Behavioral Finance 1

Week 1
Introduction and History of Behavioral Finance

People in standard finance are rational. People in behavioral

finance are normal.
—Meir Statman, Ph.D., Santa Clara University

1. Definition
2. Emergence
3. Key Figures In Behavioral Finance
4. Behavioral Finance Micro Versus Behavioral Finance Macro
5. The Great Debates Of Standard Finance Versus Behavioral Finance

BEHAVIORAL FINANCE: THE BIG PICTURE

 DEFINITION: Behavioral finance, commonly defined as the

application of psychology to finance.

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 Behavioral Finance 2

1. Behavioral Finance is combination of cognitive psychological

theory and conventional finance to provide explanations for why
people make irrational investment decisions.

2. Shefrin (1999), “Behavioural finance is rapidly growing area

that deals with the influence of psychology on the behaviour of
financial practitioner”.

3. W. Forbes (2009) defined behavioural finance as a science

regarding how psychology influences financial market. This view
emphasizes that the individuals are affected by psychological factors
like cognitive biases in their decision-making, rather than being
rational and wealth maximizing.

4. M. Sewell (2007) has stated that behavioural finance

challenges the theory of market efficiency by providing insights into
why and how market can be inefficient due to irrationality in human
behaviour.

5. Schindler (2007) behavioural finance is defined as the field of

finance that proposes psychological based theories to explain stock
market anomalies.

EMERGENCE:

 Became hot topic, with the rupture of the tech-stock bubble in March

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 Behavioral Finance 3
of 2000 and housing bubble.

 Resembling topics and resultant confusion like; behavioral science,

investor psychology, cognitive psychology, behavioral economics,
experimental economics, and cognitive science.

KEY FIGURES IN THE FIELD

In the past two decades, some very thoughtful people have contributed
exceptionally brilliant work to the field of behavioral finance.

1. Alan Greenspan, Federal Reserve chairman on

December 5, 1996, acknowledged economic growth with low inflation,

indicating stability. “But,” he warned, “how do we know when irrational
excitement has unduly escalated asset values, which then become subject to
unexpected and prolonged contractions as they have in Japan over the past
decade?” Mr. Greenspan’s prediction came true, and the bubble burst.

2. Professor Shiller of Yale university, in Irrational

Exuberance, warned investors that stock prices, by various historical measures,

had climbed too high. He cautioned that the “public may be very disappointed
with the performance of the stock market in coming years.”

3. Professor Richard Thaler, Ph.D. of the University of Chicago

penned a classic commentary entitled “Can the Market Add and
Subtract? Mispricing in Tech Stock Carve-Outs,”. His work explored
irrational investor behavior with a case study of 3Com Corporation

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Behavioral Finance 4
1999, a spin-off of Palm, Inc. In March 2000, Palm traded at levels
exceeding the inherent value of the shares of the original company.
“This would not happen in a rational world,” Thaler noted.

4. Professor Hersh Shefrin, Ph.D., a professor of finance at Santa

Clara University, California, in his book Beyond Greed and Fear:
Understanding Behavioral Finance and the Psychology of Investing
(2000), also predicted the demise of the asset bubble. He explored
the excess optimism created by investor’s approach to emphasizing
positive aspects of past events, while ignoring negative events.

5. Andrei Shleifer, Ph.D., of Harvard University, published an

excellent book entitled Inefficient Markets: An Introduction to
Behavioral Finance (Oxford University Press, 2000), which is a
must- read for those interested specifically in the efficient market
debate.

6. Meir Statman, Ph.D., Santa Clara University, has authored many

significant works in the field of behavioral finance, including an early
paper entitled “Behavioral Finance: Past Battles and Future
Engagements,” which is regarded as another classic in behavioral
finance. His research posed decisive questions:
What are the cognitive errors and emotions that influence
investors?
 What are investor aspirations?
 How can financial advisors and plan sponsors help investors?
 What is the nature of risk and regret?
 How do investors form portfolios?
 How important are tactical asset allocation and strategic asset
allocation?
 What determines stock returns?
 What are the effects of sentiment? Statman produces insightful
answers on all of these points.
7. Daniel Kahneman and Vernon Smith, won Nobel Prize 2002, for
“having integrated insights from psychological research into
economic science, especially concerning human judgment and
decision-making under uncertainty.”

8. Vernon Smith's experimental approach has influenced the field of

experimental economics, leading to a greater appreciation for the use of
controlled experiments to study economic behavior. His work has also
contributed to the understanding of market processes, bargaining, and
decision-making in various economic contexts.

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Behavioral Finance 5
9. Kahneman, together with Amos Tversky (deceased

in 1996), formulated prospect theory. An alternative to standard

models, prospect theory provides a better account for observed
behavior.
Kahneman also discovered that human judgment may take heuristic
shortcuts that systematically diverge from basic principles of
probability. His work has inspired a new generation of research
employing insights from cognitive psychology to enrich financial
and economic models.

BEHAVIORAL FINANCE MICRO

VERSUS BEHAVIORAL FINANCE
MACRO

Behavioral finance models and interprets phenomena ranging from

individual investor conduct to market-level outcomes. Therefore, it is
divided into two subtopics: Behavioral Finance Micro and Behavioral
Finance Macro.

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1. Behavioral Finance Micro (BFMI) examines psychological

biases and investigate their influence on asset allocation decisions.
2. Behavioral Finance Macro (BFMA) detects and describe
anomalies in the efficient market hypothesis that behavioral models may
explain.

THE TWO GREAT DEBATES OF STANDARD FINANCE

VERSUS BEHAVIORAL FINANCE
There are some key differences between traditional and behavioural
finance:
1. Traditional finance assumes that investors are rational and make de-
cisions based on all available information. On the other hand, beha-
vioural finance recognizes that investors are humans and make de-
cisions influenced by their emotions, biases, and cognitive limita-
tions.
2. Traditional finance assumes that the financial markets are efficient
and that prices reflect all available information. On the other hand,
behavioural finance believes that the financial markets are not al-
ways efficient and that there are opportunities for investors to profit
from market anomalies.
3. Traditional finance is normative, meaning that it provides guidelines on
how investors should make decisions. Behavioural finance is
descriptive, meaning that it describes how investors make decisions.

EFFICIENT MARKETS VERSUS IRRATIONAL MARKETS

During the 1970s, the standard finance theory of market efficiency became
the model of market behavior accepted by the majority of academics and a
good number of professionals. The Efficient Market Hypothesis had matured
in the previous decade, stemming from the doctoral dissertation of Eugene
Fama. Fama persuasively demonstrated that in a securities market populated
by many well-informed investors, investments will be appropriately priced
and will reflect all available information.
An efficient market can basically be defined as a market wherein large

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 Behavioral Finance 7
numbers of rational investors act to maximize profits in the direction of
individual securities.
The Efficient Market Hypothesis (EMH) states that the stock asset prices
indicate all relevant information very quickly and rationally. Such
information is shared universally, making it impossible for investors to earn
above-average returns consistently. The assumptions of this theory are
criticized highly by behavioral economists or others who believe in the
inherent inefficiencies of the market.

Assumptions of efficient market hypothesis

The efficient market hypothesis only holds if the following assumptions
are met:
1. All market participants have equal access to historical data on stock
prices, and both public and private information is available. This condition
proves that no arbitrage opportunity is available. Thus, none of the investors
has an advantage over the others in making investment decisions.
2. The efficient market hypothesis only holds if investors are rational,
i.e., investors are risk averse. To put it simply, if there are two investments of
the same return but of different risk, a rational investor will always prefer the
one with lower risk.
3. It is impossible to beat the market in the long run, which means that it
is impossible in the long term to consistently receive returns higher than the
market average.
4. Stock prices change randomly, i.e., trends or patterns in the past do
not allow someone to forecast their movements in the future. Therefore, the
efficient market hypothesis makes both technical and fundamental analysis
completely useless.
There are three forms of the efficient market hypothesis:

1. The
“Weak” form contends that all past market prices and data are fully reflected
in securities prices; that is, technical analysis is of little or no value.
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 Behavioral Finance 8
• Technical analysis is a method used in the financial markets, to
evaluate and predict future price movements of assets, such as stocks,
commodities and currencies based on historical price and volume data.
The primary assumption behind technical analysis is that market prices
move in trends and makes patterns as they move, and these patterns can
be identified and analysed to make informed trading decisions.
2. The
“Semi-strong” form contends that all publicly available information is fully
reflected in securities prices; that is, fundamental analysis is of no value.
• Fundamental analysis is usually done from a macro to micro
perspective to identify securities that are not correctly priced by the
market. Analysts typically study, in order:
• The overall state of the economy
• The strength of the specific industry
• The financial performance of the company issuing the stock
• This ensures they arrive at a fair market value for the stock.
3. The
“Strong” form contends that all information is fully reflected in securities
prices; that is, insider information is of no value.

If a market is efficient, then no amount of information or rigorous

analysis can be expected to result in outperformance of a selected bench-
mark.

TYPES OF ANOMALIES
‘Anomaly’ in general is nothing but the deviation from what is set as
a standard which is being expected in normal parlances. (Tversky &
Kahneman, 1986).

If markets are truly efficient and current prices fully reflect all pertinent
information, then trading securities in an attempt to surpass a benchmark is
a game of luck, not skill.
Many studies do indeed point to evidence that supports the efficient
market hypothesis. Researchers have documented numerous, persistent
anomalies, however, that contradict the efficient market hypothesis. There
are three main types of market anomalies: Fundamental Anomalies, Technical
Anomalies, and Calendar Anomalies.

Fundamental Anomalies. Irregularities that emerge when a stock’s

performance is considered in light of a fundamental assessment of the
stock’s value are known as fundamental anomalies. Many people, for
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Behavioral Finance 9
example, are unaware that value investing—one of the most popular and
effective investment methods—is based on fundamental anomalies in the
efficient market hypothesis. There is a large body of evidence documenting
that investors consistently overestimate the prospects of growth companies
and underestimate the value of out-of-favor companies.

Technical Anomalies. Another major debate in the investing world revolves

around whether past securities prices can be used to predict future securities
prices. “Technical analysis” encompasses a number of techniques that
attempt to forecast securities prices by studying past prices. Sometimes,
technical analysis reveals inconsistencies with respect to the efficient market
hypothesis; these are technical anomalies. Common technical analysis
strategies are based on relative strength and moving averages, as well as on
support and resistance. While a full discussion of these strategies would
prove too intricate for our purposes, there are many excellent books on the
subject of technical analysis. In general, the majority of research-focused
technical analysis trading methods (and, therefore, by extension, the weak-
form efficient market hypothesis) finds that prices adjust rapidly in response
to new stock market information and that technical analysis techniques are
not likely to provide any ad- vantage to investors who use them. However,
proponents continue to argue the validity of certain technical strategies.

Calendar Anomalies. One calendar anomaly is known as “The January

Effect.” Historically, stocks in general and small stocks in particular have
delivered abnormally high returns during the month of January. Robert
Haugen and Philippe Jorion, two researchers on the subject, note that “the
January Effect is, perhaps, the best-known example of anomalous behavior
in security markets throughout the world.”13 The January Effect is
particularly illuminating because it hasn’t disappeared, despite being well
known for 25 years (according to arbitrage theory, anomalies should
disappear as traders attempt to exploit them in advance).
The January Effect is attributed to stocks rebounding following year-
end tax selling. Individual stocks depressed near year-end are more likely to
be sold for tax-loss harvesting. Some researchers have also begun to identify
a “December Effect,” which stems both from the requirement that many
mutual funds report holdings as well as from investors buying in advance of
potential January increases.
Additionally, there is a Turn-of-the-Month Effect. Studies have
shown that stocks show higher returns on the last and on the first four days
of each month relative to the other days.
Validity exists in both the efficient market and the anomalous market
theories. In reality, markets are neither perfectly efficient nor completely
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anomalous. In markets exhibiting substantial inefficiency, savvy investors
can strive to outperform less savvy investors.

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 Behavioral Finance 11

RATIONAL ECONOMIC MAN VERSUS BEHAVIORALLY BIASED MAN

Stemming from neoclassical economics, Homo economicus is a simple

model of human economic behavior, which assumes that principles of
perfect self-interest, perfect rationality, and perfect information govern
economic decisions of individuals. Economists like to use the concept of
rational economic man for two primary reasons: (1) Homo economicus
makes economic analysis relatively simple. (2) Homo economicus allows
economists to quantify their findings, making their work more elegant and
easier to digest.
Most criticisms of Homo-economicus proceed be challenging the bases
for these three underlying assumptions—perfect rationality, perfect self-
interest, and perfect information.
1. Perfect
Rationality. When humans are rational, they have the ability to reason and to
make beneficial judgments. However, rationality is not the sole driver of
human behavior. In fact, it may not even be the primary driver, as many
psychologists believe that the human intellect is actually subservient to human
emotion. They contend, therefore, that human behavior is less the product of
logic than of subjective impulses, such as fear, love, hate, pleasure, and pain.
Humans use their intellect only to achieve or to avoid these emotional
outcomes.
2. Perfect Self-Interest. Many studies have shown that
people are not perfectly self-interested. If they were, philanthropy
would not exist. Religions prizing selflessness, sacrifice, and
kindness to strangers would also be unlikely to prevail as they have
over centuries. Perfect self-interest would preclude people from
performing such unselfish deeds as volunteering, helping the needy,
or serving in the military. It would also rule out self-destructive
behavior, such as suicide, alcoholism, and substance abuse.
3. Perfect Information. Some people may possess perfect or near-
perfect information on certain subjects; a doctor or a dentist, one would
hope, is impeccably versed in his or her field. It is impossible, however,
for every person to enjoy perfect knowledge of every subject. In the
world of investing, there is nearly an infinite amount to know and learn;
and even the most successful investors don’t master all disciplines.
Again, as with market efficiency, human rationality rarely manifests in
black or white absolutes. It is better modeled across a spectrum of gray.
People are neither perfectly rational nor perfectly irrational; they possess

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diverse combinations of rational and irrational characteristics, and benefit
from different degrees of enlightenment with respect to different issues.

HOW PRACTICAL APPLICATION OF

BEHAVIORAL FINANCE CAN CREATE A
SUCCESSFUL ADVISORY RELATIONSHIP

Wealth management practitioners have different ways of measuring the

success of an advisory relationship. Few could argue that every successful
relationship shares some fundamental characteristics:

■ The advisor understands the client’s financial goals.

■ The
advisor maintains a systematic (consistent) approach to advising the client.
■ The advisor delivers what the client expects.
■ The relationship benefits both client and advisor.

So, how can behavioral finance help?

Formulating Financial Goals

Experienced financial advisors know that defining financial goals is critical

to creating an investment program appropriate for the client. To best define
financial goals, it is helpful to understand the psychology and the emotions
underlying the decisions behind creating the goals. Upcoming chapters in
this book will suggest ways in which advisors can use behavioral finance to
discern why investors are setting the goals that they are. Such insights equip
the advisor in deepening the bond with the client, producing a better
investment outcome and achieving a better advisory relationship.

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Maintaining a Consistent Approach

Most successful advisors exercise a consistent approach to delivering wealth

management services. Incorporating the benefits of behavioral finance can
become part of that discipline and would not mandate large-scale changes in
the advisor’s methods. Behavioral finance can also add more
professionalism and structure to the relationship because advisors can use it
in the process for getting to know the client, which precedes the delivery of
any actual investment advice. This step will be appreciated by clients, and it
will make the relationship more successful.

Delivering What the Client Expects

Perhaps there is no other aspect of the advisory relationship that could
benefit more from behavioral finance. Addressing client expectations is
essential to a successful relationship; in many unfortunate instances, the ad-
visor doesn’t deliver the client’s expectations because the advisor doesn’t
understand the needs of the client. Behavioral finance provides a context in
which the advisor can take a step back and attempt to really understand the
motivations of the client. Having gotten to the root of the client’s
expectations, the advisor is then more equipped to help realize them.

Ensuring Mutual Benefits

There is no question that measures taken that result in happier, more satisfied
clients will also improve the advisor’s practice and work life. Incorporating
insights from behavioral finance into the advisory relationship will enhance
that relationship, and it will lead to more fruitful results.
It is well known by those in the individual investor advisory business
that investment results are not the primary reason that a client seeks a new
advisor. The number-one reason that practitioners lose clients is that clients
do not feel as though their advisors understand, or attempt to understand, the
clients’ financial objectives—resulting in poor relationships. The primary
benefit that behavioral finance offers is the ability to develop a strong bond
between client and advisor. By getting inside the head of the client and
developing a comprehensive grasp of his or her motives and fears, the
advisor can help the client to better understand why a portfolio is designed
the way it is and why it is the “right” portfolio for him or her—regardless of

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what happens from day to day in the markets.

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The History of Behavioral Finance 33

The History of Behavioral Finance Micro

1. The existence of irrationality and Tulipomania of (1634–1637).
2. Adam Simth’s “The Theory of Moral Sentiments"(1759), focused on elements like pride,
shame, insecurity, and egotism
 Vanity and the desire of wealth
3. Jeremy Bentham (1748-1832), philosopher, economist and jurist, the founder of modern
utilitarianism. His utilitarian theory is an ethical theory holding that actions are morally right
if they tend to promote happiness or pleasure.
4. Smith, Bentham, and others recognized the role of psychology in economic behavior, but their
consensus lost ground over the course of the next century, because neoclassical economists
distanced themselves from psychology, and conceived “Homo economicus,” or rational
economic man because it suits their mathematical model of utility/profit maximization.
RATIONAL ECONOMIC MAN
 Homo economicus is a simple model of human economic behavior, which assumes that
principles of perfect self-interest, perfect rationality, and perfect information govern economic decisions
of individuals.

 Economists Thorstein Veblen, J. M. Keynes, and many others criticized Homo economicus, and
supported, “bounded rationality,” of Herber Simon (1959).

 Bounded rationality assumes that individuals’ choices are rational but subject to cognitive,
personal, social and temporal limitations. Such limitations can lead to “irrational” behavior while making
economic decisions

MODERN BEHAVIORAL FINANCE

By the early twentieth century, neoclassical economics had largely displaced psychology as an
influence in economic discourse. In the 1930s and 1950s, however, a number of important events laid
the groundwork for the renaissance of behavioral economics. First, the growing field of experimental
economics examined theories of individual choice, questioning the theoretical underpinnings of Homo
economicus. Some very useful early experiments generated insights that would later inspire key
elements of contemporary behavioral finance.

Twentieth-Century Experimental Economics: M o d e l i n g I n d i v i d u a l Choice

 In order to understand why economists began experimenting with actual people to assess the
validity of rational economic theories, it is necessary to understand indifference curves.

 An indifference curve shows a combination of two goods in various quantities that provides

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equal satisfaction (utility) to an individual. It is used in economics to describe the point where
individuals have no particular preference for either one good or another based on their relative quantities.

 Louis Leon Thurstone in 1931 performed on individuals’ actual indifference curves. Thurstone
found that it was possible to estimate a curve that fit fairly closely to the data collected for choices
involving shoes and coats and other subsets of the experiment.

 Stephen W. Rousseas and Albert G. Hart in 1940 performed some experiments on indifference
curves. They required that “each individual was obliged to eat all of what he chose; i.e., he could not
save any part of the offerings for a future time.” Their experiment presented complications, but overall
the project was considered a success and led to further experiments in the same vein.

 Thurstone, Frederick Mosteller and Phillip Nogee sought in 1951 to test expected utility theory
by experimentally constructing utility curves. Mosteller and Nogee tested subjects’ willingness to accept
lotteries with given varying payoff probabilities. As these types of experiments continued, various
violations of expected utility were beginning to be observed.

 Maurice Allais, perhaps the most famous of violations of expected utility was exposed by
another Alfred Nobel Memorial Prize in Economic Sciences winner (1988), he is perhaps best known
for his studies of risk theory and showed that the theory of maximization of expected utility, did not
apply to certain empirically realistic decisions under risk and uncertainty.

As the 1950s concluded and the 1960s progressed, the field of experimental economics expanded,
that brought to light new aspects of human economic decision making and drew intellectual attention to
the field. Concurrently, two more intellectual disciplines were emerging that would contribute to the
field of behavioral finance: cognitive psychology and decision theory.

Cognitive Psychology
Many scholars of contemporary behavioral finance feel that the field’s most direct roots are in cognitive
psychology. Cognitive psychology is the scientific study of cognition, or the mental processes that are
believed to drive human behavior. Research in cognitive psychology investigates a variety of topics,
including memory, attention, perception, knowledge representation, reasoning, creativity, and problem
solving.

Applying cognitive psychology, psychologists Amos Tversky and Daniel Kahneman developed
“prospect theory” that is viewed as the intellectual foundation of behavioral finance micro. Tversky and
Kahneman examined mental processes as they directly relate to decision making under conditions of
uncertainty.

Decision Making under Uncertainty

 Simple and insignificant decisions VS complex and significant decision

 Howard Raiffa In 1968, in Decision Analysis: Introductory Lectures on Choices under

Uncertainty, decision theorist Howard Raiffa introduced three approaches that provide a more accurate
view of a “real” person’s thought process.
o Normative analysis is concerned with the rational solution to the problem at hand. It defines an
ideals and provides theoretical framework for making decisions.
o Descriptive analysis is concerned with the manner in which real people actually make decisions.
o Prescriptive analysis is concerned with practical advice and tools that might help people achieve
results more closely approximating those of normative analysis.
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Raiffa’s contribution laid the foundation for a significant work in the field of behavioral finance
micro.
 Daniel Kahneman and Mark Riepe published an article, “Aspects of Investor Psychology:
Beliefs, Preferences, and Biases Investment Advisors Should Know About.”
o According to Kahneman and Riepe, advising investors need to know cognitive and emotional
weaknesses of investors.
o This work leveraged the decision theory work of Howard Raiffa, categorizing behavioral
biases on three grounds:
 (1) biases of judgment which include:
 overconfidence,
 optimism,
 hindsight, and
 overreaction to chance events.
 (2) errors of preference which include:
 Non-linear weighting of probabilities;
 the tendency of people to value changes, not states;
 the value of gains and losses as a function;
 the shape and attractiveness of gambles;
 the use of purchase price as a reference point;
 narrow framing;
 tendencies related to repeated gambles and risk policies; and
 the adoption of short versus long views.
 (3) biases associated with living with the consequences of decisions:
 gives rise to regrets of omission and commission, and
 also has implications regarding the relationship between regret and risk taking.
 Kahnemann and Tversky, began research on decision making under uncertainty. This work
ultimately produced a very important book published in 1982 entitled Judgment under Uncertainty:
Heuristics and Biases.
 Kahnemann and Tversky, Building on the success of their 1974 paper, the two researchers
published in 1979 what is now considered the seminal work in behavioral finance: “Prospect Theory:
An Analysis of Decision under Risk.”

PROSPECT THEORY

Prospect theory, in essence, describes how individuals evaluate gains and losses. The theory names
two specific thought processes: editing and evaluation. During the editing state, alternatives are ranked
according to a basic “rule of thumb” (heuristic), which contrasts with the elaborate algorithm in the
previous section. Then, during the evaluation phase, some reference point that provides a relative basis
for appraising gains and losses is designated. A value function, passing through this reference point
and assigning a “value” to each positive or negative outcome, is S shaped and asymmetrical in order to
reflect loss aversion (i.e., the tendency to feel the impact of losses more than gains). This can also be
thought of as risk seeking in domain losses (the reflection effect). Figure 2.4 depicts a value function,
as typically diagrammed in prospect theory.
It is important to note that prospect theory also observes how people mentally “frame” predicted
outcomes, often in very subjective terms; this accordingly affects expected utility. An exemplary
instance of framing is given by the experimental data cited in the 1979 article by Kahneman and
Tversky, where they reported that they presented groups of subjects with a number of problems. One
group was presented with this problem:
1. In addition to whatever you own, you have been given $1,000. You are now asked to
choose between:
A. A sure gain of $500.
B. A 50 percent chance to gain $1,000 and a 50 percent chance to gain nothing.

Another group of subjects was presented with a different problem:

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2. In addition to whatever you own, you have been given $2,000. You are now asked to
choose between:
A. A sure loss of $500.
B. A 50 percent chance to lose $1,000 and a 50 percent chance to lose nothing.

In the first group, 84 percent of participants chose A. In the second group, the majority, 69 percent,
opted for B. The net expected value of the two prospective prizes was, in each instance, identical.
However, the phrasing of the question caused the problems to be interpreted differently.

FIGURE 2.4 The Value Function—a Key Tenet of Prospect Theory

PSYCHOGRAPHIC MODELS USED IN BEHAVIORAL FINANCE

Psychographic models are designed to classify individuals according to certain characteristics,
tendencies, or behaviors. Psychographic classifications are particularly relevant with regard to
individual strategy and risk tolerance. An investor’s background and past experiences can play a
significant role in decisions made during the asset allocation process. If investors fitting specific
psychographic profiles are more likely to exhibit specific investor biases, then practitioners can attempt
to recognize the relevant telltale behavioral tendencies before investment decisions are made.
Hopefully, resulting considerations would yield better investment outcomes.
Two studies—Barnewall (1987) and Bailard, Biehl, and Kaiser (1986)
—apply useful models of investor psychographics.

Barnewall Two-Way Model

 Barnewall Two-way Behavioral Model – Perhaps, this is the simplest of the three models
discussed in this reading. The two-way model classifies investors into one of two categories:
I. Active investors.
II. Passive investors.
According to this model, active investors risk their capital to gain wealth. For instance, an active
investor could start and sell a business. On the other hand, passive investors accumulate their
wealth through small, consistent gains. For example, passive investors can sustain their investment
through long and steady employment. Absent other factors to look at, the model explains that
active investors are likely more tolerant of risk since they have previously shown a predilection
for taking on financial risk. On the other hand, passive investors tend to prefer safer and slower
methods.
 The Bailard, Biehl, and Kaiser (BB&K) Five-Way Model –

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An advancement of the Barnewall two-way model, the BB&K model adds a few extra categories
into which investors may be classified. The model uses a vertical axis on which it measures the
degree of confidence versus the degree of anxiousness and a horizontal axis on which it measures
careful versus impetuous decision-making.

The Adventurer—People who are willing to put it all on one bet and go for it because they have
confidence. They are difficult to advise, because they have their own ideas about investing. They
are willing to take risks, and they are volatile clients from an investment counsel point of view.

The Celebrity—These people like to be where the action is. They are afraid of being left out.
They really do not have their own ideas about investments. They may have their own ideas about
other things in life, but not investing. As a result they are the best prey for maximum broker
turnover.

The Individualist—These people tend to go their own way and are typified by the small business
person or an independent professional, such as a lawyer, CPA, or engineer. These are people who
are trying to make their own decisions in life, carefully going about things, having a certain
degree of confidence about them, but also being careful, methodical, and analytical. These are
clients whom everyone is looking for—rational investors with whom the portfolio manager can
talk sense.

The Guardian—Typically as people get older and begin considering retirement, they approach
this personality profile. They are careful and a little bit worried about their money. They
recognize that they face a limited earning time span and have to preserve their assets. They are
definitely not interested in volatility or excitement. Guardians lack confidence in their ability to
forecast the future or to understand where to put money, so they look for guidance.

The Straight Arrow—These people are so well balanced, they can- not be placed in any specific
quadrant, so they fall near the center. On average this group of clients is the average investor, a
relatively balanced composite of each of the other four investor types, and by implication a group
willing to be exposed to medium amounts of risk.

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