Behavioral Finance till T1.pdf

Why this study is important?
At the level of investor:
• Why do people tend to invest in local companies?
• Why do investor confuse a good company and a good stock?
• Why do people increase the amount of risk once they experience a
good or bad portfolio?
• Why do investors are reluctant to eliminate poorly performing
investments from their portfolios?
• Why do investors insufficiently diversify their asset holdings?
• Why do people follow the crowd?

Cont..
At the level of managers
• Can managers take info relating to individual psychology into
account in an effort to achieve improvements in personal
performance?
• As a human, can managers fall prey to their own behavioral errors?

Behavioral Finance….
• Study of preferences and decision making based on behavior from
the perspectives of Social, behavioral and biological sciences.
• Insights from psychology to understand how human behavior
influences the decisions of individuals and professionals.

Modern Finance
• Foundation is based on rational decision making
• Traditional finance models have a basis in economics and
Neoclassical economics is an dominant paradigm.
Assumptions about people in Neoclassical Economics
❑People have Rational Preferences across possible outcomes
❑People Maximize Utility (Happiness/Satisfaction from the
outcome) and Firms maximize profits (u()
❑People make independent decisions based on all relevant
information (Budget Constraint)

Utility Function (No Uncertainty)

Expected Utility Theory (Uncertainty)
Risk and Uncertainty

• Heads = Rs. 1500
• Tails = Rs. 500
• Fair Value= (0.5*1500)+(0.5*500)=Rs. 1000
• =0.5* Utility (1500)+ 0.5 * Utility (500)<Fair Value

• Budget Constraint
• Poha= Rs. 5
• Idali= rs. 10
• Budget=Rs. 100

Axioms of Rational Consumer Choice
Dominance or ‘More is Better’
• It states that, all else equal, more of a particular good is better than
less.
• In reality, we need some assumptions about the ability to store, or
sell, excess amounts of a good over a given time period. E.g. Poha
or Idali
• This axiom is commonly violated and it is related to the set of
biases known as “Disposition Effect”.

Invariance or ‘Consistency’
• A decision-maker should not be affected by the way alternatives are
presented.
• Preference between option A and option B should not change based on
the language used to describe the two.
• We are strongly influenced by how options are presented to us. E.g. meat
labeled as “75% lean” will sell better than the same product marked “25%
fat.”
• The violation of this fit within the set of biases generally referred to as
“Framing" issues or “Preference Reversals.”

Independence or ‘Cancellation’
• Choices should be independent of proportional reductions .
• Introducing a third option that has no bearing on the choice
between the first two should not affect your earlier choice.
• Give Example
• Violations of this axiom are often related to a bias known as the
“Certainty Effect.”

Examples of Irrational Behavior
Example 1: Two Decisions with Gains and Losses
Decision 1
• Alternative A : A sure gain of Rs. 240
• Alternative B : A 25% chance to gain Rs. 1,000, and a 75% chance to
gain nothing
Which do you prefer A or B?

Example 1: Two Decisions with Gains and Losses
Decision 2
• Alternative C : A sure loss of Rs. 750
• Alternative D : A 75% chance to lose Rs. 1,000, and a 25% chance to
gain nothing
Which do you prefer C or D?

C -750 250
Probability 75% 25%
D -760 240 -1000 0 1000
Probability 75% 25% 56% 38% 6%
A
Decision 2
B
A
-510
100%
Decision 1
B

Did you select A & D (bottom left)?
If so, you are like about 50% of people who play this game. You will:
• Lose Rs. 760 with probability 75%
• Win Rs. 240 with probability 25%
Now compare A & D (bottom left) with B & C (top right). They look very similar, except
that B & C is better in both cases!
For B & C, you have:
• The same 75% probability of losing money, but you lose a little less(only Rs.750, instead of Rs.760).
• The same 25% probability of making money, but you make a little more(Rs.250 instead of just Rs.240).

• Even though B & C dominates A & D, So why do around 50%
of respondents typically select the dominated A & D
outcome?
There are two principal reasons:
• We are not good at looking at outcomes over multiple games
(in this case, Decision 1 followed by Decision 2). We tend to
treat each one as a stand-alone decision
• We are inclined to be risk–seeking in certain predictable
scenarios.

Example 2: Choosing and Pricing
Gamble A
• 11/36 chance of winning Rs. 80000
• 25/36 chance of losing Rs. 7500
Gamble B
• 1/36 chance of losing Rs.5000
Which Gamble would you prefer to play A or B?

Example 2: Choosing and Pricing
Gamble A
• 25/36 chance of losing Rs. 7500
Gamble B
• 1/36 chance of losing Rs.5000
How much would you be willing to Pay to play Gamble A? How
about Gamble B?

On average, people would PREFER to play A…
but would PAY MORE to play B

Example 3: The Allais Paradox
• Imagine, you are offered a bag containing 100 balls of different
colors.
➢10 of the balls are white
➢89 of the balls are brown
➢1 of the balls is blue
• You will reach in and pull out a ball at random, and you will win
money depending on the ball’s color. Would you prefer to win
money on the basis of Option A, or on Option B?

Choice 1 White Brown Blue
Option A Rs. 1 Million Rs. 1 Million Rs. 1 Million
Option B Rs. 2.5 Million Rs. 1 Million Rs. 0

• Now imagine that you are offered the same bag, with the same
distribution of balls, but a slightly different set of Options. Which
option will you pick this time, Option C or Option D?
Choice 1 White Brown Blue
Option C Rs. 1 Million Rs. 0 Rs. 1 Million
Option D Rs. 2.5
Million
Rs. 0 Rs. 0

• In Choice 1, most people pick option A and in Choice 2, option D.
• Notice that the two pairs of Options are identical in all respects,
except for the outcomes with a Brown ball.
• In the first pair of Choices (A or B), a brown ball gives you Rs. 1
million. In the second pair (C or D), it is worth nothing.
• Why do identical outcomes subtracted from each of the two
Choices change our view of the desirability of one Option versus
the other (i.e., the switch from A in Choice 1 to D in Choice 2)?

Irrational Decision Making
Regret Theory
• A flu epidemic has hit your community. This flu can be fatal for
children under the age of three. The probability of a child getting
the flu is 1 in 10, and 1 in 100 children who get the flu will die from
it. This means that, statistically speaking, 10 out of each 10,000
children in your community will die.
• A vaccine for this type of flu has been developed and tested. The
vaccine eliminates any chance of getting the flu. The vaccine,
however, has potentially fatal side effects. Suppose that the vaccine
has a 0.05% fatality rate; that is, the vaccine itself is fatal in 5 out of
every 10,000 cases. You have a two-year old daughter. Will you
choose to vaccinate her?

• Many people respond NO to this question, despite the fact that the
child has a better survival rate with the vaccine than without it.
• Regret Theory posits that we make some decisions in response to
the extent of our anticipated regret if the decision subsequently goes
against us.
• Anticipated regret may be intensified by Omission Bias: we would
prefer not to be the active agent of our child becoming fatally ill.
• If she becomes ill from the vaccine, we blame ourselves because we
gave it to her
• If she simply catches the disease in the community, the disease can
be blamed on an “act of God”

Regret Theory
• For many years, for so long, in fact, that he practically forgot that he had them,
Mr. Dave has owned Rs.20,00,000 worth of shares in a certain company. One day
he remembers them, and considers whether it’s worth hanging on to them or
whether he should sell them. He notes that they have exactly maintained their
value over the years, so he decides to keep them –that is, to do nothing.
• A few months later, the company unexpectedly fails and his shares are no longer
worth anything. Mr. Dave realizes that he has lost Rs. 20,00,000.

Regret Theory
• His friend Mr. Joshi has also owned shares worth Rs.20,00,000 in a company; and he, too, had almost
forgotten that he possessed them. One day, he remembers the shares and considers whether to keep or sell
them. He notes that they have maintained their value throughout the years, so he decides to get rid of them
and invest in a company that promises a greater return. A few months later, the company whose shares he
had sold unexpectedly markets a new product and the value of that company’s shares doubles. Mr. Joshi
realizes that he has Rs. 20 lakhs less than he might have had, if he had not sold the shares that he had owned
for so many years.
• Both men started in the same position, and both came to the same conclusion (Rs. 20 lakhs less than they
might have had) but the two men feel different levels of regret. Who feels more regret?

Risk Aversion
• Please choose between Option A (Rs. 50 for certain) and Option B
(an equally weighted gamble of either Rs. 100 or Rs. 0). Which do
you prefer?
➢Option A: Rs. 50 for certain
➢Option B: Flip a coin (if Heads=Rs. 0, if Tails= Rs. 100)
Choose between A and B

Risk Aversion
• What happens if we increase the stake a little?
➢Option C: Rs. 500 for certain
➢Option D: Flip a coin (if Heads=Rs. 0, if Tails= Rs. 1000)
Choose between C and D

Risk Aversion
• Which did you choose between A & B? On average, the majority of
respondents select A, choosing the sure Rs. 50 in favor of the
gamble which has the same expected value but is risky.
• People who select B are being risk-”seeking” rather than risk
averse. If you selected B, it may be that you simply take pleasure in
the occasional gamble, provided the stakes are low enough that
you won’t feel inordinate regret if you end up with Rs. 0.

Risk Aversion
• Between C & D, the vast majority of people prefer C, the sure thing.
The enjoyment of a gamble is typically not strong enough to offset
the desire to walk away with a sure Rs. 500, and the anticipated
regret if you choose D but the coin flip goes against you.
• For reasonable sized gambles, most of us are indeed risk averse
where financial gains are concerned.

Risk-Seeking Behavior
• Now suppose that you have been kidnapped. Your (rather
unusual) kidnapper tells you that you can choose between the
following two options to obtain your freedom. (Assume that you
have sufficient financial resources to make good on your agreement
in either case):
➢Option A: Pay the kidnapper Rs. 500
➢Option B: Toss a fair coin (Pay Rs. 0 if Heads, Pay Rs. 1000 if Tails)

Risk-Seeking Behavior
• Did you pick A or B? If you selected B, your choice is consistent
with the vast majority of respondents to this and other similar
gambles where losses (rather than gains) are concerned.
• The simple fact is that, when we are looking at a decision in a LOSS
frame, we almost always become risk-seekers, rather than selecting
options consistent with risk aversion.
• This Risk Seeking over Losses is such a strong and consistent
human behavior pattern that it is extraordinary that classical
economics models simply ignore it, and assume that risk aversion
always holds.

Loss Aversion
• In this game, you toss a fair coin: if it lands Heads, you winRs.
2,000; but if it lands Tails, you loseRs.1,000. Would you like to play this
game? If you DO choose to play, you may play it only once.
➢If Heads, Win Rs. 2000
➢If Tails, Lose Rs. 1000
Do you want to play this game?

Loss Aversion
• Many people say they would prefer not to play this game at all.
This reflects Loss Aversion: our negative response to losses is greater
than our positive feelings about gains; even if the size of the gain is greater
than the size of the loss.
• The sense that Losses loom larger than Gains is another persistent
emotional response pattern that is completely ignored by classical
economics.

Prospect Theory
• Proposed by psychologists Daniel Kahnemann & Amos Tversky in
the 1970s
• Provides insights on human behavior that are not reflected in
expected utility theory

Prospect Theory: Risk Averse Over Gains

Prospect Theory: Risk Seeking Over Losses

Prospect Theory: Loss Aversion

Prospect Theory-Reference Points

Axioms Vs Biases
Axioms Bias
Dominance or More
is Better
Disposition Effect
Invariance or
Consistency
Framing
Independence or
cancellation
Certainty Effect

Prospect Theory and the Disposition Effect
• In Game 1, you are given Rs. 30,000. It’s yours to
keep. Then you are asked to choose between the
following two possibilities:
(A) Receive an additional Rs.10,000 for sure
(B) Toss a coin: if it comes up Heads, you get an
additional Rs. 20,000;
if tails, you get nothing.
Which Option do you prefer: (A) or (B)?

Prospect Theory and the Disposition Effect
• In a completely separate Game 2 (i.e., you should
not think of these as sequential games), you are
given Rs. 50,000; again, yours to keep.
Then you are asked to choose between the
following two possibilities:
(C) A guaranteed loss of Rs. 10,000
(D) Toss a coin: if it comes up heads, you lose Rs.
20,000;
if tails, you lose nothing.
Which Option do you prefer: (C) or (D)?

Disposition Effect
• If you picked (A) in the first game, and (D) in the second, you are
in very good company: this pair is the most commonly selected
combination
• Note, however, that the outcomes in the combination (A) and (C)
are identical: in both cases, you walk away Rs. 40,000 richer.
• Similarly, (B) and (D) are identical: together, they generate a 50%
chance of either Rs. 30,000 or Rs. 50,000.
• This preference “switch” is known as the Disposition Effect.
Why do so many people “flip” their preferences? If they
selected (A) in Game 1, why not stick with (C) (which has
identical outcomes in all scenarios) in Game 2?

• Disposition Effect: Risk Averse over gains and Risk seeking over
losses
• Investing: inclined to sell our winning investments (Tata consumer)
• Hold investments which are falling in value (Biocon)
Suggestion:
We should run gains ( Tata Motors)
We Should cut losses

• 2 cards are picked at random without replacement from a deck. 1st
card is red and 2nd is black. Probability? Red: 26/52= ½
Black: 26/51
• 12/51

Axioms Vs Biases
Axioms Bias
Invariance or
Consistency
Framing
Independence or
cancellation
Certainty Effect

The Juror’s Fallacy
• You are a member of a jury. A taxi driver is accused of having run down a pedestrian on a
stormy night and having fled the scene of the accident. The prosecutor, in asking for a
conviction, bases his whole case on a single witness, a lady who saw the accident from her
window a little way away. The witness testifies that she saw the pedestrian struck by a blue taxi
and then saw that taxi drive away from the scene. The accused works for a taxi company whose
taxis are all blue.
• During the trial, the following emerges:
• 1.There are only two taxi companies in this town. The whole fleet of one company is green; the
other has only blue cabs. Eighty-five percent (85%) of all taxis on the road that night were
green, and only fifteen percent were blue.
• 2.The single witness has undergone a number of vision tests in conditions similar to those of
the night of the accident. She has been shown to be able to identify the two colors correctly
about 80% of the time; i.e., out of all of the blue & green cabs she saw during the vision test, she
got the color right 4 out of 5 times.
• How likely is it that she actually saw a blue taxi that night?

• 85% taxis green
• 15% blue
• 1000 taxis
• Green: 850: 680 grren and 170 blue
• Blue: 150-120 blue and 30 green
• 80% right

Correlation error
• Subprime crisis

Probability
• We tend to-
• Overweight low probabilities
• Underweight high probabilities

Certainty Effect- Illustration 1
Imagine that the sadistic kidnapper that we saw earlier is back, and
this time he is forcing you to play Russian roulette. However, you
are allowed to purchase one bullet from the loaded gun (which has
6 chambers).
• How much would you be willing to pay to reduce the number of
bullets in the gun from four to three?
• How much would you pay to reduce the number of bullets from
one to zero?
• What about if you are told that the gun is currently fully loaded?
How much would you be willing to pay to remove one bullet this
time?

• Respondents are typically willing to pay significantly more to
reduce the number of bullets from one to zero –thus guaranteeing
their survival –than to reduce their survival probability from two-
thirds to one-half. Even though the objective probability reduction
is the same 1/6th in both cases, the move from probable to certain
survival is more emotionally appealing.
• Similarly, individuals tend to indicate higher willingness to pay for
the possibility of survival by removing one bullet from a fully loaded gun,
than for the equivalent reduction in probability in the middle of the range.

• We tend to overweight low probability events, especially events that are
especially “front of mind” or “salient” to us at a particular time
• We tend to underweight high probability events, especially those that are
sufficiently common that they tend not to be reported in the media
• We tend to be less sensitive to changes in probability in the middle
of the range (e.g., 30% to 40%) than changes that move us from
probability to certainty (10% to 0%, or 90% to 100%): the Certainty
Effect

Certainty Effect – Illustration 2
Suppose you have just purchased a house worth $200,000 in a
region of NC in which the probability of the house’s destruction by
flooding is about 1 in 100 (that is, the property may be expected to
be destroyed by floods about once every one hundred years).
• How much would you be prepared to pay for a flood insurance
policy against the value of your home?
• Suppose the insurance company is offering an alternative form of
insurance policy, in which the dollar premium is reduced, but the
insurance only applies to certain days of the week. How much
would you pay for a flood insurance policy that will pay out only if
the flood hits on a Monday, Wednesday, or Friday?

• People would rather eliminate risk than reduce it, even if the probability
of a catastrophe is diminished by an equal amount in both cases
• From a purely statistical perspective, if you are willing to pay $100
for annual flood insurance on all days, you should be willing to pay
about $43 (= 3/7 x 100) for the “flood insurance only on MWF” option.
• Most people, however, will pay much less for the partial insurance,
since it includes a level of uncertainty that people are not willing to
accept. Another way of saying this: we are willing to pay a premium
to move from uncertainty to certainty, relative to a simple change in
probabilities.

Certainty Effect- Illustration 3 (Relative vs.
Absolute)
As Hugh set out on his habitual morning walk across the park, he
pondered the troubling information that he read in the morning’s
newspaper: that “over-the-counter painkillers such as ibuprofen can
double the risk of a heart attack.” The article noted that millions “..depend
on such drugs to relieve the symptoms of arthritis, headaches, and other
common ailments…[but] now sufferers face the dilemma of whether to
continue taking some of the most commonly-used painkillers after they
were found to carry similar risks to other drugs which have already been
withdrawn.”

• Suppose that Hugh is 70 years old, has rheumatoid arthritis, and
depends on his daily dose of ibuprofen to manage the pain in his
joints
• Suppose that he also has a family history of heart disease, with both
his father and older brother dying from heart attacks in their late
70s
• How concerned should he be about the article in his morning
newspaper? Is there critical additional information that he should
obtain before deciding whether to quit taking ibuprofen for joint
pain?

Heuristic
• Heuristic is a rule of thumb; a mental shortcut to help us navigate
the enormous number of decisions we must make on a daily basis.
• Heuristics are essential, but many of these shortcuts can lead to
“biases”; situations in which the back-of-the-envelope assumption
steers us wrong, and in a predictable manner.

The Availability Heuristic
• People’s views on outcome probabilities are strongly influenced by
the ease with which we can recall examples of that outcome.
• Dramatic, heavily reported but rare events carry greater weight in
our minds because we hear so much about them.
• On the flip side, common but under-reported outcomes seem less
likely than they actually are.
• The Availability heuristic is a rule of thumb in which decision
makers assess the probability of an event by the ease with which
instances can be brought to mind.

Framing
Difficult Business Decisions
A large car manufacturer has recently been hit
with a number of economic difficulties, and it
appears as if three plants need to be closed and
6,000 employees laid off. The vice-president of
production has been exploring alternative ways
to avoid this crisis. She has developed two plans:
• Plan A: This plan will save one of the three plants and
2,000 jobs.
• Plan B: This plan has a 1/3 probability of saving all
three plants and all 6,000 jobs, but has a 2/3
probability of saving no plants and no jobs.
Prefer Plan A or Plan B

Framing
Highway Safety
Imagine that you are advising a small town about a
highway safety program. At present, about 600 people
per year are killed in traffic accidents in this town.
Two programs designed to reduce this number are
under consideration.
• Program A is expected to reduce the yearly number of
casualties 30; its annual cost is estimated at $12
million.
• Program B is expected to reduce the yearly number of
casualties by 100; its annual cost is estimated at $55
million.
Which program do you prefer, program A or program
B?

Framing
1.You can either accept a guaranteed $1,500, or play a
stylized lottery. The outcome of the stylized lottery is
determined by the toss of a fair coin. If heads, you win
$1,950. If tails, you win $1,050.
• Would you choose to participate in the lottery, or take
the guaranteed $1,500?
2.You can either accept a guaranteed loss of $750, or play
a stylized lottery. The outcome of the stylized lottery is
determined by the toss of a fair coin. If heads, you lose
$525. If tails, you lose $975.
• Would you choose to participate in the lottery, or pay
the $750 to avoid the lottery?

Consider the following two options

Framing
3.Imagine that you have just won $1,500 in one stylized
lottery, and have the opportunity to participate in a
second lottery. In this lottery, you will win $450 if heads
comes up, but lose $450 if tails comes up.
• Would you choose to participate in the second lottery
after having already won $1,500 the first?
4.You have justlost$750 in one stylized lottery, and have the
opportunity to participate in a second lottery, in which you
will win $225 if heads comes up, and lose $225 if tails comes
up.
• Would you choose to participate in this second lottery
after having lost $750 in the first one?
Choose Option 3 or Option 4

• Did you change your preferences?
• Many respondents choose NOT to participate in Option 1, but DO
participate in Option 3. Similarly, they DO participate in Option 2,
but do NOT participate in Option 4.
• Options 1 and 3 are the same. Both result in either a guaranteed
$1,500 if you don’t play the lottery, or a 50-50 chance of either
$1,950 or $1,050 if you do.
• Similarly Options 2 and 4.
Even if you personally did not flip your preferences, think about
why many respondents make the selections described above.

Framing- Personal Expenditures
• Question 1
Imagine you have decided to see a play where admission
is $60 per ticket. As you enter the theater you discover
that you have lost $60 (although you still have enough
money in your wallet to purchase the ticket). Would you
still pay $60 for a ticket to the play?
• Question 2
Imagine you have decided to see a play and paid the
admission price of $60 per ticket. As you enter the theater
you discover that you have lost the ticket. Would you pay
$60 for another ticket?
Mark your Answers

• Did you choose to pay for the ticket in Question 1, but not
in Question 2?
• On the face of it, both scenarios involve the discovery that
you are $60 poorer than you thought you were. So why do
many people choose differently in the two settings?
Here’s why:
• we are inclined to set up “mental budgets” for different
types of discretionary expenditure (food, clothing,
entertainment, etc.)
• In the first scenario, even though you realize you have lost
some money, it wasn’t from your “entertainment” budget
so you are willing to buy the ticket anyway.
• But when it’s the ticket itself that has gone missing, you are
much more inclined to feel as though you would be paying
$120 for the show if you buy another ticket –and this feels
like too much for this month’s “entertainment budget.”

Discussion
• When we make large expenditures, such as on a house or a
car, we will more readily add on expensive optional items
that we would never normally purchase on their own
• Car salesmen understand this very well, and will tack on
all sorts of additional items –various insurance policies,
extra gizmos –because Rs. 20,000 or so seems small relative
to the cost of the Rs. 6,00,000 car
• On the other hand, this bias can work in your favor. When
purchasing a new home, the “sticker shock "of all the
furniture you now need will be much lower if you go to
the furniture store very soon after the house is purchased.
Next to a Rs. 60,00,000 home, a few thousand rupees on
furniture feels minimal…

Mental Accounting and Insurance
Next time you purchase an electronics item, notice how the store always
offers you product insurance
• They want you to “bundle” the cost of the insurance along with the item
• Electronics stores make some of their biggest margins on product insurance,
rather than on the products themselves
• As an insurance provider, they know better than you do how likely it is that
the item will break –and of course they charge you more than the insurance is
worth (assuming that you are not an excessively clumsy individual)
• If you never buy product insurance, you’ll save more than enough money over your
lifetime to cover the cost of replacing the occasional broken item
So when should you buy insurance?
• When the item is sufficiently valuable/expensive that having to pay for the
insured item/service on your own would cause you excessive hardship (your
house; car; medical bills)

Mental Accounting and Portfolio Diversification
• One of the most important rules of investing is diversification: purchasing a broad range of
financial assets that are not strongly correlated has the benefit of making our overall
portfolio less volatile. “Don’t put all your eggs into one basket”
• The following graph provides an example of how, with the combination of just two different
assets, an investor may be able to achieve a portfolio with a better risk-return profile than investing in
either asset by itself.
• The graph on the next slide shows the expected return of assets 1 & 2 on the vertical axis, and
their expected volatility (i.e., risk) on the horizontal axis.
• Investors would like returns to be as high as possible, and volatility to be as low as possible –
they would like to follow the direction of the two arrows
• If Assets 1 & 2 are not strongly correlated, investors will be able to create portfolios with risk-
return profiles that lie along the curve between the two assets by putting some of their
money in each Asset
• Portfolio P, for example, has a lower volatility than either Asset 1 or Asset 2 on their own. It
also has a higher expected return than Asset 1
• As an example, an investor may hold in her portfolio a combination of both equities and
bonds, on the basis that these two assets are not highly correlated, and may sometimes
counterbalance one another.

An example with US Equities & Government bonds
• This graph shows the actual returns that an investor
would have earned by investing $1,000 in either US
Equities, US Government Bonds, or an equally-weighted
combination of the two, from January 2006 –January
2013.

• Suppose you had invested $1,000 in equities, and $1,000 in bonds, in 2006.
• If you watched the two portfolios separately, you would have seen the value of your
equity portfolio drop to about $550 by March 2009 (see the blue line on the graph) –a
time when many investors could take no more losses and gave up on their equity
portfolios, selling everything.
• Meanwhile, however, your bond portfolio was up to about $1,180; by no means covering
the equity losses, but at least providing some cushion. Your combined portfolio is down far
less (see the “50-50” line on the graph).
• By watching the two investments as a single portfolio, and not falling prey to
“mental accounting” (the tendency to treat the bonds and equities as two separate
investments), you are taking advantage of diversification, and you don’t end up
selling your equities after they have already fallen dramatically.
• As you can see from the graph, if you hold both portfolios through 2013, the value of
the combined portfolio shows much lower gyrations, and leaves you with about the
same amount of money as you would ultimately have earned from either asset by
itself.
• An investor who looks at each investment separately, and decides to exit the equity
markets in 2009, is missing the very point of why the equities are in his portfolio; he
also misses out on the huge equity rally from March 2009 onwards…

Loss Aversion- The Disposition Effect
Endowment Effect
• Once we own an item, we tend to view it as more valuable
• We have a preference for holding on what belongs to us
• We infer that the item has a greater value when it is ours
The Endowment Effect is related to:
• Status Quo bias: we like things the way they are (so what we own stays in our possession)
• Loss aversion: we assign greater negative weight to losses than positive weight to
equivalent-sized gains
Loss Aversion and the Disposition Effect
• When we hold assets that are currently priced below where we purchased them, we don’t
want to realize the loss.
• For as long as they are just a loss “on paper”, it’s somehow not “official”

Loss Aversion
Why are retailers often willing to let you purchase an item “on
trial”, or return it for a full refund?
(1) The Endowment effect: once you’ve taken it home, it becomes
“yours” and therefore you assign it higher value
(2) The Status Quo bias and Inertia: the effort of taking it back to the
store can kick in too

Anchoring
• “Anchoring”, the inclination to rely heavily on the first data point that
we receive when making decisions, is another consistent framing bias.
Another classic scenario is with regard to house prices.
• Regardless of any recent movements in house prices in their area, many
home owners refuse to set a selling price on their home that is lower than
where they bought it
• Surprisingly, the market does not always fully correct this error: sellers
facing a possible loss do in fact transact at statistically higher prices than
other sellers (although lower than the seller’s initial offer price)
• Anchoring can affect the buyer as well, who may anchor on the initial
(high) offer price
• This type of “sticky” price behavior is more common in markets where
pricing is opaque and there are relatively few comparison transactions.

Anchoring (Cont.)
• When consumers “anchor "on a particular make of car,
and always purchase the same make, they tend to pay
a lot more, on average, than automobile buyers who
are willing to switch brands.
• Most products come with a non-negotiable price. Car
buying, however, is a game best played by talented
negotiators who are willing to barter with the
salesman.
• If you know you are going to buy a Honda, say, you
are a much easier “mark "for the skilled salesman: his
only job is to get you to buy as many expensive
accessories as possible.

Anchoring (Cont.)
Why do companies spend billions to advertise their
products?
• The Availability heuristic: the more you hear about it, the
more familiar it becomes
• Anchoring: The company wants to “anchor "its product in
your mind
• Status quo bias: once you have developed a bias for a
particular brand, you are less inclined to “comparison shop”;
you simply go with the brand you know
• Individuals who prefer a certain make of cars will tend to
pay more for their car than someone switching from another
brand
• This effect tends to be stronger for automobile purchases
than for other expensive, branded products.

Framing
Case A:
• US income tax laws permit families to take a tax
deduction per dependent (e.g., a child), regardless of
the family’s total income.
• The question has been raised as to whether it would be
better to allow wealthy families to take larger tax
deductions per child. Wealthy families, after all, spend
more on their children than do poor families, and the
amount of money that it costs for wealthy families to
have children is much higher than the amount it costs
poor families.
• Based on this analysis, would you vote in favor of
higher child tax deductions for wealthier families?

Framing (Cont.)
Case B:
• US income tax laws permit families to take a tax deduction
per dependent (e.g., a child), regardless of the family’s total
income.
• The question has been raised as to whether it would be
better to reformulate tax laws so that, instead of deducting
the cost of children from a tax schedule; based on childless
families, a “childless premium” were added to a tax schedule; that
assumed the typical family had two or three children.
• In other words, suppose childless families were charged
“extra”taxes (instead of giving families with children a tax
break). Should a poor family without children pay just as
high a premium as a wealthy family without children?

Framing (Cont.)
In the first example, did you vote NO for higher child tax
deductions for wealthy families?
• If so, then you have voted in favor of all families continuing
with a fixed deduction per child.
In the second example, did you vote NO for just as high a
“childless premium "for poor families as for wealthy families?
• If so, you have voted in favor of poor families paying a smaller
increase for being childless than rich families must pay.
• This is equivalent to permitting wealthy families with children to
take a greater deduction per child than poor families…
• But you voted NO in the first situation, indicating that you
were NOT in favor of wealthy families taking a higher
deduction than poor ones!

Framing (Cont.)
Did you vote “NO” in both cases?
• In Case A, let’s say all families get a $4,000 deduction
per child, regardless of income level.
• In Case B, let’s assume that wealthy families must pay a
$4,000 premium if they are childless, while poor families
need only pay a $2,000 premium if they are childless.
• Thus, in Case B, wealthy families with a child pay
$4,000 less tax than wealthy families without a child.
But meanwhile, poor families with a child pay only
$2,000 less tax than poor families that are childless.
• So wealthy families are getting a bigger child tax
deduction than poor families. But you voted against this in
Case A…

This is classic framing –the way in which a decision is presented to
us can dramatically influence our response.

Framing
Difficult Business Decisions
A large car manufacturer has recently been hit with a
number of economic difficulties, and it appears as if three
plants need to be closed and 6,000 employees laid off.
The vice-president of production has been exploring
alternative ways to avoid this crisis. She has developed
two plans:
• Plan C: This plan will result in the loss of two of the three
plants and 4,000 jobs.
• Plan D: This plan has a 2/3 probability of resulting in the loss
of all three plants and all 6,000 jobs, but has a 1/3 probability
of losing no plants and no jobs.
Choose Plan C or Plan D

Did you notice that you’ve seen this Business
Decision Earlier The two potential solutions
were the same in both cases, but they were
presented slightly differently:

• Plan A: This plan will save one of the three plants and 2,000 jobs.
• Plan B: This plan has a 1/3 probability of saving all three plants and all
6,000 jobs, but has a 2/3 probability of saving no plants and no jobs.
• Plan C: This plan will result in the loss of two of the three plants and
4,000 jobs.
• Plan D: This plan has a 2/3 probability of resulting in the loss of all three
plants and all 6,000 jobs, but has a 1/3 probability of losing no plants and
no jobs.

• Many people select Plan A in the first case, and Plan D in the second. Did
you? If so, your preferences “switched”:
• Plans A and C are identical, but are “framed” differently
Program A is given in terms of jobs saved
Program C is given in terms of jobs lost
• The same applies to programs B and D
Options framed in terms of gains versus losses are treated differently, and
can cause people to “flip” their preferences. People are typically prepared
to gamble to avoid losses, but become risk-averse in the context of gains.

Highway Safety
• Imagine that you are advising a small town about a highway safety
program. At present, about 600 people per year are killed in traffic
accidents in this town. Two programs designed to reduce this
number are under consideration.
• Program A is expected to reduce the yearly number of casualties by
30, at a cost of $12 million.
• Program C is expected to reduce the yearly number of casualties by
100.At what cost for program C would you be indifferent between
the two programs? Please indicate the cost (to the nearest $1
million).

You’ve also seen this situation twice –but your second option has
been a little different in the two cases

• Program A is expected to reduce the yearly number of casualties
30; its annual cost is estimated at $12 million.
• Program B is expected to reduce the yearly number of casualties by
100; its annual cost is estimated at $55 million.
• Program C is expected to reduce the yearly number of casualties by
100. At what cost for program C would you be indifferent between
the two programs?

• Between A & B, many people select Program B because it projects to save
more lives, even though the cost per life is somewhat greater.
• However, when asked at what price for Program C they would be
indifferent between the two programs, most respondents suggest an
amount considerably lower than $55 million, suggesting that they prefer
Program A.
• Why? Because choosing and pricing are different psychological processes.
• When we are simply choosing between options, the choice is not dollar-based.
There is no implicit scaling between the two: it’s simply A vs. B
• When we are asked to put a dollar equivalent on a bet, however, the
payoffs (which are also expressed in dollars) will be weighed more
heavily.

Representativeness
Representativeness: The human desire to see patterns, even where
none exist – can generate a belief that we can predict the future,
based on fallacies about what has happened in the past.

Representativeness: Gambler’s Fallacy
Gambler’s Fallacy: The belief that, after the roulette wheel has
generated a series of Red numbers, that a black number must be
‘due’.
In reality, Each spin of the wheel is independent of the last.

Gambler’s Fallacy in Financial Markets
• Investors believe that equity market returns should ‘regress to the
mean’.
There are two fallacies:
1. The belief that we know the long run mean return of the equity
market. No one can promise that this mean will stay consistent in
future years.
2. The belief that the boom-bust cycle has some pre-specified
duration.

• Belief perseverance in the context of behavioral biases is the
tendency to cling to one's previously held or recently established
beliefs irrationally or illogically.
• Investors continue to hold and justify the belief because of their
bias toward belief in themselves or their own ideals or abilities.

Belief Perseverance Bias (Cognitive)
• Conservatism
• Confirmation Bias
• Representativeness
• Illusion of Control
• Hindsight
• Cognitive Dissonance

Conservatism Bias
• Conservatism bias is a belief perseverance bias in which people
maintain their prior views or forecasts by inadequately
incorporating new information that arises.
• Academic studies have demonstrated that conservatism causes
individuals to overweigh initial beliefs about outcomes and under
react to new information.
• As a result of conservatism bias, Investors may under react to or
fail to act on new information and continue to maintain beliefs
close to those based on previous estimates and information.

Confirmation Bias
• Confirmation bias is a belief perseverance bias in which people
tend to look for and notice what confirms their beliefs, and to
ignore or undervalue what contradicts their beliefs.
• This behavior encompasses aspects of selective perception and is an
all-too-natural action in which people convince themselves of what
they want to believe by giving more weight to evidence that
supports their beliefs and ignoring or modifying evidence that
conflicts with their beliefs.
• E.g. Poorly diversified portfolio

Representativeness Bias
• Representativeness bias is a belief perseverance bias in which
people tend to classify new information based on past experiences
and classifications.
• They believe their classifications are appropriate and place undue
weight on them.
• When confronted with new information, they use those categories
even if the new information does not necessarily fit.
• Investors often overweight new information and small samples
because they view the information or sample as representative of
the population as a whole.

• Brian: 70-30
Some fall might incur:
• Smruti: 40-60 Rajat- 65-35 Ashish:
-A: Debt Equity 1990-2008 5.5 Cr
B: Equity 1990-2008 12 Cr (World tour) 12-cr to 7 cr
18 Months: 2008 to mid 2009
A:5 Cr
B: 6.5 Cr (Cancel the world tour)
(Behavioral finance)
: Equity: 17% (Highly volatile)
-Prospect Theory

Illusion of Control
• Illusion of control bias is a bias in which people tend to believe that
they can control or influence outcomes when, in fact, they cannot.
• Traders believe that they have control over the outcomes of their
investments. This view leads to excessive trading, which may lead
to lower realized returns than a strategy where securities are held
longer and traded less frequently.
• Illusion of Control bias lead investors to inadequately diversify
portfolios.

Hindsight Bias
• Hindsight bias occurs when people see past events as having been
predictable and reasonable to expect.
• People tend to remember their own predictions of the future as
more accurate than they actually were because they are biased by
the knowledge of what has actually happened.
• The hindsight bias may cause investors to take on excessive risk,
leading to future investment mistakes.

Cognitive Dissonance Bias
• When newly acquired information conflicts with preexisting
understandings, people often experience mental discomfort—a
psychological phenomenon known as cognitive dissonance.
• Cognitions, in psychology, represent attitudes, emotions,
beliefs, or values; and cognitive dissonance is a state of
imbalance that occurs when contradictory cognitions intersect.
• Cognitive dissonance can cause investors to hold losing
securities positions that they otherwise would sell because
they want to avoid the mental pain associated with admitting
that they made a bad decision.
• Cognitive dissonance can cause investors to continue to invest
in a security that they already own after it has gone down
(average down) to confirm an earlier decision to invest in that
security without judging the new investment with objectivity
and rationality. A common phrase for this concept is
“throwing good money after bad.”

Information Processing Biases
• Anchoring & Adjustment Bias
• Mental Accounting Bias
• Framing Bias
• Availability Bias
• Self Attribution Bias
• Outcome Bias
• Recency Bias

Anchoring & Adjustment Bias
• Anchoring and adjustment bias is an information processing
bias in which the use of psychological heuristics influences the
way people estimate probabilities.
• When required to estimate a value with unknown magnitude,
people generally begin by envisioning some initial default
number—an “anchor”—which they then adjust up or down to
reflect subsequent information and analysis.
• Investors exhibiting this bias are often influenced by purchase
“points,” or arbitrary price levels or price indexes, and tend to
cling to these numbers when facing questions like, “Should I
buy or sell this security?” or “Is the market overvalued or
undervalued right now?” This approach is especially prevalent
when the introduction of new information regarding the
security further complicates the situation.

Mental Accounting Bias
• Mental accounting bias is an information processing bias in which
people treat one sum of money differently from another equal-
sized sum based on which mental account the money is assigned
to.
• A potentially serious problem that mental accounting creates is the
placement of investments into discrete “buckets” without regard
for the correlations among these assets.

Framing Bias
• Framing bias is an information processing bias in which a person
answers a question differently based on the way in which it is
asked (framed).
• Investors may misidentify risk tolerances because of how questions
about risk tolerance were framed; may become more risk-averse
when presented with a gain frame of reference and more risk-
seeking when presented with a loss frame of reference. This may
result in suboptimal portfolios.

Availability Bias
• Availability bias is an information processing bias in which people
take a heuristic (also known as a rule of thumb or a mental
shortcut) approach to estimating the probability of an outcome
based on how easily the outcome comes to mind.
• People often unconsciously decide the probability of an event by
how easily they can recall a memory of the event. The fundamental
issue is that many people are biased in their memories. For
instance, recent events are much more easily remembered and
available.

Self Attribution Bias
• Self-attribution bias (or self-serving attribution bias) refers to the
tendency of individuals to ascribe their successes to innate aspects,
such as talent or foresight, while more often blaming failures on
outside influences, such as bad luck.
• Self-attribution investors can, after a period of successful investing
(such as one quarter or one year) believe that their success is due to
their acumen as investors rather than to factors out of their control.
This behavior can lead to taking on too much risk, as the investors
become too confident in their behavior.

Outcome Bias
• Outcome bias refers to the tendency of individuals to
decide to do something—such as make an investment
in a mutual fund—-based on the outcome of past
events (such as returns of the past five years) rather
than by observing the process by which the outcome
came about (the investment process used by the
mutual fund manager over the past five years).
• Investors may invest in overvalued asset classes based
on recent outcomes, such as strong performance in
gold or housing prices, and not pay heed to valuations
or past price history of the asset class in question,
thereby exposing them to the risk that the asset class
may be peaking, which can be “hazardous to one's
wealth.”

Recency Bias
• Recency bias is a cognitive predisposition that causes people to
more prominently recall and emphasize recent events and
observations than those that occurred in the near or distant past.
• Recency bias can cause investors to extrapolate patterns and make
projections based on historical data samples that are too small to
ensure accuracy. Investors who forecast future returns based too
extensively on only a recent sample of prior returns are vulnerable
to purchasing at price peaks. These investors tend to enter asset
classes at the wrong times and end up experiencing losses.

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