our study tries to find answers to the following research questions,
What are the determinants of investment behavior of individual investor and their relative
importance in shaping investment behavior?
What is the impact of determinants of investment behavior of individual investor on investment
decisions?
In our study investor behavior is studied in terms of four broad behavioral dimensions of overconfidence,
investor involvement, optimism and risk attitude that are subdivided into different factors. We not only
identified the relative importance of each of the dimension in shaping the overall investment behavior but
also the relative importance of the sub-factors in shaping the dimension is also identified. We studied
three possible ways, of reaching an investment decision, opted by the investors that are: technical
analysis, fundamental analysis and market sentiments. We also identified the relative importance of each
decision making technique in reaching investment decisions. We also analyzed the variation among
responses of different groups of investors; differentiated on the basis of demographics, sociographics and
investment objectives.
This research helps identify the determinants of investment behavior of individual investor that affect the
financial decision making process of individual investor. The research helps better understand how
emotions and cognitive errors influence investors and the decision making process. The research also
helps explain that why investors make systematic errors in their investment decisions. If the investment
behavior and consistent human flaws can be predictable then it can be exploited for profit. Professional
investors if come to know about the behavioral traits, biases and errors of individual investors, they can
attempt to “get on the other side of the trade” and simply can earn profits at the cost losses of the
individual investors. Moreover such information can be useful for financial services firms in the process
of their product development and in defining their marketing strategies. This information can be very
helpful to regulators as well while formulating different policies and regulations they can apply such
knowledge to better educate the investors and to mitigate the biases to improve the welfare of individual
investors. Moreover the individual investors themselves can learn from their mistakes and behavioral
biases by identifying the cognitive biases and errors in financial decision making process individual and
can improve their investment behavior and can make optimal investment decisions. By understanding the
human behavior, attitude and psychological mechanisms involved in financial decision-making, standard
financial models may be modified to better explain the reality in today‟s developing markets.
THEORETICAL FRAMEWORK
Traditional Finance Paradigm
“Standard finance is the body of knowledge built on the pillars of the arbitrage principles of Miller and
Modigliani, the portfolio principles of Markowitz, the capital asset pricing theory of Sharpe, Lintner and
Black and the option-pricing theory of Black, Scholes, and Merton”, (Statman, 1999). These approaches
are extremely systematic and deem markets to be efficient. The traditional finance paradigm holds some
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4. suppositions about the “individual behavior” that should be possessed by the economic agent (termed as
homo-economicus in modern finance literature) so that the financial markets can be modeled and studied.
First, the “homo-economicus” has unlimited cognitive and computational capabilities and is a super mind
who takes all likely choices and their consequences into consideration (Simon, 1955). Moreover “homoeconomicus” only values money or consumption to maximize self-interest and the value so assigned is
not prejudiced by factors as temper, familiarity with a particular state of affairs, unexpected increases in
fear or regret etc and rectifies his beliefs in the approved manner with the reception of new information.
Furthermore the „homo-economicus‟ is either risk neutral or has an aversion to risk.
Efficient Market Hypothesis: Building Block of Standard Finance
Paradigm of Standard Finance is based on the most prominent theory of efficient market hypothesis that
was initially proposed by Samuelson, (1965). Ritter (2003) put in plain words that, “EMH, the building
block of modern finance, is based on the assumption that investors compete for seeking abnormal
profits”. This rivalry between investors drives prices to their “correct” value. “Efficient market hypothesis
states that financial prices incorporate all available information and prices can be regarded as optimal
estimates of true investment value at all times. The efficient market hypothesis is based on the notion that
people behave rationally, maximize expected utility accurately and process all available information”,
(Shiller, 1998).
Emergence of New Paradigm
Conventional finance tries to explain financial decision by considering that markets and many of its
participants are rational. However, real people like you and me cannot act rationally all the time as they
are affected by their moods, emotions, beliefs that mislead them and moreover the capabilities also use to
be limited so they tend to be irrational at times if not most of the time. Kahneman and Tversky, (1974,
1979) pointed out that, “people fail to update beliefs correctly and have preferences that differ from
rational agents”. According to Simon (1957) people have limited capacity of processing information in
solving complex problems. Moreover, “people have limitations in their attention capabilities and they do
take into account social considerations (e.g. by deciding not to invest in tobacco companies)”,
(Kahneman, 1973). In addition, “rational traders are bounded in their possibilities such that markets will
not always correct „non-rational‟ behavior”, (Barberis and Thaler, 2003). Hence, traditional theories may
give an incomplete and deceptive description of financial behavior. Financial economics is, perhaps, the
least behavioral of the various sub disciplines of economics. The finance literature reveals little interest in
investor decision processes or in the quality of judgment. As a result, it is nearly devoid of 'people'. But
trend is changing, because of the presence of variations in financial markets that are unexplained by
modern finance theory; the advent of behavioral concerns in finance has become inevitable.
Thomas Kuhn‟s classic “The Structure of Scientific Revolutions”, (1970) describes the present state of
the modern finance as; “the old paradigm of an efficient market is crumbling. But the outlines of a new
paradigm, the Behavioral Finance, are visible in the resulting cloud of intellectual dust”. The first cracks
in the standard finance edifice were discovered through the application of sophisticated econometric
techniques by standard finance pioneers. As early as 1977, Roll illustrated that, “the foundation stone of
standard finance, the CAPM was almost certainly unverifiable”. In 1980s and 1990s a number of
anomalies came on the scene that the traditional finance failed to explain. That simply suggests that
traditional theory is incomplete if not faulty. Moreover in 1992, Eugene Fama, the key proponent of
CAPM, withdrew his support from the model. So we need not have waited decades for this insight as the
limitations of efficient market theory have ever been quite visible to those who wanted to look into it.
Now finance is witnessing important changes, according to some even a paradigmatic shift, from the
traditional, neo classical mathematical modeling approach based on a representative, fully rational agent
and perfectly efficient markets (Muth, 1961; Fama 1970) to a behavioral approach based on
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5. computational models where markets are viewed as complex evolving systems with many interacting,
“boundedly rational” agents using simple “rules of thumb” trading strategies (e.g. Anderson et. al., 1988;
Brock, 1994; Arthur, 1995; Arthur et al., 1997; Tesfatsion and Judd, 2006).
Behavioral Finance
Approaches based on perfect predictions, completely flexible prices, and complete knowledge of
investment decisions of other players in the market, are increasingly unrealistic in today‟s global financial
markets. Behavioral Finance is a new paradigm of finance theory, which seeks to understand and predict
systematic financial market implications of psychological decision-making, (Olsen, 1998). The new
paradigm of behavioral finance seeks not to replace but to supplement the behaviorally incomplete theory
of finance now often referred to as standard or modern finance. Behavioral finance recognizes that the
existing paradigm can be true within specific boundaries. By understanding the human behavior and
psychological mechanisms involved in financial decision-making, standard finance models may be
improved to better reflect and explain the reality in today‟s evolving markets.
Behavioral finance introduces the behavioral aspects and focuses on the application of psychological and
economic principles for the improvement of individual financial decision-making process. Shefrin (2000)
wrote a book on behavioral finance and EMH titled "Beyond Greed and Fear". It basically provides a nice
introduction to behavioral finance. The key concept conveyed in it is that people are” imperfect
processors” of information and are usually biased, commit mistakes and have perceptual problems.
Currently, no unified theory of behavioral finance exists. Shefrin and Statman (1994) began work in this
direction, but so far, most emphasis in the literature has been on identifying behavioral decision-making
attributes that are likely to have systematic effects on financial market behavior. The paradigm of new
finance, “Behavioral finance” is no more into much controversy as it was before. Now theorists have
come to acknowledge the human behavior and its impact on the decision making process and derivation
of stock prices in the market. I believe there will be time when people will look back at the articles
published in the past 15 years and wonder what the fuss was about. I predict that in the not-too-distant
future, the term "behavioral finance" will be correctly viewed as a redundant phrase. What other kind of
finance is there? In their explanation, economists will surely include as much "behavior" into their models
as they observe in the real world, after all to do otherwise would be irrational.
Understanding Investment Behavior
Social psychology provides confirmation of a variety of societal effects that help better understand the
behavior of investors in context of equity markets. Individual investors appear to invest in a manner that
is inconsistent with the traditional paradigm. Specifically, they are underdiversified (Benartzi and Thaler
(2001)), loss averse (Odean (1998)), and overconfident (Odean (1999)). Barber and Odean (2000)
document that individuals trade too much and tend to hold on to loser stocks too long while selling
winners too early. Grinblatt and Keloharju (2001) find that traders are reluctant to realize losses, and often
trade for non-rational reasons, exhibited by reference price effects. There is even evidence that investor
moods, as influenced by cloud cover or number of hours of daylight, affect financial markets (see, for
instance, Hirshleifer and Shumway, 2003 and Kamstra, Kramer, and Levi, 2003). “People are limited in
their capacity for processing information, since they possess a limited working memory and limited
computational capabilities and are limited in their attention capacity and hence ability to perform multiple
tasks simultaneously”, (Kahneman, 1973). Miller, (1956) states, “we can process only seven (plus or
minus two) pieces or chunks of information at the same time”. Therefore, the cognitive load required for
complex decision problems often exceeds people‟s cognitive capabilities. To deal with such problems
people generally adopt simplifying rules-of-thumb, or heuristics, that may result in behavior that is not
fully rational (Simon, 1955, 1979, Newell and Simon, 1972, Tversky and Kahneman, 1974, Gabaix and
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6. Laibson, 2000). Motivated in part by the above evidence, theories incorporating cognitive biases have
found a prominent niche in recent finance literature.
The proponents of the traditional paradigm are of the view that it is quite possible that few agents in the
economy can make less than optimal investment decisions however it does not affect the overall
efficiency of the market as long as marginal investors that is, “the investor, who is making the specific
investment decision at hand, is rational”, exist in the market. Milton Friedman, one of the greatest
economists of the time raised the point that these are the rational investors who set the asset prices in the
market. But his argument has been criticized as some fundamental problems have been found regarding it.
Critics are of the view that, even if the prices of different assets are set only by “rational investors”, still
studying the practices of individual investors is of main interest. Recent market trends imply increased
participation by individual investors in the investment process. As financial markets become more
„peopled‟, their behavior, actions, reactions and perceptions have a continuous impact on the stock prices
that cannot be explained by traditional models. The behavioral quirks observed in individual investors do
manifest themselves on a much larger scale in the overall stock market in the form of pricing anomalies
and unexplainable movements in stock prices. Not only markets do not behave neatly as dictated by the
traditional market theories, but also there is strong evidence in the field of psychology and financial
research that individual decision makers do not behave in accordance with the tenets of expected utility
while making decisions under uncertainty (Kahneman and Taversky, 1979 and Machina, 1982).
Most of the financial decisions are made under situations with high degree of uncertainty and complexity.
Often we have to choose between many alternatives, with many possible uncertain outcomes and
probabilities, while many other (previous) decisions situations need to be considered as well. In such
situations the „homo-economicus‟ acts if it performs comprehensive search of all relevant alternatives and
examines all possible consequences by linking the current decision with other decisions in order select
the best possible choice. However, psychological work suggests that people are not able to behave in such
a way in many situations. People are limited in their abilities and capabilities to solve especially complex
problems (Simon, 1955, 1957, 1959, 1979, Arthur, 1994, Miller, 1956, Kahneman, 1973 and Conlisk,
1996). To deal with such problems people generally adopt simplifying rules-of-thumb, or heuristics, that
may result in behavior that is not fully rational (Simon, 1955, 1979, Newell and Simon, 1972, Tversky
and Kahneman, 1974, Gabaix and Laibson, 2000).
Theoretical Evidence on Behavioral Biases
Apparently, many investors have the tendency to believe that he or she perceives better than others
(Shiller, 1998) and also that they think of themselves to be above average and this basically result in
overconfidence and an excessive trade activity that can affect the stock prices. An influential and worth
mentioning research on the trading behavior of the individual investors has been conducted by Barber and
Odean, who obtained the record of the trade activity of some 35,000 investors, who had managed their
accounts at a discount brokerage. The authors (Barber and Odean 1999, 2000; Odean 1999) argued that
investors were found to be involved in excessive trading because of their behavioral trait of
overconfidence and that ultimately resulted in diminished returns. Asch (1956) talks about the tendency
of people to conform to the judgment and behavior of others while making an investment decision. It as
conformity bias that result in herding behavior. This herding behavior has been proposed as the source of
endogenous fluctuations (bubbles and crashes) in financial markets”, (Topol, 1991). Interestingly it
suggests that such market fluctuations are irrespective of extraordinary news or other events related to the
market rather these are the societal communication that serves the purpose. Social interactions and
recommendations exert a strong influence on the trade behavior of the investors that ultimately can have
an impact on the stock market. Shiller (1990) has highlighted the significance of the role of conversation
in diffusion of admired ideas in context of financial markets. Shiller and Pound (1989) surveyed
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7. individual investors and observed that most of the investors are attracted towards some particular stock as
a result of interpersonal communication. Oberlechner and Hocking (2004) examined the information
sources, news, and rumors in the foreign exchange market and derived an exciting result that the
information pace is rated high, on a scale of importance, as compared to trustworthiness of the source, and
the precision of information.
Another important phenomenon documented in psychology is the representative heuristic. Many studies,
for example, Tversky and Kahneman (1971, 1973), DeBondt and Thaler (1985), Lakonishok, Shleifer,
and Vishny (1994), Barberis, Shleifer, and Vishny (1998) explain that individuals expect that recent order
of generated data can by the representation of the key population parameters from which they have been
taken. Shefrin and Statman (1995) investigate the relationship between representativeness and variables
such as book to market equity, beta, and size, and find that investors rely on representative heuristics in
forming expectations because they tend to regard good stocks as the stocks of large companies. Shefrin
and Statman (1994) talks about the phenomena where investors give more weights to the recent
observations or simply believe that recent events are reversed in such a way that short run event be similar
to long term probabilities.
Shefrin and Statman (1985) put forward the theory of disposition effect that got immense acceptance.
They argued that investors have the tendency to sell their winner stock hurriedly while they keep on
holding loser stocks for long just to avoid the regret of committing mistake. Ferris et al. (1988) and Odean
(1996, 1998, 1999) also acknowledged the same phenomena using trade data. They explained that
investors usually evade selling loser stocks just to avoid pain of regret by not confirming the errors they
make also they rush to sell winner stocks so that they may avoid the regret if stock price falls later.
According to Bell (1982), studying regret is of interest to theorists only if decision-makers take steps to
evade regret. One tactic is to shift the responsibility for a decision onto others. People are found to have
fear of unknown. Huberman and DeMiguel (2006) argue that "familiarity breeds investment” and the
familiarity bias is more observed in terms of investing in domestic stocks. Empirical studies reveal that
individuals are found to have more distrustful expectations about foreign stocks as compared to local
stocks. “In international financial markets, investors tend to hold domestic assets instead of diversifying
across countries, a puzzle known as home bias”, (French and Poterba, 1991). Research also confirms that
firms have a propensity to float their stocks in countries where investors are more known with the listed
firms and closer culture match (e.g., religious and genetic similarities). Individuals usually favor those
investments that are familiar to them, and that have geographical and linguistic proximity (familiarity,
local, or home bias), (e.g., Coval and Moskowitz, 1999; Grinblatt and Keloharju, 2001; Huberman, 2001).
Barber and Odean (2000) studied the trade data from discount brokerage firm and found that average no.
of stocks hold by the investors at that brokerage firm was just 4.3 stocks per head that confirms the
phenomenon of under-diversification of portfolio. The phenomena of “mental accounting” (see Thaler,
1980, 1999 for a more extensive overview), also has an impact on the decision making process of the
investors. It explains that people tend to formulate and assimilate decisions in a narrow fashion instead of
taking into consideration a broader frame, (see also Tversky and Kahneman, 1981, and Kahneman and
Lovallo, 1993). “Mental accounting describes the tendency of people to place particular events into
different mental accounts based on superficial attributes”, (Shiller, 1998). The main thought behind
mental accounting is that decision-makers put different types of gambles into separate mental accounts by
ignoring the likely connection between the accounts and make use of simple “prospect theoretic decisions
rules” to each account separately. Such mental accounts are mostly isolated on the basis of content, but
they can be isolated with respect to time as well (Goldberg, von Nitsch, 2001). Kahneman, Knetsch and
Thaler (1990) conducted numerous experiments and confirmed the existence of behavioral bias of loss
aversion that affects investor behavior.
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8. Kahneman and Tversky (2000) edit the book, “Choices, Values, and Frames”, that talked about the
phenomena of decision under uncertainty. They pointed out that investors behave like risk averse in
winning situation and the same investors become risk seeker in case of losing situation and commit
mistake in their financial decisions. Kahneman and Tversky (1991) state that people gamble over their
losses and have greater inclination to hold on losers hoping that losses will be recovered soon. DeBondt
and Richard Thaler (1985) published, “Does the stock market overreact?” and stated that, “people
systematically overreacting to unexpected and dramatic news events results in sizeable inefficiencies in
the stock market”. Tetlock (2007) studied the impact of media on “Stock Market” and came up with the
finding that some pessimistic issue highlighted in media result in a momentary negative impact on the
asset returns that are reversed later more over they also observed that during media pessimism the trade
volume also use to be abnormally high or low. Grinblatt and Keloharju (2000, 2001), observed that sell
trades of individual investors are responsive to high past returns more as compared to buy trades.
To recap, we have limited time and cannot optimally analyze all information required for fully rational
decisions. Unlike the “homo-economicus” we are often not able to solve complex problems and rely on
heuristics instead. Moreover, we use mental accounting practices, where we consider decision problems
separately instead of taking into account the possible links between them, bracket decisions narrowly,
evaluate decisions too repeatedly, and use different mental accounts for different decisions. In some
situations, these heuristics and practices result in optimal behavior, but in other situations they do not,
yielding consequential biases in financial markets and thus leading towards less then optimal investment
decisions.
METHODOLOGY
Out of three Pakistani Stock Markets we have picked the Karachi Stock Market, to study the investment
behavior of individual investors, because it is the oldest and the most developed market among all three
and moreover the KSE remains the main centre of activity and focus of attention because 75 to 80 percent
of current trading takes place here. The listed brokers of KSE have maintained their brokerage houses not
only in Karachi but also in other cities as well. After selecting the stock market for our study then in the
next step we divided brokerage houses affiliated with KSE into four major clusters on city basis, Karachi,
Lahore, Islamabad and Multan. Then we selected respondents randomly from each cluster on the basis of
convenience.
Unit of analysis:
i)
Prime unit of analysis is Individual investor having an account maintained with the broker
listed with KSE
ii) Secondary unity of analysis are the brokers who are listed with KSE
In our research we use both quantitative as well as a qualitative method of analysis. In our study
quantitative method refers to the survey we implemented in the form of questionnaires, which are directed
at individual investor. We also opted for qualitative approach, in defining the determinants of investment
behavior and factors that may affect their financial decisions, by conducting face to face and telephonic
interviews with the brokers.
To test the above mentioned hypothesis descriptive information is collected, identifying the factors that
influence investors‟ financial decision making while taking an investment decision. Moreover stock
market outlook and their views about stock market volatility are also taken. Different statistical tools and
techniques e.g. AHP, ANOVA, Means, Cross tabulation, Frequencies and Regression Models are used to
obtain the results of the study. The software packages used are SPSS 17.0 and Spread sheet.
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9. Data Collection
Data for our study is primarily collected through secondary researches, preliminary interviews with the
investors and brokers and a survey in form of two questionnaires one in the form of open ended questions
for in-depth interviews with the brokers and the other one in more structured form for investor survey. We
have obtained 246 complete survey responses from individual investors and 28 successful interviews with
the brokers in four major cities. The questionnaires were distributed among individual investors in four
cities; Karachi, Lahore, Islamabad and Multan. 500 surveys were distributed to individual investors
during the period of September 2010-November 2010. Some questionnaires were mailed to the
respondents via courier. An electronic version was also sent via e-mail. In few cases the survey was self
administered while in most of the cases we facilitated the respondents while getting response from them.
290 individual investors responded, for a response rate of 58 percent. However; several questionnaires
were incomplete as many questions had been left unanswered. It happened mostly in self-administered
surveys. We used 246 questionnaires for analysis purpose. The response rate obtained from brokers was
100 percent.
Preliminary In-Depth Interviews
The focus of these preliminary interviews was to identify a comprehensive set of factors that are likely to
influence investor sentiment and investment decisions. A group of 25 participants, 20 average individual
investors and 5 brokers in stock market, were interviewed on face-to-face basis. The format was mostly
open-ended, allowing the participants to free associate. A “funnel technique” was used to elicit
information and to generate a list of factors and anecdotal information that was used to develop a survey
that was tested on a large sample. These preliminary interviews and discussions were used to identify
recurring themes. Recurring themes were identified and were given distinct names. These preliminary
interviews with individual investors and brokers proved to be of great help for the development of the
research instruments, used in the study, related to individual investors and brokers.
Interviews with Brokers
A questionnaire was particularly designed to take responses from the brokers regarding investment
behavior and decision making style. The underlying objective was to probe into the characteristics and
behavioral aspects of the individual investors and that how they reach their investment decisions. The
survey gave insight about the irrational decision making process and different heuristics adopted by the
most of the individual investors. The survey was conducted also to get insight of brokers‟ view point
about the performance of the stock market and reasons of Pakistani stock market volatility. These
interviews are conducted with the help of questionnaire containing all open ended questions that were
developed as a result of the preliminary interviews with brokers and investors and also with the help of
existing research work done on the issue. About half of the interviews with brokers were completed
telephonically while in other cases brokers were sent questionnaires via courier and e mail that were well
responded.
Investor survey
Responses were taken from four cities: Islamabad, Lahore, Multan and Karachi. We used survey method
to collect primary data because it is their direct response that helps us develop an understanding of the
importance of each popular theme in overall decision making process, since no ideas and propositions are
put in the respondents‟ minds. Through the survey we strived to determine how well the practical
decision- making framework and behavior of investors in reality are consistent with the existing theories
of finance. Preliminary interviews and existing research studies helped identifying recurring themes and
factors influencing financial decision making process. These recurring themes are given distinct names
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10. and analyzed with the help of survey instrument targeted at individual investors. The survey instrument
consisted of structured questions focusing on investor sentiment, market and individual stock features that
had been identified based on secondary research and in-depth interviews. Demographic, psychographic
and sociological factors were also taken into account. The survey instrument was based on closed-ended
questions. Respondents were given multiple choices to choose their response from. Some rating questions
were also part of the survey where respondents were asked to rate their response on a 7 point likert scale.
There were some situational questions in the survey as well where respondents were asked to choose
between different options based on different situations. Some questions were related to the factors that
play an important role in the stock selection process. Some questions were targeted to probe into the
personality traits of the investors.
DATA ANALYSIS
This section presents the detailed discussion and analysis of the questionnaires administered to brokers
and individual investors. The purpose of each question as well as the results obtained from individual
investors and brokers are described. It also includes statistical analyses of the questions. The data
collected to study investment behavior and decision making style of individual investor is analyzed using
software packages SPSS and Spread Sheet. We used AHP to find the relative importance of different
behavioral traits of the investors in contributing overall investment behavior. We applied AHP on
determinants of investment decision. Analytic Hierarchy Process (AHP) is one of Multi Criteria decision
making method that was originally developed by Prof. Thomas L. Saaty (***). In short, it is a method to
derive ratio scales from paired comparisons. We did AHP with Spread Sheet. To analyze and represent
responses of the investors we also made use of frequency tables that is basically a representation, either in
a graphical or tabular format, of observations within a given interval. We made use of cross tabulations to
check of the relationship between specific variables. We conducted regression analysis to determine the
nature of the relationship between two or more variables; it is concerned with the problem of describing
or estimating the value of the dependent variable on the basis of one or more independent variables.
DISCUSSION OF THE INTERVIEWS WITH BROKERS
In order to probe into the investment behavior of individual investor we conducted detailed interviews
with the brokers listed with KSE. The main thought behind it was to find out brokers‟ views about
investors‟ decision making style with its link to investment behavior. A separate questionnaire was
developed that was composed of open ended questions in order to probe into the minute details of the
whole phenomena. Here is the discussion of the responses of the brokers.
We asked brokers to discuss about individual investors that in their opinion how individual investors
make their investment decisions, do they go for „fundamental analysis‟, „technical analysis‟ or „market
sentiment‟ for selecting a stocks and that what is more important to them. We got mixed responses
regarding this question but we‟ll discuss what majority says. Majority of the investors stated that
investors do go for fundamental analysis, technical analysis and also follow market sentiments. They said
investors do not follow a single technique for making a stock selection rather their investment behavior is
influenced by all three techniques for reaching an investment decision but they also clearly stated that
some give more importance to fundamental analysis some give more importance to other methods of
reaching an investment decision according to their investment objectives and behavioral traits. Some
brokers stated that majority of investors follow market sentiments, even one broker said that roughly 60
percent of the investors follow sentiments and do not conduct fundamental analysis and technical
analysis. Some brokers stated that individual investors believe that market goes after news and there is no
use of fundamental analysis or technical analysis.
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11. Few brokers stated that investors can be categorized into two main categories on the basis of their
investment horizons: short term investors and long term investors. They further stated that investors who
have short term investment horizons are more actively involved and they give more importance to
sentiments in terms of news and technical analysis in terms of looking into daily price fluctuations and
trade volume while those with long term investment horizons give more importance to fundamental
analysis while making an investment decision. They also stated that big investors with greater level of
investment give more value to fundamentals as compared to technicals and sentiments while making an
investment selection decision. They also stated that some unsophisticated investors with lack of education
usually go after market sentiments and ask for advice and recommendations from other investors and
brokers while those who are well educated do analyze company statements a little if not in detail. To
conclude we can say that investors do not follow fundamental analysis or any other method solely but
they follow all the three fundamental analysis, technical analysis and market sentiments for an investment
decision varying in degree of intensity of importance. The level of importance depends on their
investment horizon and objectives, their investment level and their level of sophistication in terms of
education. Brokers were asked about the sources of information of investors and that from where they get
ideas, tips and recommendations for investment. Responses to this question revealed that some investors
search for proper information from established sources e.g. Books of companies, Business Recorder,
Newspapers, CNN, BBC etc. Brokers stated that for ideas, tips and recommendations investor usually
contacts the brokers with whom he has opened his investment account and shares his views with them
before making an investment decision. They further stated that investors make discussions with other
investors and friends to get investment ideas and to seek for investment recommendations.
Brokers were also asked about the risk preferences of investors. Majority of the brokers were of the view
that investors are risk averse usually but as there are individual differences and few investors are risk
takers as well who make risky investments for enjoyment but majority has been found to have an aversion
to risk until and unless they are well compensated for bearing extra risk. They further explained that this
is the risk averse nature of investors due to which they make investments in less risky sectors and buy the
stocks of companies they are familiar with because they have the fear of unknown. This fear of
uncertainty leads them to make less risky investments.
Brokers also confirmed the existence of the tendency to have self-attribution for profits and blaming
others for less successful investment in investor behavior. They stated that there are very few investors
who consider themselves responsible for their less successful investments usually they are found claiming
that they have been given wrong recommendations, the market in general performed poorly, political
turbulences played their role or it was mere bad luck that make them face losses. They further stated that
in case if they make profits over their investments they take all the credit by themselves and consider that
the success is due to their own prudence and better decision making ability. They further stated that very
few investors give credit of successful investment to market conditions or better recommendations. To
conclude brokers‟ statements in one sentence we can state that investors have self attribution tendency in
case of profitable investments and others attribution in case of less successful investment.
During our preliminary interviews with brokers and investors we found investors claiming losses over
their investments. We asked brokers about the reasons of less successful investments by individual
investors. Majority of the investors attributed it to greed and fear factor that leads investors make
irrational decisions and ultimate result is losses. Brokers also revealed that inexperienced and less
sophisticated investors tend to follow market sentiments more than others and make investment decisions
by looking into the behavior of other market participants without properly evaluating all the possible
investment opportunities and make less than optimal investment decision. Moreover brokers clearly stated
that investors sell and buy stocks being emotional and thus make losses.
INVESTOR SURVEY
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12. Responses were taken from four cities: Islamabad, Lahore, Multan and Karachi. 25.2% of the total
responses were obtained from Islamabad and 27.2% each from Lahore and Multan and rest of the
responses (20.3%) were taken from Karachi.
Investor Profile
Following is the background description of the individual investors,
Table: 1
Male
97.2%
Female
2.8%
<30
20.7%
30-50
55.3%
>50
24.0%
Single
27.5%
Married
62.5%
Divorced
7.0%
Widowed
3.0%
Primary-Middle
5.3%
Matriculation-Intermediate
23.2%
Bachelor-Master
71.5%
Salaried Individual
46.3%
Self Employed
36.2%
Retired
14.2%
Student
1.6%
Un-employed
1.6%
<5
63.4%
5-10
22.0%
10-30
11.8%
>30
2.3%
<10
63.4%
10-20
32.9%
>20
3.7%
1
59.9%
2
20.9%
Gender
Age
Marital Status
Education
Occupation
Income
Investment Experience
No. of Accounts
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13. 3
4
3.0%
<20
2.3%
20-30
60.6%
30-40
14.6%
41-50
7.6%
50+
Investment Age
16.2%
14.9%
Determinants of Investment Behavior of individual Investor
The in-depth interviews and secondary research identified 4 multi-items broad dimensions of investor
behavior that could have an impact on their investment decisions. These 4 dimensions of investment
behavior are; Overconfidence, Investor Optimism, Investor Involvement and Risk Preferences, that are
further divided into different factors and respondents were asked to rate each factor. On the basis of the
overall responses of the investors and the ratings that they assign to the factors of the each dimension
“Analytical Hierarchical Process” (AHP) determined the relative weights for each dimension of the
investment behavior and priorities them in terms of their level of contribution in the formation of behavior
of the investor. AHP determined that overconfidence carries more than 50% weight, so it is the most
prominent behavioral dimension that has greater impact in the formation of overall behavior of the
investor while other three dimensions have relatively similar weights between 10 to 20 percent.
Market Knowledge
17.48%
Quick Money
79.61%
Trade Activity
20.39%
Risk Taking
23.81%
Stable Returns
28.80%
Enjoyment from
Risky Trade 8.49%
Keep Invested
47.06%
Increased Investment 17.55%
Price Increase
Expectation 22.20%
Investment
Behavior
Stock Picking
21.96%
Familiarity Bias
38.89%
Involvement
17.84%
Specific Skills
32.41%
Self-Control
28.15%
Overconfidence
50.42%
Index Recovery
13.19%
Risk Attitude
17.80%
Optimism
13.96%
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14. Figure1: Graphical Presentation of the AHP results of Q no. 18
First section of question no. 18 probes into the behavioral dimension of overconfidence. This dimension
is divided into four main factors. These four factors are measured with the help of four separate
statements. Again with the help of analytical hierarchical process we determined the relative weieghts of
each factor of the dimension of overconfidence. In the overall dimension of overconfidence the most
prominent factor is the confidence on specific skills that result in successful investment, as greater
weights (approx 32%) are assigned to this factor, while on second rank there comes factor of self-control
with approximate weights of 28%. On third rank is the stock picking ability with weights of 21.95% while
on fourth rank there comes the factor of confidence on market knowledge with weights 17.48%. Second
section is about investor optimism that is measured in terms of investor‟s outlook of the stock market.
The analytical hierarchical process determined that investors‟ determination to stay invested in the stock
market is the most important behavioral factor that shows their optimism about stock market. So
according to AHP this factor is assigned first rank with weights of 47.06%, while on second rank there
comes investors‟ expectations about an increase in the stock prices with weights of 20.20%. Investors are
not found to be much interested in increasing their investments and not much hopeful about the recovery
of the index if there comes a down fall. So these two factors are not much contributing towards the
formation of optimistic behavior of the investor rather these two factors depict investors to be little
pessimistic about the market so these factors (increasing investment and index recovery) are given third
and fourth rank with 17.54% and 13.20% respectively. In the third section of we studied the dimension of
involvement. To measure the overall level of involvement of investor in trading in stock we picked two
factors, level of trade activity and inclination towards making quick money. On the basis of the responses
of the investors AHP determined that the attitude of making quick money has the highest weights
approximately 80% while trade activity is at second rank with weights of 20% approx.
Fourth section measures the fourth dimension of the investor behavior that is risk preferences/attitude. We
measured this dimension using different factors whose relative weights are determined using AHP. We
found that investors have greater fear of un-known and uncertainty and to avoid it they make investments
in the stocks of the companies they are familiar with. The factor of familiarity bias gets the highest rank
among all four factors with weights of 38% approx. The analytical hierarchical process assigns second
rank to the tendency of investing in stocks with stable returns with weights of about 28%. These two
factors basically reveal the tendency of risk aversion of the investor. While the other two factors that are
assigned with third (risk taking) and fourth (enjoying risky trade) measures the risk loving attitude of the
investors. The low weights of these factors basically tells us that investors are not risk loving rather the
tendency of risk aversion is higher among the investors as compared to risk loving attitude. If we look at
the risk preferences as a whole, these four factors and their relative weights tell us that investors are risk
averse not risk seeking or risk indifferent.
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15. We also calculated the Global Weighted Indices of the determinants of investor behavior. Results are
summarized below,
GWI of the Investment Behavior
Dimensions
Index Recovery
Increased Investment
Price Increase Expectation
Stay Invested
Optimism
Enjoyment from Risky Trade
Risk Taking
Stable Returns
Familiarity Bias
Risk Attutude
Trade Activity
Quick Money
Involvement
Market Knowledge
Stock Picking
Sel-Control
Specific Skills
Overconfidence
0.018416628
0.024492525
0.030989385
0.065697285
0.1396
0.01511982
0.042388171
0.051261062
0.069223845
0.178
0.036363852
0.14201856
0.1784
0.088120845
0.110661184
0.141875811
0.163371026
0.5042
Figure 2: GWI of Behavioral Dimensions
In Q no. 18 investors were asked to rate different statements, regarding investment behavior, on
1(Strongly disagree) to 7(Strongly agree) point likert scale. Results are summarized here,
Table 2: Frequency Results for Behavioral Dimensions
Behavioral Dimensions
Statements
1
2
3
4
5
6
7
Total Frequency
Overconfidence
18A1
1.6
1.2
3.3
17.9
19.9
27.2
28.9
100%
18A2
2.0
2.0
0.8
7.7
11.8
25.6
50.0
100%
18A3
1.6
3.7
5.7
9.3
21.5
19.1
39.0
100%
18A4
6.1
5.3
11.8
17.9
17.1
17.9
24.0
100%
18B1
1.2
2.8
6.5
8.5
19.5
19.9
41.5
100%
18B2
26.4
9.3
9.3
12.2
16.3
11.8
14.6
100%
Optimism
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16. 18B3
9.3
12.2
16.3
11.8
14.6
100%
25.6
17.5
11.4
28.5
6.9
5.7
4.5
100%
18C1
3.7
2.8
7.3
12.2
17.9
16.3
39.8
100%
18C2
2.0
2.0
11.4
13.8
19.1
23.6
28.0
100%
18D1
53.3
15.0
8.9
6.5
7.3
6.1
2.8
100%
18D2
1.6
4.9
6.1
15.0
16.7
26.8
28.9
100%
18D3
9.3
18.7
10.6
11.0
29.3
15.0
6.1
100%
18D4
Risk Preferences/Attitude
9.3
18B4
Involvement
26.4
9.8
14.2
19.1
4.9
4.9
21.5
26.6
100%
Respondents were asked to rate four factors, described in statements from 18A1 to 18A4, on a 1(Strongly
disagree) to 7(Strongly agree) point scale. If the investors give high ratings to these statements it means
they have high level of overconfidence that can impact their investment behavior. In first statement about
the confidence of investor in having better stock picking ability than others, 28.9% (highest frequency) of
the investors showed strong agreement with the statement by giving a rating of 7 while just 1.6% of the
investors strongly disagreed with the statement. Majority of the investors (76%) agreed about their better
ability of making stock selection better than others by giving ratings of 5 or more. In 18A2 investors were
asked about how much they are agreed that they control their investment decisions and are fully
responsible for them, 50% of investors gave the highest rating of 7 while just 2% gave the lowest rating
of 1. Majority (87.4%) of the investors gave rating of 5 or above. In 18A3 39% (highest frequency) of the
respondents gave a rating of 7 and showed that they are strongly agreed with the statement that their past
investment successes were, above all, due to their specific skills. Just 1.6% (lowest frequency) of the
respondents showed that they strongly disagree with the statement and gave a rating of 1. 20.3% of
respondents gave it a rating of 4 or less while 79.7% of investors showed they agree with the statement
and gave a rating of 5 or above.
Respondents were also asked that how much they agree with the statement that they have complete
knowledge of the stock market. 24% (highest frequency) of the investors showed that they are strongly
agreed and gave a rating of 7 while just 6.1% of the investors gave a rating of 1 thus showing they are
strongly disagreed. 41.1% of the respondents gave a rating of 4 or less while 58.9% of the respondents
gave it a rating of 5 or above thus by agreeing with the statement. The frequency results of these four
statements tell us that investors have high level of overconfidence as there is greater level of confidence
on their stock picking abilities (18A1), high level of self control (18A2), greater level of self-attribution of
successes (18A3) and greater confidence of having market knowledge (18A4) as majority of investors
gave rating of 5 or above in case of each statement.
Optimism of investors is measured with the help of four statements from B1 to B4. First statement asks
investors that do they think they will stay invested in the stock market. In response to this statement
41.5%, the highest frequency in this case, of the investors were strongly agreed that they will stay
invested in the stock market while just 1.2% of the investors strongly disagreed and gave the lowest
possible rating of 1. However majority of the investors, 80.9%, gave rate of 5 or above. In statement 18B2
investors were asked about the likelihood of increasing investment in next 12 months. 26.4% of the
investors strongly disagreed depicting that they do not have any plan to increase their investments in stock
in next 12 months. However 14.6% investors strongly agreed with the statement. We observed that
majority (57.2%) of the investors gave rating of 4 or less. When asked whether they agreed that stock
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17. prices would rise for the next 12 months, 26.4% of the investors gave the lowest possible rating of 1 and
showed their strong disagreement with the statement while 14.6% of the investors were strongly agreed
with the statement. But on the whole more than 50% of the investors gave rating of 4 or less. Investors
were also asked about their opinion about a decrease in index and that do they think it will recover in few
days. 25.6% of the investors strongly disagreed with the statement and gave it a rating of 1 while 4.5% of
the investors gave it a rating of 7 and showed that they are strongly agreed. 83% of the respondents gave a
rating of 4 or less while 17% of the respondents gave a rating of 5 or more. If we analyze the whole
behavior and responses to these statements we can conclude that majority of investors do not believe that
stock prices will increase in next 12 months, also they do not think that if index has decreased in last 3
years it will be recovered soon so they do not want to increase their investments in stock in next 12
months rather they just want to keep their existing investments in stocks. So investors are not much
optimistic about the market rather they are seemed to be pessimistic. One possible reason can be the
dismal market conditions at the time the responses were taken.
Third section of Q no. 18 is composed of two statements. In the first statement investors were asked that
how much they are agreed with the statement that they are actively involved in trade activity. In response
to this statement 39.8% of the investors gave the highest rating of 7 while just 3.7% strongly disagreed
with the statement however majority agrees with the statement. In the second statement investors were
asked that do they agree with the statement that they make investment for making money quickly. 28% of
the investors strongly agreed with the statement that they make investment for making more money
quickly while just 2% of the investors strongly disagreed. 70.7% of the investors agree with the statement
and gave rating of 5 or more. By analyzing frequencies of responses we can conclude that most of the
investors are actively involved in trade activity because they want to make quick money and want to get
rich quickly.
In last section of Q no. 18, four statements from 18D1 to 18D4 were formulated to measure the risk
preferences of the investors. In first statement investors were asked that do they make risky investments
for enjoyment, in response to this statement 53.3% of the investors strongly disagreed with the statement
and gave lowest rating of 1 while just 2.8% of the investors gave a rating of 7. However 83.7% of the
investors gave rating of 4 or less. This shows majority disagrees with the statement that their motivation
behind trading in stocks is not enjoyment. This finding is also consistent with the previous finding that
investors trade for getting rich quickly not for fun. In response to the statement 18 D2, 28.9% of the
investors were strongly agreed with the statement that they prefer investing in companies they are familiar
with while just 1.6% showed strong disagreement. 72.4% of the investors gave rates of 5 ore above
showing that majority has the tendency to investing in familiar companies only. In response to statement
18D3, 9.3% of the respondents strongly disagreed with the statement while 6.1% of the investors strongly
agreed that they are risk takers. 29.3% (highest frequency) of the investors gave rating of 5, thus by
agreeing that they are risk takers. On the whole 50.4% of investors gave rating of 5 or above while 49.6%
of investors gave rating of 4 or less. 25.6% of investors gave the highest ratings and showed strong
agreement with the statement that they prefer investing in companies with stable returns even if lower
while just 9.8% of the investors gave the lowest rating of 1 and showed that they are strongly disagreed
with the statement. 52% of the investors gave ratings of 5 or above. If we analyzes the results of these
four statements collectively we can conclude that majority of investors are risk averse who do not prefer
making riskier investments. Rather they prefer investing in familiar companies that give stable returns
even if lower.
We also obtained ANOVA results to check the responses of investors from different age groups,
occupation groups, education level, income level, investment experience, investment level and age of
investment etc. The significant differences about the dimension of overconfidence among these groups
are mentioned here. When we analyzed the responses of each age group about each statement from 18A1
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18. to 18A4 then we observed significant differences in their responses to the statements 18A1 and 18A4. We
found that investors from age group 50+ gave higher rating to the statement 18A1 as compared to the
other two age groups (<30 and 30-50 with p values 0.020 and 0.022 respectively). It simply depicts that
investors (50+) have greater level of confidence in their stock picking ability as compared to other two
age groups (<30 and 30-50). No significant differences among responses of the other age groups
regarding this statement came into notice. In case of statement 18A4 (p values .005 and .002
respectively), investors with ages 30-50 and 50+ gave higher rating, showing their opinion about having
complete knowledge of stock market as compared to investors with ages <30. We can state that investors
with ages 50 or above are having higher level of overconfidence as compared to the other two age groups
while in other two age groups (<30 and 30-50 with p values .013 and .029 respectively) no significant
differences regarding the dimension of overconfidence came into observation. We also probed into the
responses of investors from different occupation categories and found that salaried individuals have
greater tendency of believing that their past successes are because of their own specific skills as compared
to self-employed and retired individuals (p values .020 and .033 respectively).
We also analyzed the responses of investors, regarding overconfidence and found that investors with
income 10 to 30 lac gave higher rating, as compared to other investors with incomes <5 and 5 to 10 lac, to
statement 18A1( p values 0.06 and 0.048 respectively) and 18A3 (p values 0.021 and 0.038 respectively),
depicting that they have higher level of confidence on better stock pick ability and specific skills. The
mean differences clearly depicts that investors with incomes 10 to 30 have higher level of overconfidence
as compared to those with income <5 lac and 5 to 10 lac (p values 0.001 and 0.025
respectively).Responses to the statements 18A2 (p value 0.038) and 18A4 (p value 0.036) revealed that
investors with income 10 to 30 lac have higher level of self-control and also they are more confident
about having complete knowledge of the market as compared to investors with income <5 lac.
We also found significant differences in responses of the investors with different level of experience of
investing in stocks. The mean differences, at statistically significant levels, suggest that investors with
investment experience of 10 to 20 years and more than 20 years are more overconfident as compared to
the investors with investment experience of less than 10 years (p values 0.001 and 0.016 respectively).
Responses of statements 18A1 and 18A4 clearly reveal the behavioral aspect of investors with experience
of more than 20 years as compared to investors with experience of less than 10 years have higher level of
confidence on stock picking ability (p value 0.016) and on having complete market knowledge (p value
0.000). Though investors are not much optimistic but among all three age groups investors with ages
more than 50 are more optimistic as compared to the other two age groups <30 and 30-50 (p values 0.001
and 0.028 respectively). In response to the statement about keeping investment in stocks, investors with
ages 50+ and 30-50 gave relatively higher rating as compared to investors with ages >30. Findings also
suggest that investors with ages 50+ plan to increase investments in stocks in next 12 months and also
they believe that if index has decreased it would be recovered soon, as compared to investors with ages.
When we analyzed investors from different income groups we found that investors with income >30 lac
believe index will be recovered in few days by giving higher rating to statement 18B4 as compared to
investors with income 5 to 10 lac and 10 to 30 lac (at the statistical significance level of .045 and .006
respectively). Also investors with income >30 lac plan to increase their investment in next 12 months, as
they gave higher rating to statement 18B2 as compared to investors with income <5lac and 5 to 10 lac
(significance levels .032 and .027 respectively). However no significant differences among investors with
>30 and 10-30 lac, about increasing investment in next 12 months came into notice. When we analyzed
the responses of investors with different occupations then interestingly retired individuals are found to be
more optimistic than self-employed individuals and salaried individuals (p values 0.002 and 0.003
respectively). Findings revealed that retired individuals strongly endorsed that they will stay invested in
stocks as compared to self-employed and salaried individuals. This is also because retired individuals are
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19. not much involved in short term profit seeking investment objectives. They mostly invest for long term or
for dividend purposes. Retired individuals plan to increase their investments in the stocks as compared to
students. This finding is also consistent with the previous finding that investors with ages 50+ are more
optimistic as compared to those with ages <30 years.
We also studied the responses of investors with different level of experience of investing in stocks and
observed that investors with investment experience of 10 to 20 years are relatively more optimistic as
compared to those with <10 years (p value 0.000), and they plan to keep the existing investment and also
plan to increase their investments in stocks in next 12 months because they believe that prices of stocks
are likely to increase in next 12 months. Again this finding is consistent with the previous finding that
investors with ages 50+ are more optimistic. We also studied the responses of investors from different age
groups, income levels, education levels, experience levels and occupation groups etc. Significant
differences are discussed here. We found no significant differences among investors at different level of
education regarding their opinion about level of involvement except that investors with MatriculationIntermediate and Bachelor-Master level of education gave higher rating to the statement 18C2 as
compared to the investors from education group of Primary-Middle (p values .030 and .044 respectively).
When we analyzed the level of involvement of investors from different occupation categories we found
significant difference (with p value .004) among salaried individuals and self-employed individuals.
Salaried individuals gave higher rating to the statement 18C2 than self-employed individuals, that simply
depicts that. No significant differences among the opinion of investors having different level of
experience of investing in stocks except that investors with 10 to 20 years of experience of investing in
stocks greatly endorsed that they are more actively involved in trade activity as compared to those with
investment experience of <10 years (p value .023)
When we analyzed the risk preferences of investors from different age groups we found that investors
with ages 50+ are more risk averse as compared to investors with ages <30 and 30-50 (p values 0.000 and
0.008 respectively). Findings also suggest that investors with ages 50+ have relatively higher preference
for investing in familiar companies that offer stable returns. We also analyzed the risk preferences of
investors at different levels of education and found statistically significant differences among the opinion
of investors belonging to Group 1 (Primary-Middle) and other two Groups (Matriculation-Intermediate
and Bachelor-Masters). Investors from Group one gave higher rating to the statement 18D 3 as compared
to other two groups (p values .046 and .012 respectively). However no further significant differences
came into notice. We also evaluated the responses of investors with different level of experience of
investing in stocks and found that investors with investment experience of 10 to 20 or >20 years are more
risk averse and have higher preference for stable returns as compared to those with <10 years (p values
0.031 and 0.010 respectively). Interestingly this finding is also consistent with the previous finding that
investors with ages 30-50 and 50+ are more risk averse and have higher preference for stable returns as
compared to investors with ages <30 years.
We also analyzed the risk preferences of investors from different occupation categories for some
occupation categories we found statistically significant differences of opinion about risk. There is
difference of opinion about statement 18D1 between salaried individuals and self-employed. Finding
suggest that salaried individuals tend to be more risk aversive than that of self employed individuals (p
value 0.007). In response to statement 18D4, retired individuals gave significantly different responses as
compared to self-employed, un-employed, salaried-individual and students (p values .001, .031, .008 and
.059 respectively). Mean differences revealed the aspect that retired people gave higher rating to the
statement that showed they are prefer stable returns even if lower and thus are more risk aversive in their
response about this statement as compared to all other occupation groups.
Investment Objectives
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20. We inquired investors about their investment objectives. As it is quite likely that a single investor can
have more than one investment objectives so we asked investors to reveal the relative proportion of their
investments in case they have more than one investment objectives. By analyzing the obtained responses
we found that 40.24% of the investors have totally short term profit seeking investment objectives to take
benefit from the daily price fluctuations, 2.33% of the investors make 100% of their investment to earn
steady income in the form of dividends, 10.98% of the investors make 100% of their investment for long
term profit objectives by investing in growth stocks, while rest of the investors have more than one
investment objectives, different combinations of short term profit seeking objectives, long term objectives
and investment for steady income but in these mixed combinations the proportion of investment for short
term profit seeking is much higher as compared to other investment objectives. It simply reveals that
investors have disposition of making investment for short term profit seeking and more people have the
mentality of getting rich quickly instead of waiting for long time period by investing in growth stocks.
We got an interesting finding by probing into the investment objectives of investors from different age
groups. We found that investors from different age groups have got significant differences in their
preferences for investment objectives. One-way Anova results revealed that the investors from age groups
of <30 and 30-50 have significant differences (with statistical significances of 0.037 and 0.023
respectively) , from investors belonging to age group of 50+ in terms of their opinion about investments
for dividend purposes. By looking into mean differences we came to know that the group of investors
with ages more than 50 years are more inclined towards making investment for generating steady stream
of income in the form of dividends as compared to investors who belong to age groups of <30 and 30 to
50 years while no significant differences among age groups of <30 and 30-50 regarding investing for
dividends are found.
Furthermore analysis of variances revealed that investors having different occupation categories have
significant differences among their preferences for investment objectives. When we compare retired
individuals with salaried individuals we got an interesting finding that both have significantly different
opinion about making investment for dividends. By analyzing mean differences we came to know that
retired individuals are more inclined towards investing for dividends as compared to salaried individuals.
By comparing investment preferences of salaried individuals with self-employed individuals we found
that both have significant differences about short term profit seeking objective and long term investments
(at the significance level of 0.001 and 0.012 respectively). We found that salaried individuals are more
inclined towards making investments for short term profit seeking as compared to self-employed
individuals. While self-employed individuals have greater preference for long term investments as
compared to salaried individuals.
When we compared investment objectives of students with that of self-employed individuals we found
that students have greater tendency towards investing for short term profit seeking than that of selfemployed individuals though the difference was not highly significant. No significant differences
regarding investment objectives were found among other groups. Investors with different education level
are also found to have significant differences among their preferences regarding investment objectives.
When we compared group 1 (investors with education Primary-Middle) with Group 2 and 3(investors
with education level of Matriculation-Intermediate and Bachelor-Masters) we found that Group 1 has
greater preference for making investments for dividend purposes as compared to other two groups, while
other two groups are more inclined towards making investments for short term profit seeking. This
finding makes a link to the previous findings that suggest that investors with education level of PrimaryMiddle and having ages 50+ and self-employed individuals are more likely to make investments for
dividend purposes. We further probe and analyzed that whether type of education (Business related or
Non-Business education) got has an impact on investment objectives or not but we got no significant
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21. differences. We also analyzed whether investment experience (in years), marital status, no. of children,
level of income and investment level has an impact on their investment objectives and found no
significant of differences.
We also investigated the impact of investor behavior on investment objectives and got interesting
findings. We conducted regression analysis to find the nature of relationship of dimensions of investment
behavior (Involvement, Risk attitude, Overconfidence and Optimism) with investment objectives.
Dimensions of investment behavior are taken as predictor variables while investment objectives are taken
as dependent variables. We analyzed each investment objective individually and significant results are
summarized in the table below,
Table 3: Regression Analysis of Investment Behavior and Investment Objectives
Dependent Variable
Predictor Variable
Beta
Short term profit seeking
Involvement
.499
t value
p value
4.170
.000
Short term profit seeking
Overconfidence
-2.58
-3.991
.000
Investing for Dividends
Involvement
-.494
-3.629
.001
Long Term Investments
Involvement
-.336
-3.870
.000
Significant at 5% level.
The statistical findings and level of significance suggest that among all four investment behavior
dimension of investor involvement and overconfidence have highly significant relation with short term
profit seeking. The beta values suggest the direction of the relationship. Negative beta for overconfidence
shows that as investors‟ level of overconfidence increases their propensity to make investment for short
term profit seeking decreases. Negative betas for dimension of involvement reveals a negative
relationship between level of involvement and making investment for long term or for dividend purposes.
But level of involvement is found to have positive relationship with short term profit seeking that shows
that more involved investors prefer short term profit making objectives.
Monitoring Behavior
When we probed into the monitoring behavior of investors, we found that 84.6% of the investors daily
monitor their investments in stocks it is also because majority look for short term profits from favorable
price moves. In order to capture benefits from favorable stock price moves they need to monitor more
frequently this finding is also consistent with the finding in our previous discussion on investment
objectives revealed that majority of investors invest for short term profit seeking. 4.7% of the investors
monitor their investment weekly, 5.6% of the investors monitor monthly, 1% of the investors monitor
quarterly while 0.7% of the investors monitor semi-annually and same percentage of investors monitor
their investments in stocks annually. These frequencies are relatively small as relatively less proportion of
investors invest for long term. Investors with different level of investments are observed to have
significantly different monitoring behavior. We found that the investors with high level of investments
tend to monitor their investments more frequently as compared to those with little investments. But at the
same time investment objectives change the monitoring behavior of the investors with short horizon
monitor more frequently as compared to those with long term investments and investments for dividend
purposes.
When we studied monitoring behavior of investors from different occupation categories we got
statistically significant findings that retired and un-employed individuals more frequently monitor their
investments more frequently as compared to other occupation categories of students, retired individuals,
self-employed and salaried individual (p values .024, .024, .015 and .010 respectively). It simply reveals
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22. the aspect that they have got ample free time and they get themselves engaged in tracking their
investments despite the fact that they do not invest for short term profit seeking. We also studied the
monitoring behavior of investors belonging to different age groups and found strange results. Statistically
significant results suggest that investors from age group of 50+ more frequently monitor their investments
as compared to other two age groups of <30 and 30-50 with statistical of significance of .001 and .005
respectively. The investors from age group of 50+ are mostly retired individuals and are more inclined
towards investing for dividend purposes while other two age groups are found to have inclination towards
short term profit seeking. The reason of this finding is basically linked to another finding related to the
monitoring behavior of investors from different occupation categories.
We also found the impact of investment objectives on the monitoring behavior of investors. Crosstab
results at the significance level of .012 showed that as the proportion of investment for short term profit
seeking increases from 20% to 100% the number of investors who monitor investments daily increases
from 5 to 91. At statistical significance of .000 it is found that with the increased proportion of long term
investment from 20% to 100% the number of investors monitoring daily decreases from 23 to 15 while
the frequency of monitoring monthly increases from 0 to 9. It simply shows that investors with short term
profit seeking objectives monitor their investments more frequently as compared to those with long term
investments.
Investment Decisions
As a result of preliminary interviews and secondary research we three ways of making an investment
decision; Technical Analysis, Fundamental Analysis and Market Sentiments/Psychology. These 3
dimensions are measured with the help of different factors.
Active Trade Volume
39.88%
Patterns, Charts,
Trends 16.60%
Daily Price Fluctuation
29.58%
Past Price Information
13.94%
Financial Ratios
50.33%
Government Regulations 11.56%
Company Information
28.51%
Management Quality
9.60%
Technical Analysis
38.34%
Decision
Making Style
Fundamental Analysis
32.72%
Herd Behavior
37.30%
Media Stories
19.65%
Rumours
30.08%
Recommendations
12.97%
Market Sentiments
28.94%
Figure 3: Graphical Presentation of the AHP results of Q no. 19
Analytical hierarchical process helped us determine the relative weights of the three dimensions in the
formation of overall investment decision. Relative weights for the factors of each dimension are also
determined using AHP. The dimension of technical analysis is ranked at number one with weights of
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23. 38.34% while fundamental analysis and market sentiments are at second and third ranks with weights of
32.73% and 28.94% respectively. It basically reveals the aspect that investment decision is neither based
on fundamental analysis solely nor on technical analysis or market sentiments rather all these three
dimensions help investor reach at an investment decision. But with different level of importance given to
each decision method as the weights suggest.
AHP helped us determine that in technical analysis the factor that is ranked as number one is the active
trade volume and turnover with weights approximately 40%. On second rank there comes daily price
fluctuation with weights of 29.58% while past patterns, charts and trends at third and past price
information of the company at fourth rank with relative weights of approximately 16% and 14%
respectively. By using AHP we ranked the factors of fundamental analysis on the basis of their level of
importance to the investors and found the hierarchical order; 1 Financial Ratios (50.33%), 2 Company
Information (financial statements) (28.51%), Government Regulations (11.56%) and 4 Management
Quality (9.60%). This hierarchical order reveals that in fundamental analysis investors give more
importance to the financial ratios as compared to other factors. The factor of Financial Ratios is further
divided into four sub-factors. Again we used AHP to determine the relative weights and level of
importance of each ratio to the investor. AHP helped us determine the ranking of the ratios, 1 Dividend
per share (21.82%), 2 Price to Earning Ratio (15.70%), 3 Debt to Equity Ratio (7.38%) and 4 Return on
Equity (5.43%). Market sentiments are measured in terms of four factors that are prioritized in
hierarchical order; 1 Herd Behavior with weights 37.30%, 2 Rumours with weights 30.08%, 3 Media
Stories with weights 19.65% and 4 Recommendations with weights 12.97%.
We also calculated the Global Weighted Indices of the determinants of investor decisions. Results are
summarized below,
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24. GWI of the Dimensions of Investment Decision
Professional Advice
0.028606349
Media Stories
0.056855706
Rumours
0.08705329
Herd Behavior
0.107946798
Market Psychology
Return on Equity
Debt to Equity Ratio
Management Quality
Government Regulation
0.289375309
0.017767907
0.024136939
0.031425269
0.037836541
Price to Earning Ratio
0.051380644
Dividemd Payout Ratio
0.071414813
Company Information
0.093287825
Fundamental Analysis
0.327249938
Past price Information
0.053426029
Patterns, Trends, Charts
0.063648311
Daily price Fluctuation
0.113419316
Active Trade Volume
0.152881097
Technical analysis
0.383374753
Figure 4: GWI of dimensions of Investment Decisions
In Q no. 19 investors were asked to rate different statements, regarding investment decisions, on 1(Least
Important) to 7(Most Important) point likert scale. Results are summarized here,
Table 4: Frequency Results of Dimensions of Investment Decisions
Decision Making Styles
Statements
1
2
3
4
5
6
7
Total Frequency
Technical Analysis
19A1
6.9
11.8
13.4
21.5
22.4
7.3
16.7
100%
19A2
20.0
2.8
2.8
14.2
15.4
18.7
45.9
100%
19A3
7.7
15.0
19.1
24.0
15.0
8.5
10.6
100%
19A4
0.0
0.0
5.7
6.9
38.6
26.8
22.0
100%
19B1
2.8
2.4
6.9
13.8
44.7
16.7
12.6
100%
19B2
4.1
4.9
6.9
9.3
22.0
22.8
30.1
100%
19B3
1.6
0.8
4.9
10.6
18.3
20.7
43.1
100%
19B4
18.7
19.1
17.5
20.3
10.2
8.5
5.7
100%
Fundamental Analysis
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25. 19B5
18.3
10.2
26.0
13.0
8.5
6.9
100%
19B6
2.8
4.1
5.3
23.2
24.8
24.4
15.4
100%
19B7
7.7
11.4
9.3
11.4
20.7
21.1
18.3
100%
19C1
0.8
1.6
8.9
19.9
20.3
30.9
17.5
100%
19C2
3.7
2.4
6.1
23.6
26.4
23.6
14.2
100%
19C3
12.6
4.1
4.1
18.3
30.9
22.8
7.3
100%
19C4
50.4
15.0
6.9
7.7
13.4
4.1
2.4
100%
19C5
Market Psychology/
Sentiments
17.1
8.5
2.8
5.3
9.8
23.2
28.5
22.0
100%
Investors were asked to rate the four statements, regarding technical analysis, from 19A1 to 19A4 on a 1
(Least Important) to 7 (Most Important) scale. In response to the first statement, “Use of past price
movements to predict future price movements and returns of stocks” 16.7% gave it a rating of 7, i.e. they
considered it as the most important factor while only 6.9% considered it the least important factor. 21.5%
of the respondent gave it rating of 4 while 46.4% of the respondents agreed with the statement that they
make use of past price movements and returns to predict the future prices and returns of the stock and
gave it rating of 5 and above. According to 32.1% of the respondents it is not an important factor and they
gave it rating of 3 and below. On the whole 53.6% of investors gave rating of 4 or less while 46.4% of
investors gave a rating of 4 or less. 45.9% of the investors regarded daily price fluctuations of the stocks
as an important factor while just 2.8% of the investors regarded it as the least important factor. Majority
(80%) of the investors gave a rating of 5 or above. When investors were asked about the importance of
historic price charts, patterns and trends they considered it not much important factor to be taken into
account for stock selection. 65.8% of the investors gave a rating of 4 or less while just 10.6% of the
investors considered it among the most important factors for stock selection. 22% of the investors
considered daily active trade volume and turnover as the most important factor to be taken into account
before making stock selection. Interestingly not a single investor considered it to be least important. Just
12.6% investors gave a rating of 4 or less while according to all other investors it as an important factor
worth considering while making stock selection.
Investors were asked to rate seven statements, regarding fundamental analysis, from 19B1 to 19B7 on a 1
(Least Important) to 7 (Most Important) scale. When we asked to the investors that do they use company
information, annual statements, and financial ratios to predict future prices and returns of stocks 22.4% of
the respondents showed strong agreement with the statement and gave a rating of 7 while only 7.3% of
the respondents showed strong disagreement and gave a rating of 7.3%. 30% of the respondents gave
rates of 4 or less while 70% of the investors gave rates of 5 or more. 30.5% (highest frequency) of
respondents gave it a rating of 5. In the first statement investors were asked to rate the importance of price
to earnings ratio. 30.1% of the investors regarded as the most important factor for selecting stock for
investment while just 4.1% of the investors regarded as the least important factor. 74.9% of the investors
gave rating of 5 or more regarded as an important factor for picking stocks before making investment.
43.1% of the investors considered dividend paying ability of the company to be the most important factor
in stock selection while 1.6% of the investors considered it as the least important factor. However
majority i.e. 82.1% of the investors gave rating of 5 and above to this factor.
When investors were asked about debt to equity ratio most of the investors did not considered it to be an
important factor for selection of the stocks. 18.7% of the investors regarded it as a least important factor
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26. in the way of selection and 75.6% of the investors gave a rating of 4 or less. Same is the case of debt to
equity ratio majority of the investors gave rating of 4 or less. According to 17.1% investors the ROE is
not an important factor for stock selection while just 6.9% considered it the most important. Majority
(71.6%) gave rating of 4 or less depicting that they do not give much importance to ROE from stock
selection point of view. Investors were also asked about the level of importance of government
regulations before making stock selection. They were asked do they look for government regulations
before investing in a particular sector. 15.4% of the investors considered it to be the most important factor
while 2.8% considered it to be the least important factors. 64.6% of investors gave a rating of 5 or above
while 35.4% gave a rating of 4 or less. Investors were also asked about the importance of the factor of
management quality before making stock selection. 18.3% of the investors gave it a rating of 7 and
considered as the most important factor while according to 7.7% of the investors it is among the least
important factors. 60.1% of the investors gave a rating of 5 or more.
In the last section Investors were asked that to them how important it is to consider the rumours before
selecting stock of some particular company. 30.9% of the investors gave a rating of 6 to this factor while
0.8% of the investors considered it to be the least important factor. However 68.7% of the investors
considered it an important factor, worth noticing while selecting stock. When investors were asked about
importance of news stories in the media, 64.2% of the investors gave a rating of 5 or above and thus
considered it an important factor to be looked for before making stock selection while 35.8% of the
investors gave a rating of 4 or less and thus considered un-important. Investors were also asked about the
level of importance of the professional advice and recommendations of the brokers and analysts. 12.6% of
the investors considered it the least important factors however 61% of the investors gave a rating of 5 or
above. Investors were also asked about the level of importance of the advice of some friend, family, peer
etc. 50.4% of the investors were of the view that it is among the least important factors while just 2.4 of
the investors considered it to be among the most important factors. According to majority it is not
important factor. Investors were also asked that how much important is the factor that majority is buying
the stocks of the company. 22.0% of the investors gave a rating of 7 to this factor while 8.5% of the
investors considered it as least important factor. However according to majority it is among an important
factor as 73.7% of the investors gave a rating of 5 or above.
We also conducted the analysis of variance of responses regarding decision making styles. When we
analyzed the responses of investors from different income level groups, regarding technical analysis, we
observed significant difference of opinion of investors with income >30 lac from other investors. When
we looked into the mean differences we found that investors with income >30 lac give more importance
to the factor of daily price fluctuations as compared to all other investors with incomes <5 lac, 5-10 lac
and 10-30 lac (p values .042, .044 and .005 respectively). When we analyzed the responses of investors
from different occupation groups regarding technical analysis we found that salaried individuals gave
high rating to the factors used to measure technical analysis as compared to self-employed and retired
individuals (p values 0.000 and 0.004 respectively). Salaried individuals gave high rating to the past price
information as compared to self-employed individuals (p value 0.013). Moreover we found that salaried
individuals look into charts, patterns and trends more than those who are students, retired and selfemployed individuals (p values 0.000, 0.009 and 0.035 respectively).
Analysis of variance suggested that there are no meaningful differences about fundamental analysis
among responses of investors from different age groups, education level, investment age and occupation
categories. However some significant differences among responses of investors with different income
levels have been noticed. Findings suggest that investors with incomes 10 to 30 lac give more importance
to fundamental analysis as compared to investors with income <30 lac (p value 0.014). When we probed
into the factors of fundamental analysis, we found that investors with income level of 10 to 30 lac give
more importance to company information and dividend payout ratio as compared to those with <5 lac (p
values 0.002 and 0.002 respectively). When we compared investors with investment experience of 10 to
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27. 20 years also found significant differences of opinion regarding fundamental analysis. Analysis of
variance revealed that investors with investment experience of 10 to 20 years or more than 20 years give
more importance to fundamental analysis as they gave high rating to the factors of fundamental analysis
as compared to those with experience of less than 10 years (p values 0.015 and 0.024 respectively).
When we studied the responses of investors from different age groups, we found that investors with ages
50+ relatively give more importance to market sentiments while making an investment decision as
compared to those with ages <30 and 30-50 years (p values 0.038 and 0.032). We found that to investors
with ages 50+ news stories in media are relatively more important as compared to other investors.
Findings suggest that investors with ages <30 give relatively more importance to recommendations as
compared to investors with ages 50+. When we analyzed the responses of investors at different education
levels we found that investors with Primary-Middle level of education rely on rumors more than investors
with Bachelor-Master level of education (p value .012). We also concluded from the mean differences
that investors with Bachelor-Master level of education give more weight to the opinion of family, friends
and peer as compared to investors with Matriculation-Intermediate level of education (p value .003). We
also probed into the behavior of investors with different levels of income. There were not many
differences among their opinions except that (p values .064 and .039) investors with income levels 5 to 10
lac and 10 to 30 lac showed significantly different opinion about statement 19C5. Mean differences
revealed that investors with income level 5 to 10 lac and 10 to 30 lac follow the majority investors (herd
behavior) as compared to investors with income <5 lac.
When we analyzed the responses of investors from different occupation groups we observed that retired
individuals believe on rumors more as compared to self-employed individuals (p value .046). We also
found that un-employed individuals take into account the recommendations of friends, family and peer as
compared to self-employed individuals (p value .012). While self-employed individuals give more
weights to the professional advice of some analyst or brokers more than retired individuals (p value.049).
We also studied the responses of investors at different level of investment experience in stocks. We found
that investors with investment experience of >20 years give relatively more importance to media stories
as compared to investors with investment experience of <10 years and 10 to 20 years (p values of .009
and .012 respectively). We also found that investors with investment experience of <10 years and 10 to 20
years, give relatively more importance to professional advice and recommendations as compared to
investors with investment experience of >20 years. These findings are also consistent with the previous
findings that investors with ages 50+ give more importance to media stories and less importance to
recommendations as compared to investors from other age groups.
To analyze the impact of the determinants of investor behavior on decision making style we fitted regression model.
Findings are summarized in the table below,
Table 5: Regression Results showing the Relationship between Determinants of Behavior and Investment Decision
Explanatory variables
Unstandardized Coefficients SE of Coeff.
Beta
t value
p value
Intercept
3.010
.248
Involvement
.085
.023
.214
Risk.Attitude
.092
.039
.136
2.383
.018
Optimism
.039
.030
.074
1.303
.194
Overconfidence
.195
.032
.356
6.062
.000
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12.153
.000
3.749
.000