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Behavioral Finance: The Psychology of Investing


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Just studying the Behavioral Finance these days, and trying to get as much informations as I can, I found this amazing Article of CREDIT SUISSE SECURITIES (USA), wich is in fact a research that tries to shed light on the emotional and psychological influence that can impact financial decisions and how this influence can result in irrational behavior. Traditional finance, based on the hypothesis of efficient markets and the optimization of statistical figures such as means and variances, suggests that investing has a lot to do with mathematics. However, behavioral finance has put the spotlight back on people. People make mistakes – even in investment decisions, which results in inefficiencies at the market level. Based on behavioral finance, investment is 80% psychology. In the meantime, behavioral finance has created methods that can help investors identify typical mistakes while finding the right portfolio for them.
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Research conducted by Professor Dr. Thorsten Hens and MSc. BA Anna Meier
from Behavioral Finance Solutions GmbH
Behavioral Finance:
The Psychology of Investing
Private Banking North America
a spin off rm of the University of Zürich
fc2 CREDIT SUISSE Private Banking North America
This document is not complete without the attached important disclosures.
Introduction and welcome 1
Orientation 2
History of portfolio theory 3
Behavioral biases 10
Cultural differences in investor behavior 18
Neurofinance: a new branch of behavioral finance 25
Market anomalies 27
Wealth management approach 32
Conclusion 41
Bibliography 42
About the contributors 43
Tables of figures 44
Introduction and Welcome
Dear Reader,
We are delighted to present to you Behavioral Finance: The Psychology of Investing, a
white paper developed in collaboration with the University of Zürich. This report is intended
to shed light on the emotional and psychological influence that can impact financial decisions
and how this influence can result in irrational behavior. It also explores how to avoid the
pitfalls that investors commonly face.
Behavioral finance is a fairly novel topic that has gained prominence since the early 1990s.
Amos Tversky and Daniel Kahneman, winners of the 2002 Nobel Memorial Prize in
Economic Sciences, helped popularize the topic with their development of Prospect Theory.
Psychology plays a big part in investing. Understanding the psychological motivations can
help investors avoid financial pitfalls.
Behavioral finance bridges the gap between theory and practice by scientifically recording
human behavior. To date, research has focused on rational investors in efficient markets,
while reality deals with day-to-day irrational investor behaviors and inefficient markets.
Combining theory and practice allows us to use behavioral finance as the basis for advisory
services, asset management, and financial product development.
At Credit Suisse, our holistic approach to providing clients with wealth management
advice transcends the traditional financial advisory relationship. Our wealth management
process enables us to understand our clients’ needs and rationale in making financial
decisions, and to assess their risk appetite and behavioral bias. Credit Suisse has had the
privilege of serving many of the world’s wealthiest individuals and families since 1856,
proving our commitment to the needs of our clients and society.
We hope you find this white paper insightful and useful.
Barbara Reinhard
Chief Investment Officer
Private Banking Americas
Credit Suisse
2CREDIT SUISSE Private Banking North America
This white paper is divided into five sections that should be read in sequential order.
The figure below shows which sections are prerequisites for later sections. Naturally, the introduction to each section is important.
However, should you skip the remainder of each section, only the section on market anomalies will be difficult to understand
without a solid background. Behavioral biases are the basis for understanding cultural differences, which in turn are the basis for
understanding neurofinance. Behavioral biases are also fundamental to selecting a wealth management approach.
The small arrows in the middle of the figure show the typical reading pattern. The large arrows on the right show the
prerequisites; here, you should refer back to the indicated sections.
Figure I: Orientation
Behavioral Biases
Cultural Differences
Market Anomalies
Wealth Management Approach
History of Portfolio Theory
Although the present functions without the past, we can understand it better if we look at its historical developments step by
step. The same is true for financial market research. This research currently consists of fairly complicated mathematical and
psychological models that, at first glance, can be confusing. The figure below highlights the history of portfolio theory, one of the
primary areas of financial market research.
The first person to focus on how we make decisions in uncertain situations was French mathematician Blaise Pascal, who did this
in 1670. Pascal looked at fairly simple situations and wondered which would be preferable. For instance:
a) a coin toss in which one could win 6 francs for heads but only 2 francs for tails, or
b) a coin toss in which one could win 9 francs for heads or 1 franc for tails
Pascal’s suggestion was to make the decision based on the expected value, or the average payout.
Figure 2: Milestones of Portfolio Theory
1600 1700 1800 1900 2000
Blaise Pascal (1670):
Expected Value
Daniel Bernoulli (1738):
Utility Function (descriptive)
Kahneman and Tversky (1979):
Portfolio Theory
Harry Markowitz (1952):
Mean Variance Model
Von Neumann and Morgensten (1944):
Utility Function (prescriptive)
4CREDIT SUISSE Private Banking North America
Figure 3: Sample Coin Toss
For the first coin toss, the expected value is 4; for the
second coin toss, it is 5. Therefore, in Pascal’s view, one
should choose the second coin toss. Daniel Bernoulli, a
mathematician from Basel, had the same idea when his
brother Nikolaus told him about the St. Petersburg game more
than one hundred years later. Under Blaise Pascal’s theory, the
citizens of St. Petersburg should wager every cent they had
to play on the St. Petersburg game, because it had an infinite
expected value. This contradicted the observations of Nikolaus
Bernoulli, which revealed an average payout of 2 ducats.
The average payout of 2 ducats may seem like a paradox
at first, but is explained by Daniel Bernoulli’s generalization
of the theory on calculating the expected payout. Bernoulli’s
function, as applied to Pascal’s theory, is now known as the
utility function. The utility function refers to a fundamental
psychological law, the diminishing marginal utility of money.
Or, as Daniel Bernoulli said, “There is no doubt that a gain of
1,000 ducats is more significant to the pauper than to a rich
man, though both gain the same amount.” It is important to
note that the diminishing marginal utility of money embodies
the risk aversion of the person making the decision. A decision
maker is averse to risk if, instead of a random payout, he
prefers the certainty of the expected fixed payout from a
game. The St. Petersburg game shows that the people of
St. Petersburg were averse to risk. Suppose someone made
the decision to receive the expected payout. If he chose to
gamble instead, in some cases he would win more, and in
other cases he would win less. Due to the money’s diminishing
marginal utility, the utility of the higher payout would be lower
than for a reduced payout. This is why it is more rational to
take the average payout with certainty.
Standard Deviation: (6-2)/2=2
Mean, Expected Value: (6+2)/2=4
Standard Deviation: (9-1)/2=4
Mean, Expected Value: (9+1)/2=5
6 9
2 1
History of Portfolio Theory
Figure 4: Utility Function for Various Level of Risk Aversion
Figure 4 shows the utility function
for various levels of risk aversion, α.1 The larger parameter α,
the less risk averse the decision maker.
The expected utility hypothesis offers a method of calculation
that explains a variety of observed behaviors.2 In 1944,
mathematicians John von Neumann and Oskar Morgenstern
determined that the expected utility hypothesis is also the
only criterion that allows people to make rational decisions in
uncertain situations. Every other criterion contradicted plausible
fundamental conditions for behavior, known as axioms.
One example for these axioms of rational behavior is the axiom
of independence, which states that when choosing between
two lotteries, one should consider only the differing aspects of
the lotteries.
For instance, two lotteries could each be based on throwing
one die. Neither lottery has a payout for an odd number. The
first lottery (A) has a payout for each even number, in the
amount of the number cast. The second lottery (B) has the
following payouts: a payout of zero for a two, a payout of four
for a four, and a payout of ten for a six.
The axiom of independence states that when selecting a
lottery, we can limit ourselves to those cases in which the two
or the six is cast, because the payouts of both lotteries are
identical in all other cases. Thus, the selection is reduced to
whether the player wants two and six, or zero and ten, with the
same probability.
1 A risk aversion of α = 1 denotes a risk-neutral investor.
In the example shown in Figure 3, for all levels of risk aversion α > 0.326, the
right coin toss is chosen. For alpha <0.326, the left one is chosen. For a risk
aversion of 0.326, both games are equal. This is calculated based on
. The result is 60.326 + 20. 326 = 90.326 + 10.326.
Capital + Profit/Loss
a = 1
a = 0.5
6CREDIT SUISSE Private Banking North America
This does not mean that everything had been figured
out by the middle of the twentieth century. The expected
utility hypothesis was flexible enough to illustrate different
behaviors in uncertain situations and was the only sensible
way to proceed in such situations. Unfortunately, there was
a significant weak spot in this hypothesis: Where besides a
coin toss could one find realistic probabilities for calculating
the expected utility? For instance, how can we define the
probabilities of returns on asset classes such as bonds,
equities, or alternative investments, or even single securities
within a class? These returns depend, among other things,
on economic factors such as the economy itself, monetary
policy, innovation, and growth alongside the behavior of other
stakeholders. The sum of these factors results in an almost
impossibly tangled mass of interactions. To unravel this
Gordian Knot, Eugene Fama developed his efficient market
hypothesis in the 1970s, which had its predecessors in the
1950s. If all market participants thought constantly about
the factors behind the returns on securities and developed
trading strategies based on these factors, their buying and
selling decisions would ensure that all profitable information
about these factors was priced into the securities. The market
anticipates every predictability in prices. The remaining price
developments result from previously unanticipated changes
– in other words, surprise information. Because surprises
are impossible to predict, the prices of securities develop by
pure chance, statistically independent of one another. We
know from statistics that the sum of random variables can be
defined by normal distribution (bell curve). The distribution is
well-defined by its mean and its standard deviation.
The efficient market hypothesis is a brilliant simplification
of decision-making in uncertain situations because these
decisions depend only on the mean and the standard deviation
Figure 5: Axiom of Independence
Lottery A
Lottery B
1 2 3 4 5 6
0 0 4 0
0 0 4 0
2 6
0 10
History of Portfolio Theory
of the distributions. In 1952, Harry Markowitz built on this idea
to develop his mean variance model, which was based on two
factors: returns, measured by mean, and risk, measured by
standard deviation. It was clear to Markowitz that investors
preferred a high average return with a low risk. We saw this in
the two coin tosses in Figure 3. For the first toss, the average
payout is 4 and the standard deviation is 2; for the second, the
average payout is 5 and the standard deviation is 4. Decision
makers will choose the first or the second coin toss depending
on risk tolerance (here, the aversion to fluctuating returns).
Therefore, Markowitz presented the various investment options
in a return-risk diagram such as the one shown in Figure 6.
As we can see in Figure 6, when the average return (mean) increases, the expected risk (standard deviation) of an investment
also increases. For each return level indicated, an investor can minimize his risk by diversification. This sequence of minimization
results in the efficient frontier, which denotes the minimum risk for a given return level. Depending on the individual risk tolerance
of an investor, the best portfolio can be selected on the efficient frontier.
Figure 6: Risk-Return Diagram
Efficient Frontier
Capital Protection
8CREDIT SUISSE Private Banking North America
Behavioral finance is the newest chapter in the history
of portfolio theory. Why do we yet need another theory?
Behavioral finance explains the typical mistakes (behavioral
biases) made by investors. It also provides a detailed picture
of investors’ risk preferences. This second aspect is covered
by Daniel Kahneman and Amos Tversky’s prospect theory
(1979). Unlike the Markowitz analysis, the prospect theory
focuses on the significance of investment losses. In their
studies, Kahneman and Tversky found that most investors are
averse to loss. This means that investment losses must be
compensated through the opportunity for higher returns. For
most investors, these returns must be at least twice as high as
the potential loss.3
The utility function of the prospect theory is shown in
Figure 7. A maximizer of prospect utility evaluates the result of
his investments using a reference point. For example, this can
be the purchase price of a security. Loss aversion is reflected
in the fact that the utility function initially has a much steeper
curve than the profit area. The prospect utility theory draws
from the expected utility theory the characteristic of declining
marginal utility of the gains.
The loss area reflects the declining marginal damage of the
losses. This is demonstrated by the fact that prospect utility
maximizers would risk their investment for a break-even
opportunity rather than face a definite loss. Thus, they prefer a
random payout to the expected utility if it is negative.
If markets were efficient as per Fama’s theory, all investment
returns would have normal distribution and the application
of the mean-mean standard deviation criterion would still be
justified for prospect theory investors. In reality, the efficient
market hypothesis is not valid, so very few investments
have returns with normal distribution. For this reason, the
loss aversion under the prospect theory is key to an optimal
portfolio. We must replace the efficient market line in the
mean-standard deviation model with a behavioral efficient
frontier based on the prospect theory. The behavioral efficient
frontier was first developed in a paper by Enrico De Giorgi,
Thorsten Hens, and Janos Mayer (2011). It depicts the
prospect theory using a risk-return diagram. Investment
results are broken down into cases in which a profit is made
and those in which a loss is sustained. The degree of loss
aversion determines the selection of an optimal portfolio on
the behavioral efficient frontier, as shown in Figure 8. If we
compare the prospect theory portfolios with the Markowitz
Figure 7: Utility Function of the Prospect Theory
3 To be precise, it is 2.25 times higher.
Reference Point
Loss Gain
History of Portfolio Theory
portfolios, we see that these have a lower portion of equities
and hedge funds while weighting capital protection products
more heavily. Equities and hedge funds are not largely
represented in the prospect portfolios, because of their
potential high losses. On the other hand, capital protection
products are not very common in the Markowitz portfolios.
Although they do not show a loss as long as the counterparty
does not default, they have varying levels of high returns and
thus a standard deviation. Practice has shown that clients
whose portfolios are based on the Markowitz theory do not
adhere to their investment strategy when the markets decline.
As a result, they usually miss the rebound and performance
is lower than if they had maintained their strategy. Thus, it is
worth choosing a prospect theory so that investors can stick to
the strategy both financially and emotionally.
As a result, investment advice based on current research findings must optimally position prospect theory investors
for inefficient markets.
Figure 8: The Behavioral Efcient Frontier Based on the Prospect Theory
Capital Protection Product
Price-Dividend Ratio
Behavioral Efficient Frontier
10 CREDIT SUISSE Private Banking North America
The cyclical investment process – including information procurement; stock picking; and making,
holding, and selling investments, followed by making a new selection – is full of pitfalls. These
can come at a high price to investors. As Benjamin Graham liked to say, “The worst enemy of the
investor is most likely himself.” Purchasing investments is a rapid-fire process, and the value of
these investments can decline just as rapidly – even to zero, making them a waste of money.
In this section, we will illustrate each step of the process and explain the potential pitfalls. In the next section, we will show
how you can avoid these pitfalls with the help of Credit Suisse’s wealth management approach. Let us start from the beginning:
the investment roller coaster.
Figure 9: Investment Process – Roller Coaster of Emotions
Ah, I see a trend.
I should watch
this market.
Thankfully I didn’t
wait to buy!
If I wait any
Ionger, I will not
profit from the
trend. BUY
I will use this correction to
increase my position. BUY
Wow! At this price
I will double my
position. BUY
I can’t believe it! The price
has now halved. This must be
the absolute bottom!
Ah, it will still fall...
Why doesn’t the
banking association
have anything to say
about this?
Enough is enough! I should sell and
never look at stocks again! SELL
Luckily I sold everything! What did I say?
What is going
on here?
I knew all along
that it would
Whatever, I will buy
again! Anyway, it is
cheaper than last time.
Behavioral Biases
The markets are on the rise, the stock exchanges register
record highs, and the media waters down this news. Business
journalists report on innovative, creative companies that are all
making a profit in these markets. However, they fail to see that
not all companies are successful using those same criteria.
Thus, they do not falsify the theory of success, a mistake
known as the confirmation bias. We cannot avoid reading
the headlines about price gains and booming markets or the
multitude of success stories. Unfortunately, these stories
attract the interest of many amateur investors.
Readers follow developments in the bull market with baited
breath; with some hesitation and a safe distance, they make
note of certain stocks and shares. If the media spotlights a
particular stock, it is more likely to attract investor attention.
After a certain amount of watching from the wings, some
investors will decide to participate in the uptrend before it is
too late. With the wind of so many success stories beneath
their sails, investors erroneously believe they have almost no
chance of failing. So the survival error takes hold. The media
and its readers love success stories; looking at the gossip
magazines while at the hairdresser, for instance, all we see are
glitz and glam. However, these publications only feature the
rich and famous – wealthy entrepreneurs, writers, celebrities,
singers, and other people who have made it.
Of course, there is never any mention of the hundreds of
thousands, even millions, of people who have not succeeded.
As a result, we grossly overestimate the stellar achievements
of the success stories, which are as unlikely as a winning
lottery ticket. Investors also fall victim to induction. They see a
security rise and rise, until they are certain that it can only get
better. Often they invest a large portion of their assets in this
security – resulting in a serious cluster risk – and are likely to
lose it all.
Because investors do not know they have fallen into the trap,
they look for familiar company names when trying to find a
good investment. In situations like these, it is very hard to
avoid the availability/attention bias. Events that come up
more frequently (often with additional media coverage) remain
in our minds more than events we hear about less frequently.
We forget that there are other scenarios.
On the other hand, rare, dramatic events that attract heavy
media attention are overestimated. For example, if we ask
a random person what the most common cause of death is,
he or she might say a car accident or plane crash. This is
because the media pounces on these sensational causes of
death, which then stay in our minds whether we want them to
or not. What is more, illustrated, easy-to-digest information is
easier to remember than statistical figures. This distorts our
perception between the frequency distribution and statistical
reality. As a result, investors never choose information from
the other side of the fence. Instead, they choose information
based on their experiences and preferences. This means that
we are more likely to recall the front page of a newspaper
showing a CEO racing down the French Riviera in his
convertible. We are less likely to remember that his company’s
net profit margin dropped by 30% and its earnings by 18%.
Investors make positive associations with the company
because they liked the car or the CEO had a nice smile in
the photo. They may also remember the CEO’s attractive
companion with bright red lipstick. The image in their head is a
good one, and so is their impression of the company.
Typical investors evaluate information according to how quickly
it can be recalled. This means that in most cases, we do not
continue to think of alternatives because we are satisfied with
our initial thought. Investors who remember the CEO in his
convertible associate the company with success and think it
would be a good investment.
As soon as we remember a promising company, we begin to
support our opinions about it with other publicly accessible
information. This is not very rational, as the process does not
permit a differentiated view. Once an investment has won
the investor over, he often makes the mistake of looking
for only positive information. We made reference to this at
the beginning of this section when we mentioned business
journalists. Confirmation bias is the phenomenon of supporting
our own opinions with selective information. Investors seek
confirmation for their assumptions. They avoid critical opinions
and reports, reading only those articles that put the product in
a positive light.
12 CREDIT SUISSE Private Banking North America
Suppose our investor’s boss is also interested in market
developments and likes to talk about the bull market during
his coffee breaks. And suppose this boss recommends
investing in the pharmaceuticals industry. Because the
investor is afraid to contradict his boss or would not even
consider doing so, he begins to do some research into these
investments. The coffee break scenario is a good example of
the authority pitfall that our investor falls prey to. He considers
his boss an investment authority and, right or wrong, takes
his recommendations to heart. However, the boss is no more
or less correct than his employee. Because our investor
does not know about this bias (or that he has succumbed
to it), he begins to research the earnings made by three US
pharmaceutical companies over the last few years.
The investor also reviews the returns on the companies’ stock.
Unfortunately, he looks only at the last three years. In addition,
he cannot find the profits for one of the three companies.
However, he sees that corporate revenues have grown steadily
over the last three years. Thus, he incorrectly concludes that
profits will continue to grow in the future and that the company
must be successful.
Investors do not tend to use representative data. This means
that the time period they examine is too short to determine
the statistical population. Thus, it is not possible to draw
conclusions about the statistical population. In the above
scenario, it would be wrong to draw conclusions about the
entire industry based on an analysis of three companies.
Moreover, one to three years is too short a time period to draw
a valid conclusion.
We refer to this as the law of small numbers. You may
remember learning about the law of large numbers in school.
If you toss a coin enough times, the number of times you get
heads will be essentially equal to the number of times you get
tails. Unfortunately, we often believe that this equality applies
to smaller random samples. As a result, we look forward to
very high returns based on very little information.
Behavioral Biases
…back to the roller coaster
Suppose that while researching the profits of the
pharmaceutical company, our investor finds an interesting
article in a reputable business journal. It reports on a US
company with a 40% chance of generating a 5% excess
return over the S&P 500. Our investor is so excited that he
decides to invest in this company. He probably would not have
done so if he had read that there was a 60% chance of the
company generating a less than 5% excess return over
the S&P 500. Our investor has just fallen for the framing
effect. In other words, the way information is presented will
influence our decisions.
For instance, there is a huge difference in whether a sum is
presented as a loss or a missed profit, even if these terms
mean the same thing. Therefore, our decisions are based
largely on how the data is depicted. The choice of scale on a
chart is seldom random. It is chosen intentionally to influence
the desired result as much as possible.
Such framing effects apply to everything in life. Imagine our
investor is having dinner at a friend’s house and she tells him
that she made the sauce with 80% fat-free cream. Do you
think she would have bought the cream if the package labeled
it 20% fat? Now consider the package that says 98% fat-free
as opposed to 2% fat. Most people would choose the 98%
fat-free product even though factually, it has more fat than the
product with 2% fat. Since he saved so many calories with
the meal, our investor should treat himself to another beer.
Imagine the beer bottle says 3.9% alcohol – how do you think
consumers would feel about a beer label that boasts 96.1%
A company’s presentation of a product is never random. It is
usually intended to serve the seller’s purpose, which does not
always conform to the buyer’s purpose.
Because our investor does not really care about cream sauce,
he changes the subject and boasts about the investments he
made in the stock market. He tells his friend that he invested
in high-growth, successful companies, namely equities from
Apple, Google, Facebook, and Credit Suisse. As he moves
down the list, he does not realize most of these shares are
country specific or target-customer specific.
The home bias is to blame. According to this bias, most
investors choose the majority of their equities from their home
country. These stocks seem more trustworthy, as we grew up
with these company names. They are also mentioned more
frequently in the local media. This is one reason investors do
not diversify enough, but it is far from the only reason.
Once we invest in a stock, we hope the price will go up but
worry it will go down. Of course, price developments depend
on chance. Psychologically speaking, what counts is how
we handle these fluctuations. When the price goes up, the
optimists feel satisfied with their decision. They think, “Thank
goodness I didn’t wait any longer.” However, our investor is
not the only one; everyone wants to be part of the boom (herd
instinct). This includes the pessimists, who feel lucky each
time the price increases. This herd instinct is rooted within us
and, once upon a time, was necessary for our survival.
After an uptrend phase – a phase of hoping for big profits,
for instance – the price begins to drop. The optimists will
say that these dips in price are bad luck, or a necessary
correction. The pessimists will be furious if they suffered a
loss. Pessimists do not remain invested for long – unless they
are masochists. This is why the stock market tends to attract
more optimists, who frequently invest out of hope. Thus, they
invest in innovative technologies that have a low probability
of generating enormous returns. We call this the favorite
long-shot bias.
People who fall into this psychological trap always bet on the
long shot because it promises very high returns. Unfortunately,
they forget that the likelihood of the long shot winning
cancels the profit. Of particular interest is the typical investor
behavior during long-term loss, when the downward spiral
persists and the prices plummet – a bear market. On the one
hand, investors will initially ignore all information indicating a
downward trend because such information does not support
their preconceived notion that the investment is good and that
there is an uptrend. Another common, irrational response is to
buy more stock (“I’m taking advantage of the correction and
reinforcing my position,” or, “Great, I’ll double my position at
this price”). This behavior is caused by contrast and anchoring.
14 CREDIT SUISSE Private Banking North America
When making these decisions, investors do not rely on
fundamental factors. Rather, they tend to base their decision
on the price at which the stock was purchased. This price –
also known as the acquisition cost – is the unfortunate anchor
that causes irrational decisions. Unlike the acquisition cost, the
new price seems cheap to the investor.
Anchoring influences decisions when investors do not realize
how the information is presented. People are influenced by
random data when making decisions, even if they know the
data has no informational value or is outrageously high or low.
For instance, suppose we ask one group of subjects whether
Mr. Miller died before or after the age of 90 and another group
of subjects whether he died before or after the age of 40. The
subjects will be influenced by the anchors of 90 and 40 years.
On average, those asked about 90 years would list a higher
age of death for Mr. Miller than those asked about 40 years.
But if we leave out the age entirely, most people will guess
that Mr. Miller died at about the age of 80.
People want an anchor to cling to. Not even the experts are
immune, as various experiments reveal. The price at which we
last bought something is the psychological anchor. Financial
institutions tend to provide investors with the acquisition price
in standard form or, on request, in the safekeeping account
statements (which is less sensible from a behavioral finance
standpoint, given the bias stated above).
If the price drops below the psychological anchor (such as
the purchase price), then investors are more likely to buy
because the stock seems cheap, as if it were on sale at the
supermarket. Private investors frequently will keep buying as
the losses continue. This is because they want to make up for
their initial losses. “I can’t believe it! The price is 50% lower!
That has to be a record low.” No, it does not. This behavior
can result in investors taking more and more risks, because
they have to make up for greater and greater losses. It is like a
bottomless pit.
People tend to be short-sighted, meaning that they overthink
matters fairly often. As a result, they make decisions that
they would not make over longer periods of time. Bernartzi
and Thaler (1995) showed that investors would invest more
in stocks, and thus with more risk appetite, if they made the
decisions at longer intervals. This phenomenon is known as
myopic loss aversion. Rational investors are unfamiliar with
this type of behavior. They consider the consequences of their
decision over a lifetime and not only for a limited time period.
A discretionary mandate can keep investors from falling into
the myopic loss aversion trap.
It is foreseeable that prices will rise again at some point.
Although it usually takes a longer time for prices to rise again,
the time period is not necessarily the critical factor in large
investor losses. How sharply the prices drop is far more
important. Most investors cannot handle large price losses
from an emotional standpoint. Their psychological risk ability
is too low. They suffer from insomnia, existential anxiety, or
panic attacks. They look for external help (“Why isn’t the
Bankers’ Association commenting on this?”). Financial risk
ability is usually higher than psychological risk ability. Because
psychological risk ability is initially triggered, it should be
assigned equal or even higher priority than financial risk
ability. Today’s investment advisory services pay a great
deal of attention to financial risk ability while casting aside
psychological risk ability. Although psychological risk ability is
sometimes evaluated, it rarely occurs systematically or with a
process that is proven to deliver reliable, informative results.
You may be wondering why the investor in our story does
not sell off his investments. Many private investors engage
in mental accounting, meaning they make distinctions in
their head that do not exist financially. Often, losses incurred
are viewed separately from paper losses. This means that
investors sell stocks from their portfolio too soon when they
earn a profit and too late when they incur a loss. Turning a
paper profit into real profits makes us happy, but we shy away
from turning a paper loss into a real loss. Literature refers to
this bias as the disposition effect. A second form of mental
accounting is the distinction we make between money in the
bank and money made on the financial market. The latter,
known as house money, is often placed at a greater risk than
bank balances, which usually come from savings. So mental
accounting makes us think that a dollar is not worth a dollar –
a dangerous attitude.
In addition, it is hard to admit our mistakes and confess
that the investment might not have been the cash cow we
once thought. At the very least, we want to earn back the
acquisition cost from our investment.
Behavioral Biases
All of these considerations – expenses already incurred (in
this case, the purchase price), not wanting to regret our
decision, or engaging in mental accounting – lead to irrational
decisions and can cost a lot of money. Investors may reach the
point where they cannot take it anymore just before the price
bottoms out. Their nerves shot, they decide to sell everything.
“Enough is enough! I’m never buying or even thinking about
equities again!” they say. Then the prices drop a bit more and
investors feel their decision was validated. “Good thing I sold it
all,” they think.
Looking back at their investment decision, we can see that the
buyer underestimated market developments and overestimated
his psychological risk appetite. This is a very common mistake.
If the markets are up, investors become too confident – known
as the overconfidence bias. This means they overestimate
their own abilities and think they know more than they
actually do. They are certain they possess above-average
skills. Notably, most experts also overestimate themselves –
frequently to a greater degree than laypersons. Many investors
are too confident. This is often seen when the markets
are on the rise. The sweet smell of success quickly clouds
our judgment. Some individuals overestimate themselves
more often than others. The opposite (underestimation)
does not exist. There are merely varying degrees of
overestimating oneself.
Back to our roller coaster. Stocks are getting cheaper and
cheaper, the return on dividends is much higher than the
interest on bonds, and eventually the market is oversold.
Anyone still standing is very lucky indeed. However, the
average private investor is just as surprised by the rebound as
by the crash.
With the shock of the sales rally fresh in his mind, he is
initially very cautious and does not trust the rebound. Despite
small price gains, the investor is convinced that “it’s still going
to crash.” The share price does in fact drop again and the
investor feels happy and vindicated. “It’s just as I said…” he
tells himself. He becomes more confident again. Then the
16 CREDIT SUISSE Private Banking North America
rapid switch from a downward spiral to a sharp increase nearly
takes his breath away. “Now what’s going on?” he wonders.
The investor needs a little time to get back on board with the
fast-paced market. Usually he gets himself together pretty
quickly and that old familiar self-confidence is back. He thinks
he saw the rebound coming and invests again once the price
is high (or higher than the record low).
Hindsight is 20/20. The statement “I knew the whole time
this would happen” shows that we have an explanation for
everything after the fact. This hindsight bias keeps us from
learning from our mistakes. Even if prices rise, we keep
buying. “What the heck, I’ll buy it again because it’s cheaper
than last time,” we say. This statement is also interesting
because we have the last acquisition cost in our head as
the anchor, and not the last selling price. In other words, the
typical private investor buys high and sells low – wasting a lot
of money in the long term.
Human behavior adapted to our natural environment over
millions of years of evolution. However, the way we behave
around the financial markets is anything but natural. We
cannot use our adaptations to the natural environment in a
profitable manner. We find ourselves in a complex system that
we do not fully understand. If we apply human behavior in
natural settings to the financial market, we usually buy when
it is too late and do not sell early enough. By nature, people
are adaptive learners, meaning that we keep doing what has
worked well for us and we avoid repeating those actions that
have not led to positive results. This is a bad idea on the stock
market, as it causes pro-cyclical behavior. Investors tend to
buy more of a share once the price has gone up, when maybe
it is so high that they should consider selling instead.
We must remember that we cannot make money on a stock
unless someone is willing to pay more for it than we did. So it
is better to swim upstream through the financial market than
follow the herd of investors. One consequence of the roller
coaster ride and of irrational decisions is that private investors
only rarely beat the returns on a highly diversified index, such
as on the MSCI World. On average, investor performance is
4.3% worse than the index, according to a 2011 study US
financial analyst Dalbar conducted. This is true not only for
private investors but also for fund managers – the pros. Private
investors typically do not realize they are investing more poorly
than the market is. They succumb to various psychological
pitfalls but do not realize it because they are not measuring
their investment result in a systematic manner.
Overview – Denition of the biases mentioned
in this paper
Confirmation bias - The confirmation bias refers to
the phenomenon of seeking selective information to
support one’s own opinions or to interpret the facts
in a way that suits our own world view. Investors seek
confirmation for their assumptions. They avoid critical
opinions and reports, reading only those articles that
put their point of view in a positive light.
Availability/Attention bias - The attention bias states
that products, companies, and issuers that are more
frequently highlighted in the media will be remembered
more quickly by investors when they look for a suitable
investment. Bad or scarcely accessible information is
(unconsciously) not considered.
Home bias - Statistics show that most investors tend
to buy stocks from companies in their home country.
These stocks seem more trustworthy, as investors
grew up with these company names. They are also
mentioned more frequently in the local media.
Favorite long-short bias - People who fall into this
psychological trap always bet on the long shot because
it promises very high returns. Unfortunately, they forget
that the likelihood of the long shot winning cancels
the profit.
Anchoring - When making decisions, investors do
not rely on fundamental factors. Rather, they tend to
base their decision on the price at which the stock was
purchased. This purchase price acts as the anchor that
causes irrational decisions. Unlike the acquisition cost,
the new price seems cheap to the investor. Anchoring
influences decisions when investors do not realize
how the information is presented. When making
decisions, people are influenced by random data,
even if they know the data has no informational value or
is outrageously high or low.
Behavioral Biases
Overview – Denition of the biases mentioned in this paper
Myopic loss aversion - Most investors fear losses
more than they enjoy profits. If they check their stock
performance too often, they will see they have lost
money and sell everything off. A long-term view would
be better. They should check their stock performance
less often. The more they can keep their curiosity at
bay, the more likely they are to turn a profit with their
investments, provided that their portfolio is broadly
Mental accounting - Many private investors make
distinctions in their head that do not exist financially.
Often, losses incurred are viewed separately from paper
losses. This means that people are too quick to sell
stocks when they earn a profit and too slow to sell when
they sustain a loss. So mental accounting makes us
think that a dollar is not worth a dollar – a dangerous
Disposition effect - With the disposition effect, gains
are realized too early and losses too late. Turning a paper
profit into real profits makes us happy, while we tend to
shy away from turning a paper loss into a real loss.
One possible explanation for this is mental accounting
(see above).
Overconfidence - In most cases, we overestimate
our own abilities and think we are above average. Most
experts overestimate themselves – frequently to a
greater degree than laypersons do. Overconfidence is
often seen when the markets are on the rise.
Hindsight bias - Hindsight is 20/20. The statement “I
knew the whole time this would happen” shows that we
have an explanation for everything after the fact. This
hindsight bias keeps us from learning from our mistakes.
Get-even-itis - Once we have lost money, we take a
greater risk to make up for it. Get-even-itis can cause
us to place everything in one basket and potentially lose
even more money.
Representativeness bias - After even a brief period of
positive returns on the financial markets, we may think
the world has changed for the better. People tend to
think in terms of schemes and stereotypes experienced
in the past. They arrive at a result too quickly, based on
imprecise information.
Gambler’s fallacy - Here, the effective probabilities are
greatly underestimated or overestimated. For example,
based on the (false) assumption that prices are about to
drop, we sell too soon and vice versa (assuming that the
prices will recover soon, even though they are not yet
doing so).
Framing bias - Decisions are based largely on how
facts are depicted in statistical terms. For instance,
we do not think that “Four out of ten are winners”
and “Six out of ten are losers” mean the same thing.
The statements are identical, but most people do not
realize it.
Regret avoidance - If we invest in a blue chip stock
and it does not perform as hoped, we call this bad luck.
However, if we invest in a niche product that fails to
perform well, we tend to regret this more than we do
the failure of the blue chip stock. This is because many
other people have made the same mistake and thus our
decision to buy it does not seem so wrong.
18 CREDIT SUISSE Private Banking North America
One branch of behavioral finance that has evolved lies in the field of cultural research. Such
research shows how behavior patterns differ from culture to culture. Cultural finance provides an
essential foundation for globally active banks, and for good reason.
Despite advancing globalization, we can still identify some significant cultural differences around
the world. Around 500 languages are spoken worldwide, eating habits vary from region to region,
and there are some differences in our social conventions that we should know before crossing
the globe. However, traditional finance barely acknowledges international cultural diversity. This is
due to the premise that money is the great equalizer.
Nowadays, investors can trade nearly any security they want
just by pressing a few computer keys. Traditional finance
dictates that in the end, we all want the same thing: to achieve
high returns without assuming too much risk.
For some twenty years, behavioral finance researchers have
been trying to determine whether finance is indeed subject to
cultural differences. Even if we assume that investors around
the globe are focused on the return/risk trade-off, researchers
believe that culture can influence investors differently in
terms of investment type, investment time horizons, and risk
aversion. Ultimately, behavioral finance shows that while there
is only one way to act rationally, there are many ways to act
irrationally. Thus, it would not be far-fetched to say that our
culture helps determine which psychological pitfalls we are
more likely to succumb to. In this section, we will explore the
fascinating cultural differences in investment behavior and how
they can influence returns on the equity markets.
What is culture?
In the broadest sense, culture is everything that people
create. Examining the world’s artistic treasures is an excellent
way to identify the cultural differences that existed, and may
continue to exist, in various regions of the globe. The question
is how to measure culture and make a numeric correlation to
something as mundane as investment behavior and market
returns. Because investment behavior is also part of our social
behavior, we can take a cue from the cultural dimensions
identified by Dutch sociologist Geert Hofstede.
Cultural Differences In Investor Behavior
4 Hofstede’s web page,, shows an interactive map of
cultural differences.
Figure 10: Professor Dr. Geert Hofstede found that our social behavior can best be described using
the following ve dimensions. The diagram shows which countries have the most extreme forms
of the ve dimensions Professor Hofstede identied.4
Power Distance Index Imbalance between
power and wealth
Austria Malaysia
Individualism Reward for individual
or collective performance
Columbia USA
Masculinity Gender differences
in society
Norway Japan
Uncertainty Avoidance Index Intolerance for uncertainty Denmark Greece
Long-Term Orientation Respect for traditions Czech Republic China
20 CREDIT SUISSE Private Banking North America
How culture shapes investment behavior
In 2010, in the world’s largest study of cultural differences
in investment behavior to date, Professor Dr. Mei Wang,5
Professor Dr. Marc Oliver Rieger,6 and Professor Dr. Thorsten
Hens looked at the time preferences, risk behavior, and
behavioral biases of nearly 7,000 investors in 50 countries.
If we group the results by cultural region, we find some
astonishing differences. First, investors in Nordic and
German-speaking countries are the most patient, while
African investors are the least patient. Second, investors in
Anglo-Saxon countries are the most tolerant of loss, while
investors in eastern Europe have the greatest loss aversion
(see Figure 11).
5 Chairholder at WHU – O tto Beisheim School of Management
6 University of Trier, Germany
7 Italy, Spain, Greece, and Portugal
Figure 11: Loss Aversion and Time Preference
High LowLoss Aversion High LowPatience
East Europe
Latin Europe
Nordic Germanic
East Asia
Middle East
Latin America
Latin Europe
Latin America
East Europe
Middle East
East Asia
Nordic Germanic
Cultural Differences In Investor Behavior
The following figures show the international differences per country.
(Source: Study by Professor Dr. Mei Wang,5 Professor Dr. Marc Oliver Rieger,6 and Professor Dr. Thorsten (2010))
Figure 12: International Differences in Investor Patience
New Zealand
United Kingdom
South Korea
Hong Kong
Czech Republic
Figure 13: International Differences in Investor Loss Aversion
United Kingdom
New Zealand
South Korea
Czech Republic
Hong Kong
22 CREDIT SUISSE Private Banking North America
As far as behavioral biases are
concerned, we see that in all cultural
regions there is a high inclination to
increase the risk after losing money
Figure 14: Get-even-itis: The inclination to risk more money to avoid a denite loss,
even if this may result in a greater loss.
Hong Kong
New Zealand
Czech Republic
South Korea
Cultural Differences In Investor Behavior
In most countries, there is a tendency
to take unlikely events too seriously
– whether they are largely positive
or largely negative. In the first case,
fantasies about what people could do
with an extremely positive outcome
are so tempting that people fail to
realize how unlikely they are to win.
In the second case, anxiety about an
event with a very negative outcome is
so worrisome that people fail to realize
how unlikely this is as well.
Figure 15: Inclination to Bet on Extremely Unlikely Events with a Very Positive Outcome
(Small numbers = high inclination)
Hong Kong
Czech Republic
New Zealand
South Korea
24 CREDIT SUISSE Private Banking North America
These findings indicate that there
are cultural differences in investor
behavior. Further research is needed
to determine whether, as globalization
continues, these differences will
decline just as our differences in
language, eating habits, and social
customs have declined.
Figure 16: Inclination to Avoid Extremely Unlikely Events with a Very Negative Outcome
(Small numbers = high inclination)
New Zealand
Hong Kong
South Korea
Czech Republic
Neuronance: A New Branch of Behavioral Finance
So far we have examined the behavioral biases that investors often fall prey to. Behavioral finance has not only drawn up a long list
of these pitfalls, but it also has developed reliable diagnostic methods and suitable remedies for avoiding them. In addition, behavioral
finance incorporates findings from neurofinance in the brain research field.
In recent years, researchers have applied this knowledge to economics, thanks to major
technological advances, and are applying it to financial sciences. Neurofinance allows us to
determine which pitfalls have a biological origin and are thus more difficult to avoid.
Evolution: the cause of bad financial
Everyone makes mistakes in life. Even if we know better, we
make these mistakes over and over. In the financial world
especially, we continually make decisions that economists
consider to be irrational. We play the lottery even though we
usually lose. We go to Las Vegas, play roulette, and when we
lose we say, “I knew I should have bet on red.” We buy that
beautiful coat we saw in the shop window, even if it is beyond
our budget. Our brain is not designed to make financial
decisions or navigate complex financial markets.
When the human brain began its complex development, simple
neural networks were created. From there, our brain continued
to develop over millions of years. Our ancestors spent most of
their time fighting for survival — foraging for food, reproducing,
and avoiding natural enemies. It was not until the last millennium
of this development that we began using our brain for
financial decisions as well. No wonder, then, that investors
(professionals and amateurs alike) systematically deviate from
rational decision-making behavior.
The human brain
To understand neurofinance and its reasoning, we must first
take a brief look at the neurosciences. The human brain consists
of different parts, shown in the following figure.
26 CREDIT SUISSE Private Banking North America
The oldest part of the brain, the inner core, is the stem (truncus
cerebri). The brain stem controls key bodily functions such
as circulation, respiration, and digestion. The limbic system is
responsible for our senses (in the thalamus) and such instincts as
survival and reproduction (in the hypothalamus), as well as positive
emotions (in the nucleus accumbens) and fears (in the amygdala).
Not surprisingly, this part of our brain plays a large part in
managing intuition. What is more, three-quarters of the
human brain comprises the cerebral cortex (telencephalon).
What distinguishes humans from other species is the
prefronta l cortex, it s role in short-term and long-term memory, as
well as learning, planning, and self-control. The telencephalon also
helps us reflect on feelings such as love, hate, and happiness.
It is important to note that the older parts of the human brain
have not changed much over the course of evolution. Instead,
new parts have developed, such as the telencephalon, which is
in charge of additional functions including planning and social
conduct. When we have to make decisions, our limbic system
and telencephalon are activated. Here, intuition and emotions
meet cognition.
These systems do not always act in unison. Emotions often get
the upper hand, as best seen by measuring psychological and
neuronal activity. To understand investment behavior, we need to
ask: How does our brain respond to gains and losses? How about
risks? What about instant versus long-term gains, losses, and
risks? Can our brain assess gains, losses, and risks correctly?
Our neurons send signals to reveal an emotionally charged
assessment of returns and risks. For instance, gains and
losses sometimes affect different parts of the brain. Some of
these parts, such as the striatum and the amygdala, clearly
come from the limbic system rather than our rational prefrontal
cortex. Thus, a clear separation of gains and losses, as the
Nobel Prize-winning prospect theory of Kahneman and Tversky
showed, is more natural than traditional finance intended. The
main hypothesis of the prospect theory is loss aversion, meaning
that the pain of financial loss is twice as acute as the happiness
we derive from financial gains. When we talk about a painful
financial loss, we are not exaggerating. Financial losses are
processed by parts of the brain responsible for the pain network.
One of these areas is the amygdala. Patients with damaged
amygdalas are not afraid of loss and often take higher financial
risks than they should.
Figure 17: The Functional Structure
of the Human Brain
Globus pallidus
Mammillary body
Spinal cord
Market Anomalies
Is individual error relevant to the market?
Behavioral finance shows that when it comes to risk and
uncertainty, investor behavior deviates greatly from the ideal
scenario of the rational investor. Typical investors fall victim to
an array of psychological pitfalls, as described in the previous
Are these behavioral biases also pertinent to market
developments? Is it possible that individual errors ultimately
balance each other out? If some investors are too optimistic
and others are too pessimistic, the market may find its
happy medium.
Is it true that investors who make errors lose money to rational
arbitrageurs, such as hedge funds, meaning they keep losing
relevance to the market? In spite of these plausible questions,
behavioral finance research on market activity has found
a wide range of market inefficiencies, known as market
anomalies. So it seems that individual investment errors move
in the same direction and occur more or less simultaneously.
Ultimately, it is unclear whether irrational investors lose money
to rational arbitrageurs. The reverse may be true. If the
stock market is too cheap from a fundamental standpoint so
that rational investors will buy, panic among irrational investors
may still lead to further price losses. The famous British
economist John Maynard Keynes8 summed up this problem
nearly a hundred years ago: “The markets can remain irrational
longer than you can stay solvent.” The great hope that rational
investors can quickly make an impact on the market can be
very dangerous.
Thus, good asset management should consider fundamental
factors alongside behavioral finance, as Credit Suisse has
been doing for years.
Empirical evidence and behavioral explanations
Whether financial markets are efficient is not a matter of faith.
It can be measured empirically.
The starting point for an efficiency market hypothesis is
that any profitable information has always been priced
into shares. Thus, share prices should be statistically
independent of one another, just like the repeated coin
toss. However, this statistical independence does not apply
to major share indexes such as the S&P 500. If the S&P 500
increases in a month, the probability that it will grow again
the next month is 63%; the average return of the next month
is then 0.11%. If the S&P declines in a month, the probability
that it will decline again the next month is 48%; the average
return of the next month is then 0.06% (Gerber, Hens, and
Vogt, 2010).
This monthly momentum is also reflected by the positive
correlation of the monthly returns from the S&P of 28%. This
means that 28% of the returns from the next month have
been defined by the previous month. In an efficient market,
this figure would be 0%. Due to adaptive investor behavior,
as described in the roller coaster section of this paper, even
in highly liquid equity markets, there are escalation processes
that ultimately collapse. If we look at the S&P not just from
one month to the next, but over its 140+ year history, we
8 Keynes, ideas built the basis for the Keynesian economics.
28 CREDIT SUISSE Private Banking North America
see that there are long phases of deviation from the efcient
market hypothesis (Figure 18). The largest deviations occur
in times of speculative bubbles and crashes, such as in the
roaring twenties and the subsequent global depression,
the dotcom bubble and the crash of 2000–2003, and the
subprime bubble and major financial crisis of 2007/2008.
The result of the escalation processes and subsequent
collapses is that equity returns do not have normal distribution.
Statistically speaking, there are too many months with very
poor returns, as shown in Figure 19.
It is also true that not all profitable factors are always priced
into share prices. Even very basic factors, such as the price/
dividend ratio, can predict developments only to some extent,
as seen in Figure 18. After a year with a high price/dividend
ratio, the return of the S&P (in excess of the risk-free rate)
tends to be lower than after years of a low price/dividend ratio.
Figure 18: Ination-Adjusted Performance
of the S&P 500 Compared with the Analysis
under the Efcient Market Hypothesis
(Source: Gerber, Hens, Vogt (2010))
Figure 19: Abnormal Distribution of Returns on the S&P 500
Annual Returns (in %)
S&P 500 Normal DistributionPsychologically Weighted S&P 500
-48 -38 -28 -18 -8 2 12 22 32 42 52 62
Market Anomalies
Other market anomalies on other asset classes exist, such as
bonds. When we compare short-term and long-term interest
rates, the efficient market hypothesis says that if long-term
rates are higher today than short-term ones, short-term rates
will soon rise. If we compare the expected short-term rates
with the rates that later occur, we see that rise during a phase
of interest growth in Figure 20. If we compare the expected
short-term rates with the rates that later occur, we see that
during a phase of interest growth, the expected rates from the
comparison underestimate the actual rates that occur. During
a phase of interest rate decline, the reverse is true.
Behavioral finance uses the anchoring bias to explain
this phenomenon. Future interest rates that are implicitly
expected based on current rates are too close to the current
rates, which are used as the starting point (the anchor) for
expectations. Even on the options markets, there are surprising
deviations from the efficient market hypothesis. For example,
Figure 20: Returns of the S&P 500 (in Excess of the Risk-free Rate) (Source: Gerber, Hens, Vogt (2010))
and the Price-Dividend Ratio at the End of the Previous Year
Excess Returns
Price-Dividend Ratio ZeroPsychological Distribution of Returns
20 40 60 80
30 CREDIT SUISSE Private Banking North America
Figure 21: The Forward Rate Bias (Source: Burkhardt (2008))
out-of-money options9 are more expensive than they should
be from a rational standpoint. Options such as lottery
tickets have a small probability of delivering high returns. As
psychologists Kahneman and Tversky found in numerous
studies, investors place too much value on low probabilities,
which means they pay too much for out-of-money options
like lottery tickets. If the probability under an alternative rises
by 1%, the psychological appeal of the resulting situation
depends on how high the probability was to begin with.
If the original option had a 0% probability, the same 1%
increase has a much greater psychological impact than if
the original probability had been 49%. In the latter case, the
increase was from fairly possible to slightly more possible;
in the former case, the increase was from impossible to
possible. For an example of this, see Figure 15 and 16 in
the section on Cultural Differences.
9 Options that would have a zero value if the current date was the maturity date.
USA 1 Yr Forward vs 1 Yr Spot Interest Rates
Forward Rate in 1 Yr for 1 Yr Realized Spots 1 Yr
1990 01
1991 01
1992 01
1993 01
1994 01
1995 01
1996 01
1997 01
1998 01
1999 01
2000 01
2001 01
2002 01
2003 01
2004 01
2005 01
2006 01
2007 01
2008 01
2009 01
Market Anomalies
If we apply this psychological weighting of probabilities to the
returns on the S&P 500, we obtain the brown bars shown in
Figure 19. Thus, not only do equities have too many months
of excess loss from a statistical standpoint, but also investors
exaggerate the probability of these months occurring.
Rather than continue down the list of market anomalies, it is
worth considering what would happen if everyone invested
using the prospect theory portfolio model, identified their
biases with a diagnostic test, and then abandoned these
biases. The markets would ultimately be efficient under these
ideal conditions. The Markowitz model would suffice as well:
because the prospect theory portfolio model includes the
Markowitz model, it also works in efficient markets.
After all, you still can drive a car cross-country with four-wheel
drive in the summer.
32 CREDIT SUISSE Private Banking North America
The goal of any investment advisory service is to explore the
best personal strategy for the client and to review it on a
regular basis. An investment strategy cannot be optimal
unless it integrates the client’s risk ability, risk tolerance,
and risk awareness.
Risk ability refers to the client’s financial situation. What
are the client’s assets and income, spending patterns, and
earning sources? The client’s risk ability limits the optimal
portfolio if they cannot financially bear losses beyond a certain
amount. This circumstance must be accounted for. Risk
tolerance indicates how much risk an investor is emotionally
willing to bear. The subjective assessment of the objective
(measurable) risk of an investment is determined by
risk awareness.
The client’s risk awareness is often distorted and can change
quickly. Due to the biases just mentioned, among other
factors, they are unable to identify the real risk and evaluate
it properly. One example is hedge funds, or collateralized
debt obligations (CDOs), which became notorious during the
financial crisis. Many investors considered these investments
evil, due in part to media coverage.
Despite its importance, subjective risk awareness is generally
not given the attention it deserves, even in the year 2015.
The goal of investment advisory services should be to review
the investor’s risk awareness and provide sufficient risk
disclosure. Because we can assume that the client’s risk
awareness is distorted by many biases and influenced by the
media, it should not be a part of optimal portfolios. Reputable
Your Needs
Your Strategy
Your Plan
Cultivating Our
your unique
needs and
wealth profile
to create a
holistic approach
to planning,
growing, and
your wealth.
Utilizing our
firm’s global
views to
strategies and
for you.
the views of
our global firm
and the diverse
resources of our
organization into
portfolios that
are customized
to meet
your goals.
A differentiated
suite of
and solutions
to execute
your customized
Our partnership
with you is
and maintained
through ongoing
reviews and
(Source: Credit Suisse (2015))
Wealth Management Approach
banks have a research department that uses the best methods
to adequately assess the current risks of asset classes. The
advisor must provide the client with this market view along with
an explanation.
A structured advisory process can help investors explore their
actual risk ability and risk appetite.
We also advise conducting a diagnostic test for behavioral
biases and identifying the client’s existing financial knowledge.
The test will identify four categories of investors, based on
their investment approach and financial knowledge. Does the
client want to make his own investment decisions based on
the investment advice received, or is a discretionary mandate
preferable? The investor type determined by the diagnostic
test can help answer this question.
10 Brinson, Hood, and Beebower (1986), and Ibbotson and Kaplan (2000).
Figure 22: Determining Investor Type
Intuitive Exploring
Realistic Strategic
Financial Knowledge
Intuitive investors - Intuitive investors make emotional
decisions. Without the right investment strategy, they may be
influenced too heavily by current market developments and
lose sight of their investment goals.
Using a discretionary mandate can help intuitive investors to
maintain a defined investment strategy. Research studies show
that the investment strategy is responsible for about 80%
of investment gains.10 Otherwise, clients may make hasty
purchases in a rush of euphoria when the markets are up (too
expensive) and sell off stock in a panic when the markets are
down, which likely will erode at their assets over time.
Exploring investors - Exploring investors are very familiar
with the financial market but make emotional decisions.
They have a good understanding of the opportunities and risks
on the market. Although they are sometimes dazzled by new,
innovative financial products, they always bear the risks in
mind. Despite their vast financial knowledge, these investors
sometimes abandon their predefined investment strategy for
emotional reasons. This is why their investments must be
reviewed periodically.
Realistic investors - These investors are not swayed
by emotions. However, they lack the financial knowledge
to assess risks and opportunities properly. Professional
investment advice is recommended for realistic investors. Such
advice can help them make investment decisions and improve
their financial knowledge.
Strategic investors - Strategic investors have a good
understanding of the financial markets, so they can assess the
risks and opportunities they are facing. They are not swayed
by emotions and can make objective decisions. Their strategic
approach does not allow them to lose sight of their investment
goals. They are qualified to implement their investment
strategy in conjunction with a non-discretionary mandate.
Next, based on the investors’ background, a holistic
investment strategy is developed, taking into account the
investor’s assets, wealth building, obligations, and asset
depletion. In particular, this proposal focuses on personal
liquidity management – in other words, coordinating income
with financial obligations.
34 CREDIT SUISSE Private Banking North America
This plan helps investors ensure that they can meet all of their
expenses when due and that they do not run into any liquidity
First, however, the client’s investment goals must be
determined. The focus is on the client’s wishes and plans,
which should be accounted for in the investment plan as
expenses (income). Investors should rank these goals in
order of importance. Goals can include obligations (paying
off a mortgage, children’s education, and so on) and plans
and wishes for themselves and their family (vacation home,
international travel, and so on). The defined goals should be
used to determine the minimum investment horizon.
Once the obligations (including wishes/needs) have been
prioritized over time, we can determine which part of the
investments are freely available – in other words, not subject to
an obligation. In this step, it is important to consider tax, legal,
and personal restrictions.
Traditional finance uses the concept of value at risk (VaR)
here. Value at risk is the amount of loss that will not be
exceeded for a certain period of time (save for a few
exceptions). Aside from the argument that VaR is not
necessarily the right measurement tool, this viewpoint is
somewhat unsettling in psychological terms because there
are cases in which investors can lose so much money that
they are unable to meet their obligations. This can mean that
investors get nervous when prices are down and abandon
their investment strategy. A better method is to cover the fixed
obligations with secure investments. So instead of a value-at-
risk view, an asset split is preferable.
From a behavioral finance viewpoint, asset splits are a
very good idea. This is because clients still know that their
obligations are not at risk (even when they are losing money
from their free assets) and they can better maintain their
investment strategy. This means clients will not have to
make emergency selloffs and can act if attractive investment
opportunities arise during turbulent times.
One of the most important steps is analyzing the client profile
and risk analysis. The advisor and the investor try to determine
the investor’s actual psychological risk profile together.
Specifically, they need to know which fluctuations the client
can bear without losing sleep.
Of course, the client must be able to bear these fluctuations
not only emotionally but also financially. The all-important
decision is then how to define the investor’s risk appetite.
Under the traditional view, risk lies only in the fact that for
some investments (such as equities), it is difficult to determine
with certainty how high the returns will be at the end of the
investment horizon. In empirical terms, the average returns
and standard deviation in returns will rise along the investment
class chain (money market, bonds, hedge funds, equities).
From a traditional finance standpoint, determining risk appetite
consists only of choosing from this trade-off. Some banks also
use risk profilers that inquire directly about this trade-off by
offering the client a few combinations of average returns and
standard deviations.
Investors may be overwhelmed by this process. If an investor
does not understand the question properly, their answer
usually will result in an asset allocation that has draw downs
(accumulated loss during a specific period) for them. They
cannot maintain the strategy during times of crisis. Behavioral
finance takes a different view of risk tolerance. Although
uncertainty about the amount of the yield upon maturity is
a key aspect of risk tolerance, loss tolerance is far more
important. Because most asset yields do not have the same
amount of opportunities for losses and gains, this distinction
is very important for asset allocation. Equities, for instance,
have many more losses than they normally should, given their
standard deviations. Capital-protected products have a high
standard deviation in their yields, although their losses are
limited. Therefore, the inclusion of losses in risk tolerance
means that the asset allocation has fewer stocks – but capital-
protected investment products can play a key role.
Behavioral finance also integrates fluctuation (volatility) into
the portfolio. The response to asset volatility, called investment
temperament, is a key indicator of whether investors can
maintain their strategy.
Wealth Management Approach
This figure illustrates that volatility (standard deviation
of returns) is not easy to understand, especially for
nonprofessionals. It shows that Investment A is subject to a
higher (one-time) fluctuation in returns than Investment B.
For Investment A, the difference between the minimum and
the maximum return is higher than for Investment B. However,
B has a higher volatility than A because the volatility is defined
as the average standard deviation in the returns. However,
because A fluctuates enormously only once, it has a lower
influence on the average of the standard deviation. This is
because the weight of a one-time deviation is less than if it
were to fluctuate frequently, even if these fluctuations are
smaller. This lies in the definition of average.
An investor who chooses Investment A due to the lower
volatility and cannot withstand the drop due to an excessively
low psychological or financial risk tolerance will suffer a greater
loss than if he had invested in the higher risk Investment B
(measured with the risk criteria of volatility). This example
illustrates that volatility as a sole risk measurement tool must
be treated carefully. It is also important to know how willing
the client is to take risks. Once we know the client’s financial
situation and risk analysis, the foundation is set for creating
the investment strategy.
The investment strategy can be implemented in an active or
passive manner. This is a decision that clients must make and
with which the advisor can assist. The investment strategy is
based on the client’s individual investment goals and personal
risk profile.
After the plan has been implemented and the partnership has
been cultivated, the process repeats itself continually.
By implementing the strategy, the research team protects
clients from the availability/attention bias. The research team
uses fundamental data and does not blindly apply the past to
the future. This is why every disclaimer includes the caveat
Figure 23: Various Risk Aspects
36 CREDIT SUISSE Private Banking North America
“past performance does not guarantee future earnings” or
something to that effect. Today’s talents are not necessarily
tomorrow’s stars.
Typical investors evaluate information according to how quickly
it can be recalled. Advisors also present sufficient timelines for
returns and not just those from the last year.
If the client wishes to make the investment
decisions (execution only):
People should not stop at the first best result that comes
to mind. The attention bias states that investors will more
quickly remember products, companies, and issuers more
frequently highlighted by the media when looking for a suitable
investment instrument. Instead, investors should look for
arguments that refute their opinions. They must weigh the
pros and cons.
An objective analysis protects an investment idea from
the confirmation bias. This refers to the phenomenon of
supporting our own opinions with selective information. We
want confirmations of our views. We avoid critical opinions and
reports, reading only those articles that put the product in a
positive light.
The correct assessment of individual risk ability is particularly
important during this process, but it is very difficult to
achieve. Determining the client’s risk preference is part
of the risk profiler’s job. The goal is to give an investment
recommendation that reflects the client’s risk preferences as
accurately as possible.
That is why a good risk profiler is needed.
Finding the right risk profile for the client is probably the most
important piece of investment advice. The risk profile defines
the strategic asset allocation (SAA). Many studies show that
investment success depends largely on SAA. The studies by
Brinson et al. show that SAA accounts for 80% of investment
gains. However, to reach this goal, the investor must be able
to maintain the strategy, as Dalbar’s study (2011) found.
Thus, SAA is the main component of investment success.
Just a few years ago, most banks defined SAA solely on the
qualitative opinion of investment advisors. But today nearly
all banks use a formal questionnaire, known as a risk profiler
or risk profile. In most industrialized nations, the regulatory
agencies mandate this profile by law.
The same is true of risk profilers as it is for everything else:
Some are good, and some are bad. Unfortunately for banks
and clients, however, it is not easy to determine how the good
differ from the bad. Controlled lab experiments are useful
for designing risk profilers. Lab experiments conducted on
decision making are one of the most important research
methods in behavioral finance.
These experiments originated with Vernon Smith, an American
professor who won the Nobel Prize in 2002 for economic
sciences. The key advantage of lab experiments is that the lab
manager retains control over the exogenous influences and
thus can make direct comparisons – for instance, between the
gains of investors with or without risk profilers before investing.
This comparison can be applied to all market phases (rising,
falling, sideways, and so on), as the lab manager can set
these in the experiments. This is a huge advantage over the
real world, where it is not possible to experiment with the client
advisory process. For about five years, a group of researchers
led by Thorsten Hens at the Institute for Banking and Finance,
University of Zürich, has been developing risk profiles based
on lab experiments.
The goal of a risk profiler is to determine asset allocation
by asset class, which the investor tailors optimally to the
return/risk trade-off so that he can tolerate fluctuations in
the investment strategy financially and emotionally over the
long term. The bar is set very high, as it requires a balance
between the investor’s rational and irrational aspects. If
investors’ behavioral biases have too much influence over their
asset allocation, they will lose money. At the same time, the
clients’ psychology must be considered, so that they are not
overwhelmed by the ups and downs of the investment strategy
and do not abandon it at the wrong time. To diffuse the conflict
between irrational behavior and mental overload, it is not
Wealth Management Approach
advisable to use the risk profiler in an isolated manner. Instead,
the risk profiler should be used in context (for instance, with
a diagnostic module and a training module before and good
reporting after). A diagnostic module can reveal investors’
behavioral biases, and a training module can teach the pros
and cons of asset classes and investment strategies.
What questions should a risk profiler include?
The questions in a risk profiler must impart a logical thought
pattern so that investors can see why they must answer
them. One logical pattern is to start with the investors’ goals,
followed by the tools with which they want to reach these
goals, followed by a definition of the potential restrictions to
keep in mind when using the tools, and finally to analyze the
In order to understand how the solution is defined by the
goals, tools, and restrictions, it is important to return to these
aspects time and again so that a dialogue based on the risk
profiler can be held.
Portfolio design
Once the investment goals, obligations, investment tools, and
risk tolerance have been determined, the question is how to
link this information to asset allocation. Unfortunately, this
step is not well covered in practice. Scoring methods are very
popular. They assign a score to each answer in the risk profiler
and add these numbers based on specific rules. The problem
with this method is that all the hard-won, carefully extracted
pieces of information are lost, because they are presented only
on a scale (for example, between 0 and 10).
However, this is a simple procedure, because the points in the
scale can simply be allocated to certain sample portfolios in
the risk/trade-off.
A more detailed method is to evaluate the answers using a
decision model. Based on the investor’s answers, parameters
of a target function and their restrictions are defined. The
decision model is then optimized in line with a data set of
returns. The central decision-making model of behavioral
finance is the prospect theory of Kahneman and Tversky
mentioned earlier (page 8).
Documentation and reporting
Individuals usually want to ponder the suggested asset
allocation and may want to discuss it with others. For this
reason, they should be given thorough documentation about
the entire decision-making process. The documentation also
can help manage certain biases, such as the hindsight bias
and regret avoidance. Thus, each decision and the basis for it
should be documented. This enables investors to learn from
their mistakes. In making their own investment decisions, they
should keep a trading diary, listing the reasons and goals for
buying each stock. Before selling, the client should review the
purchase entry and determine whether the facts consulted
when making the original purchase are true.
Risk monitor
The optimal investment strategy for the client must be
reviewed continually and revised if needed. Over time, the
client’s risk ability can change significantly for two reasons.
Gains and losses on the financial market change their assets,
and personal events such as marriage, birth, divorce, and
retirement change their obligations. A risk monitor provides
an ongoing review of the suitability of the investment strategy
chosen. It shows which of the client’s obligations and wishes
can be met with current assets and which can likely be met in
the future. Thus, the risk monitor provides valuable information
to review the investment strategy. It should be based on
long-term expected returns and anticipate a certain amount
of tolerance to market fluctuations so that it does not lead to
knee-jerk reactions in the portfolio.
38 CREDIT SUISSE Private Banking North America
Conrmation bias
attention bias
Home bias
long-short bias
Mental accounting
Look for counterarguments.
Be honest with yourself.
Also, an objective analysis of
an investment idea will protect
you from a conrmation bias.
Ask yourself why you have
just thought of this particular
instrument. Do not stop at
the rst best idea. Do not be
taken in by glossy brochures.
Ask a neutral party for advice.
Structure your portfolio top-
down and start by dening
the strategic asset allocation.
It is best to let your client
advisor assist.
Be satised with smaller gains,
which offer higher chances.
Ask yourself how the
investment will pay off in the
future. Whether you make
or lose money with an
investment is not relevant
to future per formance.
Try to avoid this distinction
and be aware of when you fall
prey to this pitfall.
Helps the client get
an objective viewpoint.
Should be able to access
a database with research
reviews. The database should
not contain any biases and
should be objective in content.
A structured investment
process helps. Diversication
principles are standard.
Your relationship manager
can explain the risks
and opportunities to you
and prevent you from taking
excessive risks.
Decisions to buy or sell are
made based on fundamentals.
IT-based systems help the
client advisors act without
emotions getting in the way.
Your client advisor will
not even mention these
distinctions so that you can
avoid this pitfall.
Fundamentals and long time
periods help the client with
an objective analysis.
Review companies regardless
of the level of media coverage.
Evaluates global stocks
and markets based
on fundamentals.
Research analyzes each
opportunity and risk
in a neutral manner.
Research contributes
to rational decision making.
Overview – De-Biasing
Countermeasure Client Advisor Research
Wealth Management Approach
Disposition effect
Myopic loss aversion
House money effect
Overcondence bias
Hindsight bias
Stick to your predened
strategy. Keep a diary of your
investment ideas. Why are you
buying an investment, what do
you want to achieve, and under
what circumstances (based
on what facts) is the
investment to be re-sold?
Consult your diary before you
actually sell. Has the reason
for selling occurred? If not,
review your decision.
Stick to a long-term strategy;
do not let your emotions lead
you in nancial matters.
Realize that a dollar is a dollar,
no matter where it came from.
Look at the abilities of the
average person and realize
that everyone wants to be a
Realize that this will not
help you. Try to learn from
your mistakes. Look at your
investment diary from time to
time. You will then see what
the situation was when you
chose an investment.
With the help of a relationship
manager and a systematic
investment process, it is easier
to maintain the previously
dened strategy.
Your advisor will guide you
along the way. He will provide
you with information as
required for your portfolio or
the markets.
It is easier for an outsider
to realize this than it is for
us. Your client advisor will
inform you if your risk ability
has increased so much from
nancial returns that you can
risk more.
Your client advisor will make
it easier to realize your actual
abilities, as long as he is
Together you can accelerate
the learning process and nd
the cause sooner.
With the help of a client
advisor and a systematic
investment process, it is easier
to maintain the previously
dened strategy.
Research will review on a
regular basis whether your
strategy still meets the market
Research will review on a
regular basis whether your
strategy still meets the market
Research provides you with
peer group comparisons
that you can use to see how
much better or worse you are
compared with others.
Research will review on a
regular basis whether your
strategy still meets the market
Countermeasure Client Advisor Research
40 CREDIT SUISSE Private Banking North America
Gambler’s fallacy
Framing bias
Regret avoidance
Realize that losing money is
as much a part of investing as
making money. Maintain your
long-term strategy and do not
try to turn things around by
taking extreme steps.
Look at longer time periods.
Consider the actual probability
that the trend will reverse.
Look at everything in the
reverse. For example, if
there is a 60% chance of X
happening, there is a 40%
chance that it will not happen
(4 out of 10 cases).
Learn from these situations
and do not make excuses.
If you are suffering too greatly
from nancial loss and want
to make up for it as soon as
possible, your client advisor will
counsel you to be patient and
Your client advisor will be
glad to show you the long-
term performance of your
investments in the past.
Your client advisor will be
glad to show you the long-
term performance of your
investments in the past.
Ask your advisor for further
information. Consider the
source’s possible motivation
for providing you with
Your client advisor will help
you look at the situation in a
factual manner.
Research will review on a
regular basis whether your
strategy still meets the market
Statistical models tr y to track
trends and are not led by
Statistical models tr y to track
trend turnarounds and are not
led by emotions.
Research institutes can
give you additional public
background information.
Research will provide you
with the pros and cons of
investments with a neutral
Overview – De-Biasing
Countermeasure Client Advisor Research
Traditional finance, based on the hypothesis of efficient markets and the optimization of
statistical figures such as means and variances, suggests that investing has a lot to do with
mathematics. However, behavioral finance has put the spotlight back on people. People
make mistakes – even in investment decisions, which results in inefficiencies at the market
level. Based on behavioral finance, investment is 80% psychology.
In the meantime, behavioral finance has created methods that can help investors identify
typical mistakes while finding the right portfolio for them. The hope is that as many investors
as possible will make use of this school of thought and that the markets will become as
efficient as traditional finance assumes. However, the saying “There is no such thing as a
free lunch” will always apply.
Be aware of the risks before you make a decision,
and choose the right combination of risk and return.
The findings of behavioral finance can help you.
42 CREDIT SUISSE Private Banking North America
Bank Leu (2005)
“Chancen und Risiken auf den Finanzmärkten,
Irrationales Anlegerverhalten und eine Analyse von
Anlagestrategien seit 1950”
Bernartzi, S. and Thaler, R.H. (1995)
“Myopic Loss Aversion and the Equity Premium Puzzle”
Quarterly Journal of Economics, Vol. 110, pp. 73–92
Bollen, J., Mao, H., and Zeng, X. (2011)
“Twitter mood predicts the stock market”
Journal of Computational Science Vol. 2, pp. 1–8
Brinson, G.P., Hood, L.R., and Beebower, G.L. (1986)
“Determinants of Portfolio Performance” FA Journal, 42(4)
Burkhardt, Dominic (2008)
“Der Forward Rate Biases in ökonomischen
Zinsstrukturmodellen” Thesis, Institut für Schweizerisches
Bankenwesen, University of Zürich
Dalbar (2011): Quantitative Analysis of Investor Behaviour
“Helping Investors Change Behaviour to Capture Alpha”
Dalbar Inc. Boston
De Giorgi, E., Hens, T., and Mayer, J. (2011)
“A Note on Reward-Risk Portfolio Selection and Two-Fund
Separation” Finance Research Letters, Vol. 8(2), pp. 52–58
De Giorgi, E., Hens, T., and Levy, H. (2012)
“Two Paradigms and Nobel Prizes in Economics: A
Contradiction or Coexistence” European Financial
Management, Vol. 18(2), pp.163–182
Gerber, A., Hens, T., and Vogt, B. (2010)
“Rational investor sentiment in a repeated stochastic game
with imperfection monitoring” Journal of Economic Behavior
and Organization, Vol. 76(3), December 2010, pp. 669–704
Hens, T. and Bachmann, K. (2009)
“Behavioural finance for private banking” Wiley Finance
Ibbotson, R.G. and Kaplan, P.D. (2000)
“Does Asset Allocation explain 40, 90, or 100% of
Performance?” FA Journal 56(1)
Kahneman, D. and Tversky, A. (1979)
“Prospect Theory: An analysis of decision under risk”
Econometrica, Vol. 47, pp. 263–291
Markowitz, H. (1952)
“Portfolio Selection” Journal of Finance, Vol. 7, pp. 77–91
Rieger, M.O., Wang, M., and Hens, T. (2010)
“Prospect Theory around the World” NCCR-Finrisk working
paper number 731
Robert Shiller (O.j.)
Online Data Robert Shiller
Please note that this paper does not claim to be original research. To the best of our knowledge, we have cited all original work on which it is based.
About the Contributors
Credit Suisse
Credit Suisse AG is one of the world’s leading financial
services providers and is part of the Credit Suisse group
of companies (referred to here as ‘Credit Suisse’). As an
integrated bank, Credit Suisse is able to offer clients its
expertise in the areas of private banking, investment banking
and asset management from a single source. Credit Suisse
provides specialist advisory services, comprehensive solutions
and innovative products to companies, institutional clients
and high net worth private clients worldwide, and also to retail
clients in Switzerland. Credit Suisse is headquartered in
Zurich and operates in over 50 countries worldwide.
The group employs approximately 46,300 people. The
registered shares (CSGN) of Credit Suisse’s parent company,
Credit Suisse Group AG, are listed in Switzerland and, in
the form of American Depositary Shares (CS), in New York.
Further information about Credit Suisse can be found at
Thorsten Hens
Thorsten Hens is Swiss Finance Institute Professor
of Financial Economics at the University of Zürich and
Adjunct Professor of Finance at the Norwegian School
of Economics in Bergen. He studied at Bonn and Paris
and held professorships in Stanford, Bielefeld, and
Zurich. Since 2007, he has served as the Head of the
Department of Banking and Finance of the University of
Zürich. His research areas are behavioral and evolutionary
finance. Professor Hens is ranked among the top 10
finance professors in the German spoken area (Germany,
Switzerland, and Austria). In researching how investors
make their decisions, Professor Hens draws on work
in psychology and applies insights from biology in order
to understand the dynamics of financial markets. His
consulting experience includes application of behavioral
finance for private banking and evolutionary finance for
asset management. He is a founding partner of Behavioral
Finance Solutions, a spin off firm of the University of Zürich.
Professor Hens is a consultant of the investment committee
of the city of Zurich pension fund as well as the president of
the investment committee of the Vita pension foundation.
Anna Meier
Anna Sarah Meier has more than seven years of experience
in the financial industry. She is an expert in private banking
and has several collaborations with the Department of
Banking and Finance of the University of Zürich. Anna
Sarah Meier holds a Bachelor in Banking and Finance and a
Master in Business Administration with a major in innovation
management. She is a Certified International Investment
Analyst CIIA® and holds a certificate in informatics granted
by the Swiss Federation.
44 CREDIT SUISSE Private Banking North America
Figure 1: Orientation 2
Figure 2: History of portfolio theory 3
Figure 3: Sample coin toss 4
Figure 4: Utility function for various levels of risk aversion 5
Figure 5: Axiom of independence 6
Figure 6: Risk-return diagram 7
Figure 7: Utility function of the prospect theory 8
Figure 8: The Behavioral Efficient Frontier Based on the Prospect Theory 9
Figure 9: Investment process – roller coaster of emotions 10
Overview: Definition of the biases mentioned in this paper 16
Figure 10: Extreme forms of Hofstede’s cultural dimensions 19
Figure 11: Loss aversion and time preference 20
Figure 12: International differences in investor patience 21
Figure 13: International differences in investor loss aversion 21
Figure 14: Get-even-itis: the inclination to risk more money to avoid a definite loss,
even if this ultimately results in a greater loss 22
Figure 15: Inclination to bet on extremely unlikely events with a very positive outcome
(Small numbers = high inclination) 23
Figure 16: Inclination to bet on extremely unlikely events with a very negative outcome
(Small numbers = high inclination) 24
Figure 17: The functional structure of the human brain 26
Figure 18: Inflation-adjusted performance of the S&P 500 compared
with the analysis under the efficient market hypothesis
(source: Gerber, Hens, Vogt (2010)) 28
Figure 19: Abnormal distribution of returns on the S&P 500 28
Figure 20: Returns of the S&P 500 (in excess of the risk-free rate)
and the price-dividend ratio at the end of the previous year
(source: Gerber, Hens, Vogt (2010)) 29
Figure 21: The forward rate bias (Burkhardt (2008)) 30
Figure 22: Determining investor type 33
Figure 23: Various risk aspects 35
Overview: De-biasing 38
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The equity premium puzzle refers to the empirical fact that stocks have outperformed bonds over the last century by a surprisingly large margin. We offer a new explanation based on two behavioral concepts. First, investors are assumed to be “loss averse,” meaning that they are distinctly more sensitive to losses than to gains. Second, even long-term investors are assumed to evaluate their portfolios frequently. We dub this combination “myopic loss aversion.” Using simulations, we find that the size of the equity premium is consistent with the previously estimated parameters of prospect theory if investors evaluate their portfolios annually.
In order to delineate investment responsibility and measure performance contribution, pension plan sponsors and investment managers need a clear and relevant method of attributing returns to those activities that compose the investment management process—investment policy, market timing, and security selection. The authors provide a simple framework based on a passive, benchmark portfolio representing the plan's long-term asset classes, weighted by their long-term allocations. Returns on this "investment policy" portfolio are compared with the actual returns resulting from the combination of investment policy plus market timing (over- or underweighting within an asset class). Data from 91 large U.S. pension plans over the 1974-83 period indicate that investment policy dominates investment strategy (market timing and security selection), explaining on average 95.6 percent of the variation in total plan return. The actual mean average total return on the portfolio over the period was 9.01 percent, versus 10...
This paper presents a general reward-risk portfolio selection model and derives sufficient conditions for two-fund separation. In particular we show that many reward-risk models presented in the literature satisfy these conditions.
We consider a repeated stochastic coordination game with imperfect public monitoring. In the game any pattern of coordinated play is a perfect Bayesian Nash equilibrium. Moreover, standard equilibrium selection arguments either have no bite or they select an equilibrium that is not observed in actual plays of the game. We give experimental evidence for a unique equilibrium selection and explain this very robust finding by equilibrium selection based on behavioral arguments, in particular focal point analysis, probability matching and overconfidence. Our results have interesting applications in finance because the observed equilibrium exhibits momentum, reversal and excess volatility. Moreover, the results may help to explain why technical analysis is a commonly observed investment style.
Behavioral economics tells us that emotions can profoundly affect individual behavior and decision-making. Does this also apply to societies at large, i.e., can societies experience mood states that affect their collective decision making? By extension is the public mood correlated or even predictive of economic indicators? Here we investigate whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time. We analyze the text content of daily Twitter feeds by two mood tracking tools, namely OpinionFinder that measures positive vs. negative mood and Google-Profile of Mood States (GPOMS) that measures mood in terms of 6 dimensions (Calm, Alert, Sure, Vital, Kind, and Happy). We cross-validate the resulting mood time series by comparing their ability to detect the public's response to the presidential election and Thanksgiving day in 2008. A Granger causality analysis and a Self-Organizing Fuzzy Neural Network are then used to investigate the hypothesis that public mood states, as measured by the OpinionFinder and GPOMS mood time series, are predictive of changes in DJIA closing values. Our results indicate that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions but not others. We find an accuracy of 87.6% in predicting the daily up and down changes in the closing values of the DJIA and a reduction of the Mean Average Percentage Error by more than 6%.
Markowitz and Sharpe won the Nobel Prize in Economics more than a decade ago for the development of Mean-Variance analysis and the Capital Asset Pricing Model (CAPM). In the year 2002, Kahneman won the Nobel Prize in Economics for the development of Prospect Theory. Can these two apparently contradictory paradigms coexist? In deriving the CAPM, Sharpe, Lintner and Mossin assume expected utility (EU) maximization following the approach proposed by Markowitz, normal distributions and risk aversion. Kahneman & Tversky suggest Prospect Theory (PT) and Cumulative Prospect Theory (CPT) as an alternative paradigm to EU theory. They show that investors distort probabilities, make decisions based on change of wealth, exhibit loss aversion and maximize the expectation of an S-shaped value function which contains a risk-seeking segment. Employing change of wealth rather than total wealth contradicts EU theory. The subjective distortion of probabilities violates the CAPM assumptions of normality and homogeneous expectations, and the S-shaped value function violates the risk aversion assumption. We prove in this paper that although CPT (and PT) is in conflict to EUT, and violates some of the CAPM’s underlying assumptions, the security market line theorem (SMLT) of the CAPM is intact in the CPT framework.
Analysis of decision making under risk has been dominated by expected utility theory, which generally accounts for people's actions. Presents a critique of expected utility theory as a descriptive model of decision making under risk, and argues that common forms of utility theory are not adequate, and proposes an alternative theory of choice under risk called prospect theory. In expected utility theory, utilities of outcomes are weighted by their probabilities. Considers results of responses to various hypothetical decision situations under risk and shows results that violate the tenets of expected utility theory. People overweight outcomes considered certain, relative to outcomes that are merely probable, a situation called the "certainty effect." This effect contributes to risk aversion in choices involving sure gains, and to risk seeking in choices involving sure losses. In choices where gains are replaced by losses, the pattern is called the "reflection effect." People discard components shared by all prospects under consideration, a tendency called the "isolation effect." Also shows that in choice situations, preferences may be altered by different representations of probabilities. Develops an alternative theory of individual decision making under risk, called prospect theory, developed for simple prospects with monetary outcomes and stated probabilities, in which value is given to gains and losses (i.e., changes in wealth or welfare) rather than to final assets, and probabilities are replaced by decision weights. The theory has two phases. The editing phase organizes and reformulates the options to simplify later evaluation and choice. The edited prospects are evaluated and the highest value prospect chosen. Discusses and models this theory, and offers directions for extending prospect theory are offered. (TNM)
Chancen und Risiken auf den Finanzmärkten, Irrationales Anlegerverhalten und eine Analyse von Anlagestrategien seit Myopic Loss Aversion and the Equity Premium Puzzle
  • Credit Suisse
  • Private Banking North America
  • Bibliogr Aphy Bank Leu
  • S Bernartzi
  • R H Thaler
CREDIT SUISSE Private Banking North America BIBLIOGR APHY Bank Leu (2005) " Chancen und Risiken auf den Finanzmärkten, Irrationales Anlegerverhalten und eine Analyse von Anlagestrategien seit 1950 " Bernartzi, S. and Thaler, R.H. (1995) " Myopic Loss Aversion and the Equity Premium Puzzle " Quarterly Journal of Economics, Vol. 110, pp. 73–92
Rational investor sentiment in a repeated stochastic game with imperfection monitoring Behavioural finance for private banking Does Asset Allocation explain 40, 90, or 100% of Performance? Prospect Theory: An analysis of decision under risk
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  • T Hens
  • B Vogt
  • T Hens
  • K Bachmann
  • R G Finance Ibbotson
  • P D Kaplan
  • D Kahneman
  • A Tversky
Gerber, A., Hens, T., and Vogt, B. (2010) " Rational investor sentiment in a repeated stochastic game with imperfection monitoring " Journal of Economic Behavior and Organization, Vol. 76(3), December 2010, pp. 669–704 Hens, T. and Bachmann, K. (2009) " Behavioural finance for private banking " Wiley Finance Ibbotson, R.G. and Kaplan, P.D. (2000) " Does Asset Allocation explain 40, 90, or 100% of Performance? " FA Journal 56(1) Kahneman, D. and Tversky, A. (1979) " Prospect Theory: An analysis of decision under risk " Econometrica, Vol. 47, pp. 263–291