Necessity of Behavioral Finance in Everyday Life

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Muhammed Faraz Ashraf
Necessity of Behavioral Finance in Everyday Life
EXECUTIVE SUMMARY
The following dissertation hopes to provide a better understanding of some of the
anomalies (i.e., irregularities) that conventional financial theories have failed to explain. In
addition, layout some insights into the underlying reasons and biases that cause some people to
behave irrationally (and often against their best interests). Furthermore, it looks into the need for
an awareness in behavioral finance in the most basic level for people of every turf. Eventually, this
newfound knowledge shall come to the aid while making financial decisions.

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TABLE OF CONTENTS
0 Introduction ................................................................................................................................. 1
Background ................................................................................................................................. 1
Homo Economics .................................................................................................................... 2
Important Contributors.......................................................................................................... 3
Critics...................................................................................................................................... 4
Anomalies.................................................................................................................................... 5
January Effect .......................................................................................................................... 5
The Winner's Curse ................................................................................................................ 6
Equity Premium Puzzle........................................................................................................... 7
1 Literature Review ......................................................................................................................... 9
1.1 Anchoring ........................................................................................................................ 9
1.2 Mental Accounting........................................................................................................ 11
1.3 Confirmation & Hindsight Bias.................................................................................... 12
1.3.1 Confirmation Bias...................................................................................................... 12
1.3.2 Hindsight Bias........................................................................................................... 13
1.4 Gambler’s Fallacy .......................................................................................................... 13
1.5 Herd Behavior................................................................................................................ 14
1.6 Overconfidence.............................................................................................................. 15
1.7 Availability Bias............................................................................................................. 16
1.8 Prospect Theory ............................................................................................................ 17
2 Research Methodology............................................................................................................... 19
2.1 The General Approach .................................................................................................. 19
2.2 Choice of Method.......................................................................................................... 20
2.3 Data Collection.............................................................................................................. 21
2.3.1 Primary Data.............................................................................................................. 21
2.3.2 Secondary Data.......................................................................................................... 22
2.4 Criticism of the Sources ................................................................................................ 22
2.4.1 Criticism of Primary Data.......................................................................................... 22

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2.4.2 Criticism of Secondary Data...................................................................................... 23
2.4.3 Validity...................................................................................................................... 23
2.4.4 Reliability.................................................................................................................. 24
2.5 Data Collection and Analysis ........................................................................................ 25
2.5.1 Scale of Awareness .................................................................................................... 26
2.5.2 Anchoring.................................................................................................................. 28
2.5.3 Mental Accounting.................................................................................................... 29
2.5.4 Confirmation Bias...................................................................................................... 31
2.5.6 Hindsight Bias........................................................................................................... 32
2.6 Recommendation .......................................................................................................... 33
References ..................................................................................................................................... 36
Appendix A – Questionnaire......................................................................................................... 38
Appendix B – Results Analysis ..................................................................................................... 40

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Acknowledgments
The process of writing and completing this dissertation has been challenging yet
very rewarding for me. I would like to express my sincere gratitude to several important
people. I thank Vinod Shukla, my program leader, for his guidance, support, and
confidence in me. I appreciate the guidance and help from the faculty at Amity University,
Dubai. I am grateful to my fellow students for their friendship and support throughout the
years of my study.
I would like to convey my deepest appreciation to my family, for their love and
support along every step of the way. They have always encouraged me to pursue what I
wanted to do with my life.

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0
Introduction
According to conventional financial theory, the world and its participants are, for
the most part, rational "wealth maximizers". However, there are many instances where
emotion and psychology influence people’s decisions, causing unpredictable or irrational
behavior.
Behavioral finance is a relatively new field that seeks to combine behavioral and
cognitive psychological theory with conventional economics and finance to provide
explanations as to why people make irrational financial decisions.
Background
Before going over the specific concepts behind behavioral finance, the following
paragraphs hope to show a much general look at this branch of finance. This section,

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examines a comparison between behavioral and conventional finance, give introduction to
the three important contributors to the field and runs an eye over the criticism it has
received.
Why is behavioral finance necessary?
When using the labels "conventional" or "modern" to describe finance, one aims to
talk about the type of finance that is based on rational and logical theories, such as the
capital asset pricing model (CAPM) and the efficient market hypothesis (EMH). These
theories assume that people, for the most part, behave rationally and predictably.
For a while, theoretical and empirical evidence suggested that CAPM, EMH and
other rational financial theories did a respectable job of predicting and explaining certain
events. However, as time went on, academics in both finance and economics began to find
anomalies and behaviors that couldn't be explained by theories available at the time.
While these theories could explain certain "idealized" events, the real world proved to be
a very messy place in which market participants often behaved very unpredictably.
Homo Economics
One of the most fundamental assumptions that conventional economics and
finance brands is that people are rational "wealth maximizers" who seek to increase their
own welfare. According to conventional economics, emotions and other minor factors do
not influence people when it comes to making economic choices.
In most cases, however, this assumption does not reflect how people behave in the
real world. The fact is people habitually behave irrationally. Consider how many people
purchase lottery tickets in the hope of hitting the big jackpot. From a purely logical
standpoint, it does not make sense to buy a lottery ticket when the odds of winning are

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overwhelming against the ticket holder (roughly 1 in 146 million, or 0.0000006849%, for
the famous Powerball jackpot). Despite this, millions of people spend countless dollars on
this activity.
Such anomalies prompted academics to look to cognitive psychology to account
for the irrational and illogical behaviors that modern finance had failed to explain. Thus,
Behavioral Finance seeks to explain our actions, whereas Modern Finance seeks to explain
the actions of the "economic man" (Homo economics).
Important Contributors
As in every other branch of finance, the field of behavioral finance have certain
brilliant minds that have provided significant theoretical and empirical contributions. The
following section provides a brief introduction to three of the biggest names associated
with the field.
Daniel Kahneman and Amos Tversky
Cognitive psychologists Daniel Kahneman and Amos Tversky are considered the
fathers of behavioral economics/finance. Since their initial collaborations in the late 1960s,
the duo have published roughly 200 works, most of which relate to psychological concepts
with implications for behavioral finance. In 2002, Kahneman received the Nobel Memorial
Prize in Economic Sciences for his contributions to the study of rationality in economics.
Kahneman and Tversky have focused much of their research on the cognitive biases
and heuristics (i.e. approaches to problem solving) that cause people to engage in
unanticipated irrational behavior. Their most popular and notable works include writings
about prospect theory and loss aversion - topics that shall be examined later.

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Richard Thaler
While Kahneman and Tversky provided the early psychological theories that set
the foundation for behavioral finance, it would not have evolved if it weren't for economist
Richard Thaler.
During his research, Thaler became more and more mindful of the shortcomings in
conventional economic theories as they relate to people's behaviors. After reading a draft
version of Kahneman and Tversky's work on prospect theory, Thaler realized that, unlike
conventional economic theory, psychological theory could be used to account for the
irrationality in behaviors.
Thaler went on to collaborate with Kahneman and Tversky, blending economics
and finance with psychology to present concepts, such as mental accounting, the
endowment effect and other biases.
Critics
Although behavioral finance has been gaining support in recent years, it is not
without its own share of criticism. For example, few of the supporters of Efficient Market
Hypothesis, are vocal critics of Behavioral Finance.
The efficient market hypothesis is considered one of the foundations of modern
financial theory. However, the hypothesis does not account for irrationality because it
assumes that the market price of a security reflects the impact of all relevant information
as it is released.
The most notable critic of behavioral finance is Eugene Fama, the founder of
market efficiency theory. Professor Fama suggests that even though there are some

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anomalies that cannot be explained by modern financial theory, market efficiency should
not be totally abandoned in favor of behavioral finance.
In fact, he notes that many of the anomalies found in conventional theories could
be considered shorter-term chance events that are eventually corrected over time. In Fama
(1998), he argues that many of the findings in behavioral finance appear to contradict each
other, and that all in all, behavioral finance itself appears to be a collection of anomalies
that can be explained by market efficiency.
Anomalies
The presence of frequently occurring anomalies in conventional economic theory
was a big contributor to the formation of behavioral finance. These so-called anomalies,
and their continued existence, directly violate modern financial and economic theories,
which assume rational and logical behavior. The following is a quick summary of some of
the anomalies found in the financial literature.
January Effect
The January effect is named after the phenomenon in which the average monthly
return for small firms is consistently higher in January than any other month of the year.
This is at odds with the efficient market hypothesis, which predicts that stocks should
move at a "random walk".
However, Rozeff and Kinney (1976), found that from 1904-74 the average amount
of January returns for small firms was around 3.5%, whereas returns for all other months
was closer to 0.5%. This suggests that the monthly performance of small stocks follows a
relatively consistent pattern, which is contrary to what is predicted by conventional

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financial theory. Therefore, some unconventional factor (other than the random-walk
process) must be creating this regular pattern.
One explanation is that the surge in January returns is a result of investors selling
loser stocks in December to lock in tax losses, causing returns to bounce back up in
January, when investors have less incentive to sell. While the year-end tax selloff may
explain some of the January effect, it does not account for the fact that the phenomenon
still exists in places where capital gains taxes do not occur. This anomaly sets the stage for
the line of thinking that conventional theories do not and cannot account for everything
that happens in the real world.
The Winner's Curse
One assumption found in finance and economics is that investors and traders are
rational enough to be aware of the true value of some asset and will bid or pay accordingly.
However, anomalies such as the winner's curse - a tendency for the winning bid in
an auction setting to exceed the intrinsic value of the item purchased - suggest that this is
not the case.
Rational-based theories assume that all participants involved in the bidding
process will have access to all relevant information and will all come to the same valuation.
Any differences in the pricing would suggest that some other factor not directly tied to the
asset is affecting the bidding.
According Thaler (1988), there are two primary factors that undermine the rational
bidding process: the number of bidders and the aggressiveness of bidding.

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For example, the more bidders involved in the process means that you have to bid
more aggressively in order to dissuade others from bidding. Unfortunately, increasing your
aggressiveness will also increase the likelihood in that your winning bid will exceed the
value of the asset.
Consider the example of prospective homebuyers bidding for a house. It is possible
that all the parties involved are rational and know the property’s true value from studying
recent sales of comparative houses in the area. However, variables irrelevant to the asset
(aggressive bidding and the amount of bidders) can cause valuation error, oftentimes
driving up the sale price more than 25% above the property’s true value. In this example,
the curse aspect is twofold: not only has the winning bidder overpaid for the house, but
now that buyer might have a difficult time obtaining financing.
Equity Premium Puzzle
An anomaly that has left academics in finance and economics scratching their
heads is the equity premium puzzle. According to the capital asset pricing model (CAPM),
investors that hold riskier financial assets should be compensated with higher rates of
returns.
Studies have shown that over a 70-year period, stocks yield average returns that
exceed government bond returns by 6-7%. Stock real returns are 10%, whereas bond real
returns are 3%. However, academics believe that an equity premium of 6% is extremely
large and would imply that stocks are considerably risky to hold over bonds. Conventional
economic models have determined that this premium should be much lower. This lack of
convergence between theoretical models and empirical results represents a stumbling
block for academics to explain why the equity premium is so large.

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Behavioral finance's answer to the equity premium puzzle revolves around the
tendency for people to have "myopic loss aversion", a situation in which investors - overly
preoccupied by the negative effects of losses in comparison to an equivalent amount of
gains - take a very short-term view on an investment. What happens is that investors are
paying too much attention to the short-term volatility of their stock portfolios. While it is
not uncommon for an average stock to fluctuate a few percentage points in a very short
period of time, a myopic (i.e., shortsighted) investor may not react too favorably to the
downside changes. Therefore, it is believed that equities must yield a high-enough
premium to compensate for the investor's considerable aversion to loss. Thus, the
premium is seen as an incentive for market participants to invest in stocks instead of
marginally safer government bonds.
Conventional financial theory does not account for all situations that happen in
the real world. This is not to say that conventional theory is not valuable, but rather that
the addition of behavioral finance can further clarify how the financial markets work.

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Literature Review
In the following section, the study will explore eight key concepts that pioneers in
the field of behavioral finance have identified as contributing to irrational and often
unfavorable financial decision making. Chances are, at one point or another, most people
have fallen prey to some of these biases.
1.1 Anchoring
Similar to how a house should be built upon a good, solid foundation, our ideas and
opinions should also be based on relevant and correct facts in order to be considered valid.
However, this is not always so. The concept of anchoring draws on the tendency to attach
or "anchor" our thoughts to a reference point - even though it may have no logical relevance
to the decision at hand (Fromlet, 2001).

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Although it may seem an unlikely phenomenon, anchoring is fairly prevalent in
situations where people are dealing with concepts that are new and novel.
Anchoring is one of the root psychological flaws that pushes otherwise brilliant
people to make financial mistakes (Belsky & Gilovich, 2010). It is critical to admit this
heuristic is hardwired in ones’ brain or else people will continue to succumb to it. To avoid
making serious financial mistakes, one must become a vigilant contrarian.
In the mental process of anchoring, it begins with some tentative solution to the
problem and then seek for a better or more accurate solution. For example, a person walks
into a car lot and notes the sticker price, and he then uses that number as the starting point
for negotiations. It is well known that the car can be purchased for that amount, however,
the same person shall start the process of seeking to get a better price.
Studies have shown that the higher the first price is for an item, the higher will be
the final price one ends up paying for the exact same item (Kauffman & Wood, 2005).
Stores sometimes bump their prices 30% higher before a 30% off sale because they
understand this principle. Sellers on eBay may set a "buy-it-now" price artificially high
simply to induce higher competitive bids.
Avoiding Anchoring
According to Marotta (2008), the antidote for anchoring is doing the extra analysis
to evaluate the answer more rationally. “Anchoring is like finding ourselves sitting in a chair in a
pitch-black room. When we stand up, we keep one hand on the chair and reach as far as we can in each
direction to try to get a feel for our location. The anchor of the chair keeps us from straying too far from
our original point. The answer, of course, is to turn on the lights” Marotta (2008).

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For rookie investors especially, it is never a bad idea to seek out other perspectives.
Listening to a few "devil's advocates" could identify incorrect benchmarks that causes their
strategy to fail.
1.2 Mental Accounting
According to Foulke (2014), mental accounting, also known as “two-pocket”
theory, is a behavioral bias that occurs when people put their money into separate
categories, separating them into different mental accounts, based on, say, the source of the
money, or the intent of the account.
“Mr. and Mrs.L and Mr. and Mrs. H went on a fishing trip in the northwest and caught some
salmon. They packed the fish and sent it home on an airline, but the fish were lost in transit.
They received $300 from the airline. The couples take the money, go out to dinner and spend
$225. They had never spent that much at a restaurant before.”
– Richard H. Thaler (2008)
Although many people use mental accounting, they may not realize how illogical
this line of thinking really is.
Another aspect of mental accounting is that people also treat money differently
depending on its source (Belsky & Gilovich, 2010). For example, people tend to spend a
lot more "found" money, such as tax returns and work bonuses and gifts, compared to a
similar amount of money that is normally expected, such as from their paychecks. This
represents another instance of how mental accounting can cause illogical use of money.
Avoiding Mental Accounting Bias
The key point to consider for mental accounting is that money is fungible;
regardless of its origins or intended use, all money is the same. One can cut down on

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frivolous spending of "found" money, by realizing that "found" money is no different than
money that is earned by working.
As an extension of money being fungible, realize that saving money in a low- or no-
interest account is fruitless if one still has outstanding debt. In most cases, the interest on
debt will erode any interest that can be earned in most savings accounts. While having
savings is important, sometimes it makes more sense to forgo savings in order to pay off
debt (Ritter, 2003).
1.3 Confirmation & Hindsight Bias
It's often said that "seeing is believing". While this is often the case, in certain
situations perception is not necessarily a true representation of reality. This is not to say
that there is something wrong with the senses, but rather that the minds have a tendency
to introduce biases in processing certain kinds of information and events.
1.3.1 Confirmation Bias
It can be difficult to encounter something or someone without having a
predetermined opinion. This first impression can be hard to shake because people also
tend to selectively filter and pay more attention to information that supports their
opinions, while ignoring or rationalizing the rest (Tripathy, 2013). This type of selective
thinking is often referred to as the confirmation bias.
In investing, the confirmation bias suggests that an investor would be more likely
to look for information that supports his or her original idea about an investment rather
than seek out information that contradicts it. As a result, this bias can often result in faulty
decision making because one-sided information tends to angle an investor's frame of
reference, leaving them with an incomplete picture of the situation (Shefrin, 2002).

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Consider, for example, an investor that hears about a hot stock from an unverified source
and is intrigued by the potential returns. That investor might choose to research the stock
in order to "prove" its advertised potential is real. What ends up happening is that the
investor finds all sorts of green flags about the investment (such as growing cash flow or a
low debt/equity ratio), while glossing over financially disastrous red flags, such as loss of
critical customers or deteriorating markets.
1.3.2 Hindsight Bias
Another common perception bias is hindsight bias, which tends to occur in
situations where a person believes (after the fact) that the onset of some past event was
predictable and completely obvious, whereas in fact, the event could not have been
reasonably predicted (Gilson & Kraakman, 2002).
Many events seem obvious in hindsight. Psychologists attribute hindsight bias to
the inborn need in people to find order in the world by creating explanations that allow
us to believe that events are predictable. While this sense of curiosity is useful in many
cases (take science, for example), finding inaccurate links between the cause and effect of
an event may result in incorrect oversimplifications (Kartašova, 2013).
1.4 Gambler’s Fallacy
When it comes to probability, a lack of understanding can lead to incorrect
assumptions and predictions about the onset of events. One of these incorrect
assumptions is called the gambler's fallacy.
In the gambler's fallacy, an individual erroneously believes that the onset of a
certain random event is less likely to happen following an event or a series of events. This

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line of thinking is incorrect because past events do not change the probability that certain
events will occur in the future (Shefrin, 2002).
For example, consider a series of 20 coin flips that have all landed with the "heads"
side up. Under the gambler's fallacy, a person might predict that the next coin flip is more
likely to land with the "tails" side up. This line of thinking represents an inaccurate
understanding of probability because the likelihood of a fair coin turning up heads is
always 50%. Each coin flip is an independent event, which means that any and all previous
flips have no bearing on future flips.
Avoiding Gambler’s Fallacy
It's important to understand that in the case of independent events, the odds of
any specific outcome happening on the next chance remains the same regardless of what
preceded it (Johnson, et al., 2005).
1.5 Herd Behavior
One of the most infamous financial events in recent memory would be the bursting
of the internet bubble. However, this wasn't the first time that events like this have
happened in the markets. This leads one to ask the question of how something so
catastrophic can be allowed to happen repeatedly.
The answer to that question can be found in what some people believe to be a
hardwired human attribute: herd behavior, which is the tendency for individuals to mimic
the actions (rational or irrational) of a larger group. Individually, however, most people
would not necessarily make the same choice.

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There are a couple of reasons why herd behavior happens. The first is the social
pressure of conformity (Shiller, 2001). This is because most people are very sociable and
have a natural desire to be accepted by a group, rather than be branded as an outcast.
Therefore, following the group is an ideal way of becoming a member.
The second reason is the common rationale that it's unlikely that such a large group
could be wrong (Hirshleifer & Teoh, 2003). . Despite a conviction that an idea or a course
of action may be wrong or irrational, one tends to follow the herd due to the belief that
they could be privy to some information that one does not have. This is very well sighted
in situations where a person has minimal experience.
Avoiding Herd Behavior
While it is tempting to follow the newest investment trends, an investor is
generally better off steering clear of the herd. Just because everyone is jumping on a certain
investment "bandwagon" doesn't necessarily mean the strategy is correct. Therefore, the
soundest advice is to always do the needed homework before following any trend.
1.6 Overconfidence
According to a survey (Montier, 2006), 74% of the 300 professional fund managers
believed that they had delivered above-average job performance. Of the remaining 26%
surveyed, the majority viewed themselves as average. Incredibly, almost 100% of the survey
group believed that their job performance was average or better. Clearly, only 50% of the
sample can be above average, suggesting the irrationally high level of overconfidence these
fund managers exhibited.

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As one can imagine, overconfidence (i.e., overestimating or exaggerating one's
ability to successfully perform a particular task) is not a trait that applies only to fund
managers (Barberis & Thaler, 2003). Consider the number of times that a person
participated in a competition or contest with the attitude “I have what it takes to win!”;
regardless of the number of competitors or the fact that there can only be one winner.
Keep in mind that there is a fine line between confidence and overconfidence.
Confidence implies realistically trusting in one's abilities, while overconfidence usually
implies an overly optimistic assessment of one's knowledge or control over a situation
(Ritter, 2003).
Avoiding Over Confidence
Professional fund managers, who have access to the best investment/industry
reports and computational models in the business, can still struggle at achieving market-
beating returns. The best fund managers know that each investment day presents a new
set of challenges and that investment techniques constantly need refining. Just about every
overconfident investor is only a trade away from a very humbling wake-up call.
1.7 Availability Bias
According to the availability bias, people tend to heavily weight their decisions
toward more recent information, making any new opinion biased toward that latest news
(De Bondt, et al., 2008).
This happens in real life all the time. For example, seeing a car accident on a route
that is usually used by someone to go to work to, could lead to a tendency to drive extra
carefully the next time they are using it. Even though the danger level for that route was

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always the same as it had always been, having sighted the accident can lead a person to
overreact. Eventually one would even return to the same driving habit once they have
gotten over it.
Avoiding Availability Bias
Perhaps the most important lesson to be learned here is to retain a sense of
perspective. While it's easy to get caught up in the latest news, short-term approaches
don't usually yield the best investment results (Carter, et al., 2007). A thorough job of
researching investments, can bring about better understanding of the true significance of
recent news. It is important to remember to focus on the long-term picture.
1.8 Prospect Theory
Prospect theory, contends that people value gains and losses differently, and, as
such, will base decisions on perceived gains rather than perceived losses (Kahneman and
Tversky, 1979). Thus, if a person were given two equal choices, one expressed in terms of
possible gains and the other in possible losses, people would choose the former - even
when they achieve the same economic end result.
According to prospect theory, losses have more emotional impact than an
equivalent amount of gains. For example, in a traditional way of thinking, the amount of
utility gained from receiving $50 should be equal to a situation in which you gained $100
and then lost $50. In both situations, the end result is a net gain of $50.
However, despite the fact that one may end up with a $50 gain in either case, most
people view a single gain of $50 more favorably than gaining $100 and then losing $50.

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The prospect theory can be used to explain quite a few illogical financial behaviors
(Olsen, 1998). For example, there are people who do not wish to put their money in the
bank to earn interest or who refuse to work overtime because they don't want to pay more
taxes. Although these people would benefit financially from the additional after-tax
income, prospect theory suggests that the benefit (or utility gained) from the extra money
is not enough to overcome the feelings of loss incurred by paying taxes.

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2
Research Methodology
This chapter describes the overall approach of the thesis as well as the choice of
method, data collection and criticism of the sources.
A method can be escribed as an instrument in solving problems and in arriving at
new knowledge of the subject in question. Everything that contributes in achieving these
goals is a part of the method. It is important that the method is consistent with the reality
that is being researched. Furthermore, the achieved results should generate increased
comprehension and understanding of the problem being examined (Holme and Solvang,
1996).
2.1 The General Approach
The general approach of a study is affected by the researcher’s frame of reference,
which refers to one’s overall knowledge, norms and values (Wiedersheim-Paul and

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Eriksson, 1997). The approach of this dissertation is based upon the frame of reference,
which works as an individual scale. The applied theories and models themselves affect the
individual scale of the research. Therefore, it is important that the researcher maintains an
objective approach. To achieve objectivity, a wide range of theories and literature in the
field of Behavioral Finance have been studied. However, interpretations and opinions in
literature and scientific articles that influence people might make it difficult to achieve an
entirely objective approach.
According to Wiedersheim-Paul and Eriksson (1997) the scientific approach of a
study can be described by two fundamental perspectives: rationalism and empiricism. The
rationalistic perspective refers to a deductive method where the researcher bases the study
on a theory, creates a hypothesis and subsequently reaches a logical conclusion through
observations. On the other hand, the empirical perspective refers to an inductive method
where general conclusions are based on empirical data. In contrast to the deductive
method the research first takes an empirical point of view (data collection) and thereafter
relates the findings to a theory. This dissertation chooses a deductive method as the
research is based on a theoretical framework of finance with an emphasis on behavioral
finance. It then tests the empirical findings with the existing theories. However, a part of
the theory that the dissertation is based on, such as the prospect theory by Kahneman and
Tversky, is based on an inductive framework.
2.2 Choice of Method
A method can be either quantitative or qualitative. A quantitative method is
formalized, structured and is characterized by selectivity as well as a distance from the
source of information (Holme and Solvang, 1996). The approach centralizes on numerical

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observations and aims at generalizing a phenomenon through formalized analysis of
chosen data where statistical indicators play a central role. On the other hand, a qualitative
method is formalized to a lesser extent is directed at testing if the information is generally
valid. The approach is characterized by the use of verbal descriptions instead of purely
numerical data and aims to create a common understanding of the subject being studied.
In order to achieve the purpose, a quantitative as well as qualitative method has
been adopted for the dissertation. The quantitative method refers to the survey
implemented in the form of a questionnaire, which is directed at the common public (both
active investors and otherwise). The survey intends to determine how well the practical
decision-making framework and behavior of investors in reality are consistent with the
existing theories of finance. A qualitative method is implemented through the attempt to
describe the reasons and existence of behavioral biases with the help of existing theories.
2.3 Data Collection
Data for the dissertation was primarily collected through a survey in form of a
questionnaire as well as through research based on existing material concerning
behavioral finance.
2.3.1 Primary Data
Primary data refers to data, which is collected for a specific purpose and which was
required in order to complement secondary data (Wiedersheim-Paul and Eriksson, 1997).
The primary data in this dissertation consists of the survey in the form of a questionnaire
directed at the common public. The sample was randomly chosen, questionnaires handed
out and answered voluntarily by those who wished to participate.

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The questionnaire consists of questions concerning the fundamental factors
affecting financial decision-making and questions referring to the behavior of people. An
example of the survey is included in Appendix 1.
The questionnaires were first processed with the help of Microsoft Excel to get an
overview of the preliminary results. The analysis was divided into two parts. A regular
analysis with comparisons among questions, which were based on the same theory were
grouped with each appropriate theory. This was done in order to be able to analyze and
compare questions easily.
2.3.2 Secondary Data
Secondary data refers to the existing collected and summarized material of the
subject in question. This data originates from sources such as existing online database,
journal articles and books (Wiedersheim-Paul and Eriksson, 1997). The secondary data
used in the research refers to the existing theories in finance, more specifically behavioral
finance, such as articles in journals and literature on the subject as well as Internet data
sources. The emphasis was on finding material on the relatively new area of behavioral
finance.
2.4 Criticism of the Sources
Both the primary and secondary sources of data may contain factors influencing
the quality of the research. Furthermore, one must also consider the validity and reliability
of the research in order to establish the overall quality of the study.
2.4.1 Criticism of Primary Data
The survey conducted in the form of a questionnaire, is advantageous as the
collected data is unique and contemporary in nature and the questions may be formulated

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to specifically correspond to the area being researched. However, the questionnaire is
susceptible to the subjective opinions of the respondents. When asking about previous
events extending farther into the past, investors’ responses are exposed to their subjective
ability to recollect specific past events. The respondents may also have changed their
perception of past events. Therefore, the answers given by respondents can be biased
toward what they think would have been the right course of action if they were given the
same choice today instead of reflecting the actual decision that would have been made in
the past. This is called hindsight bias.
2.4.2 Criticism of Secondary Data
The theories and literature written on behavioral finance are relatively new. It is
currently an evolving branch of financial theory and thus subject to many interpretations
and, to some extent, controversy with standard finance. An objective perspective on
behavioral finance has been taken while describing and utilizing the existing theories in
explaining the behavior of market participants. The majority of the secondary data is
obtained from scientific sources and is contemporary in nature. Therefore the secondary
data is considered to be highly pertinent.
2.4.3 Validity
A research has high validity if the dissertation only contains what one wants to
study and nothing else (Thuren, 1991). Validity refers to how well the data collection and
data analysis of the research captures the reality being studied. Validity can be divided
into three subgroups: construct-, internal- and external validity (Yin, 1994). First,
construct validity refers to the data collection procedure, i.e. establishing correct

24
operation measures for the concepts being studied. The dissertation concentrates on
financial decision-making in everyday lives on the basis of the observed phenomenon.
Internal validity refers to the process of establishing a casual relationship, whereby
certain conditions are shown to lead to other conditions, as distinguished from bogus
relationships (Yin, 1994). It also refers to the link between theory and the empirical
research (Svenning, 1997). The theories in behavioral finance, if not the only contributing
theory, are valid in explaining the empirical findings. However, it is difficult to show that
specific behavior among the investors observed would be the sole reason for the
phenomenon described.
2.4.4 Reliability
Reliability demonstrates that the operations of the dissertations, such as the data
collection procedures, can be repeated with the same outcome. The objective is to be sure
that if a later researcher followed exactly the same procedures as described by an earlier
researcher and conducted the same case study all over again; the later researcher should
arrive at the same findings and conclusions (Yin, 1994). One prerequisite for a repeated
case study is the need to document in detail the procedures in the relevant case. In this
study, a quantitative method has been utilized in the form of a questionnaire directed
toward the common public. It is considered easily applicable to another similar sample,
and should render the same results if directed toward the same sample group. Therefore,
it fulfills the reliability criteria.

25
2.5 Data Collection and Analysis
The core objective of this dissertation was to understand the concepts of
behavioral finance, as well as to test its awareness among people. Another aim was to also
pin-point how behavioral finance concepts can be linked to everyday decisions in life.
The data collection was done in the form of an online survey through the website
SurveyMonkey (see appendix for the questionnaire template). The questions were
targeted at the general public with a greater focus on working professionals from various
fields ranging from medicine to business. Due to a limited time frame the sample set
consists only of 60 responses. The age demographic was set from 18 to 60. Out of these,
the majority of the responses came from the 21-29 age group; which roughly makes them
the emerging generation who are the investors of tomorrow. Questions 1-3 were general
questions that illustrates the demographics such as age, gender and field of profession of
the sample set. The actual testing of the concepts begin from question 4 till question 10.
The questions have been designed with the purpose of identifying the key concepts
of behavioral finance such as Anchoring, Mental Accounting, and Confirmation &
Hindsight Bias.

26
2.5.1 Scale of Awareness
There are two questions that come under this factor. One test’s the awareness of
the subject and the second looks at the awareness consumers have with regards to their
investment/purchase decisions.
The above question highlights the awareness of the subject among the general
public.
From the graph, it can be seen that out of the 59 responses, majority (47%) are not
aware about such a topic as behavioral finance. Another 27 % have heard about it but they
are not sure, which loosely translated, means that they do not know. This means that
roughly 75% of the general public do not know what behavioral finance means.
This clearly shows that there is an immense need to create an awareness regarding
the subject among the masses solely for their benefit with regards to future investments.

27
This question was aimed at knowing how much people realize that there are external
factors that affect their investment/purchase decisions. It also shows that these external
factors are those the general public was not even aware of.
A staggering 86% admit that external factors affect their decisions as well as the fact that
they do not know them. It basically means that, most people do not make wise, informed
decisions by knowing all information beforehand. Only a small percent (15) of people take
the effort to know all the relevant information that is necessary to make a wise and
informed decision
This only highlights the need for people to become more proactive with regards to their
investment strategies and need to push themselves to be aware of all the information.

28
2.5.2 Anchoring
Q6. How much did you/will you be willing to spend for an engagement ring?
This question was designed to test the presence of Anchoring in people’s mind.
Although 50% of the respondents believe the accepted average cost is reasonable for an
engagement ring. 45% believe in assigning a salary scale to the cost which is clearly an
irrelevant reference point is created by the jewelry industry to maximize profits, and not
a valuation of love.
Conventional wisdom dictates that a diamond engagement ring should cost
around two months' worth of salary (Cawley, 2014). Believe it or not, this "standard" is one
of the most illogical one, as most men can't afford to devote two months of salary towards
a ring while paying for living expenses. Consequently, many go into debt in order to meet
the "standard".

29
2.5.3 Mental Accounting
Q7. Do you have special accounts/funds set aside for a vacation or a new home (or any
specific purpose) and have a Credit Card at the same time?
This question was aimed at understanding the mental accounting bias among the
current general public. According to the figures, 66% of the populatio do not have a special
fund set aside while having a credit card as well.
This could mainly be due to the living condition experienced by the sample set
who’ve answered the survey. Since the majority of the respondents fell into the 21-29 age
category, it could also be that the current generation is less into saving and more into
making easier lifestyle choices that reduce their existing debts , if any.
By all means, it is a relief to see that there are lesser people out there affected by
Mental Accounting Bias. People often have a special "money jar" or fund set aside for a
vacation or a new home, while still carrying considerable credit card debt as discussed in
the literature review.

30
Q8. Do/Would you spend “found money” (bonuses, incentives, raffle, etc.) in a much
more lavish manner than compared to that of your salary?
Although not by a bigger margin, however, there are people out there affected well
by this concept. This refers to an example stated above for Mental Accounting, where
people tend to use ‘found money’ a lot more than their normal income, such as paychecks.
Logically speaking, money should be interchangeable, regardless of its origin.
Treating money differently because it comes from a different source violates that logical
premise. Where the money came from should not be a factor in how much of it has been
spend - regardless of the money's source, spending it will represent a drop in one’s overall
wealth.

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2.5.4 Confirmation Bias
Q9. For example, you hear about a product for the first time – excellent review with
rich features that fit your requirements. While researching about the product, have
you felt that you tend to pay more attention to information that support your original
review and ignore or rationalize the rest (negatives)?
Confirmation bias represents a tendency to focus on information that confirms
some pre-existing thought (Shefrin, 2002). The above graph illustrates that 56% of people
tend to stick with the first information they received while researching about it. At the
same time there is an evidence of 44% to show that there is a tendency for people to
consider the negative factors as well. This is a hopeful scenario as it shows not all people
are thinking the same way. Part of the problem with confirmation bias is that being aware
of it isn't good enough to prevent it. One solution to overcoming this bias would be finding
someone to act as a "dissenting voice of reason". That way the investor shall be confronted
with a contrary viewpoint to examine.

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2.5.6 Hindsight Bias
Q10. Think of a past event in your life where you had to make a financial decision and
its outcome was unfavorable. Looking back on that event today, would you say that
there were signs for it to have an unfavorable outcome and could have been avoided?
A staggering 83.33% of respondents are experiencing Hindsight Bias and most
likely a majority of those do not even know there exists such a psychological concept.
People should be careful when evaluating how past events affect the present, especially
when considering their own ability to predict how current events will impact the future.
Believing that one is able to predict future results can lead to overconfidence, and
overconfidence can lead to making choices that most often end up catastrophic.

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2.6 Recommendation
It is no rocket-science that the cause for recessions (in any form – DOTCOM, The
Great Recession, etc.) ultimately are investors as a whole – let it be small-time individual
investors or large-scale mutual/hedge funds. Considering the fact that, if not all, most of
the behavioral finance concepts help identifying the emotional factors that affect the
decision making process of such investors which clearly the majority is not aware of,
brings about the need for its awareness in the general public. The simple fact of being
aware that there are emotional factors which are most often not in their control shall make
them more conscious and reserved about their investment choices. It will urge them to do
further research and study in depth about their portfolio choices, which will eventually
result in favorable outcomes.
The one way this need for awareness about behavioral finance can be achieved is
through education. Currently, behavioral finance is still in its early stages of development
as a concrete theory. It is only included as a module, sometimes even a chapter, for those
opting to enter the world of finance.
Behavioral finance should be included on an academic level in its most basic form
for students of every field of study – be it engineering, medical, media etc. This is will help
the younger generation, presumably the future investors, to become much more rational
and efficient in their decision making. This in turn shall make the world of finance a much
better place and less prone to meltdowns and crashes.

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4
Conclusion
This brief introduction to behavioral finance has only touched a few points. More
extensive analysis can be found in Barberis and Thaler (2003), Hirshliefer (2001), Shefrin
(2000), and Shiller (2000).
So what can be done by knowing the many principles of behavioral finance? “Very
little; I have 40 years of experience with this, and I still commit these errors. Knowing the errors is not the
recipe to avoiding them,” said Daniel Kahneman, at CFA Institute’s 2012 Annual Conference.
In fact, he feels that organizations can improve the quality of thinking, but that individuals
cannot do as much.
Whether it's mental accounting, irrelevant anchoring or just following the herd,
chances are everyone is guilty of at least some of the biases and irrational behavior

35
highlighted in this dissertation. Now that some of these biases can be identified, it's time
to apply that knowledge and if need be take corrective action. It will also help future
financial decisions be a bit more rational and lot more lucrative as well.
In conclusion, human element cannot be taken out of human decisions or
institutions. But an understanding of how the human mind works, can help make better
investment/purchase decisions.

36
References
Barberis, N. and Thaler, R. (2003). A Survey of Behavioral Finance. SSRN Journal.
Belsky, G. and Gilovich, T. (1999). Why smart people make big money mistakes--and how
to correct them. New York, NY: Simon & Schuster.
Carter, C., Kaufmann, L. and Michel, A. (2007). Behavioral supply management: a
taxonomy of judgment and decision‐making biases. International Journal of
Physical Distribution & Logistics Management, 37(8), pp.631-669.
Cawley, L. (2014). De Beers myth: Do people spend a month's salary on a diamond
engagement ring? - BBC News. [online] BBC News. Available at:
http://www.bbc.com/news/magazine-27371208.
DeBondt, W., Shefrin, H., Muradoglu, Y. and Staikouras, S. (2008). Behavioural Finance:
Quo Vadis?. Journal of Applied Finance, 19, pp.7-21.
Eriksson, L. and Wiedersheim-Paul, F. (1997). Att utreda, forska och rapportera.
Stockholm: Liber ekonomi.
Fama, E. (1998). Market Efficiency, Long-Term Returns, and Behavioral Finance. SSRN
Journal.
Foulke, D. (2014). Behavioral Bias Bingo - Mental Accounting - Alpha Architect. [online]
Alpha Architect. Available at:
http://blog.alphaarchitect.com/2014/09/04/behavioral-bias-bingo-mental-
accounting/
Fromlet, H. (2001). Behavioral Finance-Theory and Practical Application. Business
Economics, 36(3), p.63.
Gilson, R. and Kraakman, R. (2002). The Mechanisms of Market Efficiency Twenty Years
Later: The Hindsight Bias. SSRN Journal.
Hirshleifer, D. (2001). Investor Psychology and Asset Pricing. SSRN Journal.
Hirshleifer, D. and Hong Teoh, S. (2003). Herd Behaviour and Cascading in Capital
Markets: a Review and Synthesis. European Financial Management, 9(1), pp.25-
66.
Holme, I. and Solvang, B. (1996). Metodevalg og metodebruk. [Oslo]: Tano.
Johnson, J., Tellis, G. and MacInnis, D. (2005). Losers, Winners, and Biased Trades.
Journal of Consumer Research, 32(2), pp.324-329.
Johnsson, M., Lindblom, H. and Platan, P. (2002). Behavioral Finance - And the Change of
Investor Behavior during and After the Speculative Bubble At the End of the 1990s.
Postgraduate. Lund University - School of Economics and Management.

37
Kahneman, D. and Tversky, A. (1979). Prospect Theory: An Analysis of Decision under
Risk. Econometrica, 47(2), p.263.
Kartašova, J. (2013). Factors Forming Irrational Lithuanian Individual Investors’
Behaviour. Business Systems And Economics, 3(1), Pp.70 - 79.
Kauffman, R. and Wood, C. (2005). The effects of shilling on final bid prices in online
auctions. Electronic Commerce Research and Applications, 4(1), pp.21-34.
Montier, J. (2006). Behaving Badly. SSRN Journal.
Olsen, R. (1998). Behavioral Finance and Its Implications for Stock-Price Volatility.
Financial Analysts Journal, 54(2), pp.10-18.
Phung, A. (2007). Behavioral Finance: Introduction | Investopedia. [online] Investopedia.
Available at: http://www.investopedia.com/university/behavioral_finance/
Ricciardi, V. and Simon, H. (2000). What is Behavioral Finance?. Business, Education &
Technology Journal, 2(2), pp.1-9.
Ritter, J. (2003). Behavioral Finance. Pacific-Basin Finance Journal, 11(4), pp.429-437.
Rozeff, M. and Kinney, W. (1976). Capital market seasonality: The case of stock returns.
Journal of Financial Economics, 3(4), pp.379-402.
Shefrin, H. (2000). Beyond greed and fear. Boston, Mass.: Harvard Business School Press.
Shiller, R. (2000). Irrational exuberance. Princeton, NJ: Princeton University Press.
Shiller, R. (2001). Human Behavior And The Efficiency Of The Financial System. pp.1305-
1340.
Svenning, C. (1997). Metodboken. Eslöv.
Thaler, R. (1988). Anomalies: The Winner's Curse. Journal of Economic Perspectives, 2(1),
pp.191-202.
Thaler, R. (2008). Mental Accounting and Consumer Choice. Marketing Science, 27(1),
pp.15-25.
Thurén, T. (1991). Vetenskapsteori för nybörjare. Stockholm: Runa.
Tripathy, C. (n.d.). Role of Psychological Biases in the Cognitive Decision Making Process
of Individual Investors. Orissa Journal of Commerce, XXXIV(1), pp.69-80.
Yin, R. (1994). Case study research. Thousand Oaks: Sage Publications.

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Appendix A – Questionnaire
“Your honest feedback is of highest importance in the course of my academic research. This
information will not be used to serve any other purpose.”
1. What is your Gender?
a. Male
b. Female
2. What is your age?
a. 17 or younger
b. 18 – 20
c. 21 – 29
d. 30 – 39
e. 40 – 49
f. 50 – 59
g. 60 and above
3. What is your major area of study/profession?
a. Business/Economics
b. Law
c. Engineering
d. Healthcare
e. Media/Culture
f. Education
g. Other (please specify)
4. Are you aware of the concept – Behavioral Finance?
a. Yes
b. No
c. Heard about it, not sure!
5. Do you believe that factors you're not aware of, affect your investment/purchase
decisions?
a. Yes (there are factors that I'm not aware of)

39
b. No (I'm fully aware of all the factors)
6. How much did you/will you be willing to spend for your engagement ring?
a. One Month Salary
b. Two Months’ Salary
c. Three Months’ Salary
d. Average Accepted Cost
e. Others (please specify)
7. Do you have special accounts/funds set aside for a vacation or a new home (or any
specific purpose) AND have a Credit Card at the same time?
a. Yes
b. No
8. Do/Would you spend "found money" (bonuses, incentives, raffle, etc.) in a much
more lavish manner than compared to that of your salary?
a. Yes
b. No
9. For example, you hear about a product for the first time - excellent review with
rich features that fit your requirements. While researching about the product, have
you felt that you tend to pay more attention to information that support your
original review and ignore or rationalize the rest (negatives)?
a. Yes
b. No
10. Think of a past event in your life where you had to make a financial decision and
its outcome was unfavorable. Looking back on that event today, would you say
that there were signs for it to have an unfavorable outcome and could have been
avoided?
a. Yes
b. No

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Appendix B – Results Analysis
This appendix presents all 10 questions results analysis. Seven of them have already been
presented in Data Collection and Analysis. Three of them were performed but the results
were not interesting enough to be presented and analyzed in the chapter. However, the
remaining three results are presented here for the completeness of the statistical research.

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42

43

44

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