FIN 468: Intermediate
Corporate Finance
Topic 11–Behavioral Corporate Finance
Larry Schrenk, Instructor
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Topics

Foundations of Behavioral Finance

Anomalies and Applications to Corporate
Finance
A Cautionary Note

In my Opinion–but Not Necessarily in the
Opinion of my Colleagues in Finance.
1.
There is good evidence for the empirical
examples I will present.
2.
The theoretical explanations are more
speculative, and almost every claim in these
areas is controversial.
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Foundations of
Behavioral Finance
Three Areas of Study
Anomalies▪
Evolutionary
Psychology
Neuroeconomics▪
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1. Anomalies

Deviations from Classical Economic Behavior


‘Irrationalities’
Only Relevant if Systematic
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Anomaly Example


Framing
'Asian Disease' Experiment



Given an outbreak of the Asian disease, and 600
people who are going to die, which plan should be
implemented?
Plan A or Plan B?
Same Choice, but Two Alternate Frames
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Frame 1–’Life’ Language

Plan A


200 people are saved.
Plan B


33% chance that all will be saved
67% chance that none of them will be saved
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Frame 2–’Death’ Language

Plan A


400 people die.
Plan B


33% chance that all will be saved
67% chance that all will die.
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Results

Frame 1–Life Language



A
B
72%
28%
Certain Choice
Risky Choice
Frame 2–Death Language


A
B
22%
78%
Certain Choice
Risky Choice
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2. Evolutionary Psychology

Reasoning

Human Organs Evolve in Response to
Environment

Brain is a Human Organ

Our Brian has Evolved in Response to
Environment encountered during Human
Evolution
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Evolutionary Psychology

Traditional Brain View



Tabula Rasa–’Blank Slate’
Flexible; Open to Any Programming
Evolutionary Psychology (one version)



Modular Brain
Neural circuits designed for problems faced during
our evolutionary history.
Question of Universality

Domain-Specificity vs. Domain-Generality
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Evolutionary Psychology

When Did the Brain Evolve?

Pleistocene Period


Human Evolution




1.8M to 10,000 years ago
Homo erectus
1.6M years ago
Homo sapiens
200,000 years ago
Permanent Human Settlements 10,000 years ago
Hunter-Gatherer Societies for 99% of Human
Development
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Evolutionary Psychology

Possible Evolution 10,000 to present

Lactose Intolerance Example

Future Evolution

Time Scale
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Evolutionary Psychology

Roughly phrased…
We are using hunter-gatherer modules
to confront 21st century problems, or
Our modern skulls house a stone age
mind.
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Evolutionary Psychology
Examples

Evolved Fear-Learning Psychology


Data: While spiders and snakes kill far less than
guns, people nonetheless learn to fear spiders
and snakes about as easily as they do a pointed
gun, and more easily than an unpointed gun,
rabbits or flowers.
Explanation: Spiders and snakes were a threat to
human ancestors throughout the Pleistocene,
whereas guns (and rabbits and flowers) were not.
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Evolutionary Psychology
Examples

Hunting Hypothesis and Human Coalitions

Mating Behavior
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3. Neuroeconomics




Study of how the brain functions when
making decisions.
Neuroimaging, e.g., fMRI, PET Scans
Imaging brain activity to infer how the
brain works.
Issues


Automatic versus Controlled Processes
Emotions
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Neuroeconomics

fMRI
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Neuroeconomics
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Neuroeconomics and Framing



“Activity in the frontal and parietal cortices suggests that working
memory and imagery mechanisms are involved differentially in
choosing risky versus sure options”
“fMRI results indicate that the certain choice is considerably less
costly (in terms of cognitive effort) than the risky one when
individuals choose among options framed as gains.”
“Since [in negatively framed questions] participants chose the risky
option more often than the certain option in response to such
problems, our results suggest that people are more willing to accept
a computational rather than an emotional cost,

Gonzalez, et al. “The Framing Effect and Risky Decisions: Examining
Cognitive Functions with fMRI.” (2005)
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Neuroeconomics and Framing
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Automatic versus Controlled
Processes
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Anomalies
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The Anomalies
1.
2.
3.
4.
5.
6.
7.
8.
Excessive Optimism
Overconfidence
Confirmation Bias
Illusion of Control
Representativeness
Availability
Anchoring
Framing
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Excessive Optimism

People overestimate favorable and
underestimate unfavorable outcomes.
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Excessive Optimism Examples



Most people display unrealistically rosy views
of their abilities and prospects.
Typically, over 90% of those surveyed think
they are above average in such domains as
driving skill, ability to get along with people
and sense of humor.
They predict that tasks (such as writing
survey papers) will be completed much
sooner than they actually are.
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Excessive Optimism and
Corporate Finance




Managerial overconfidence and optimism
lead to overinvestment.
Foreign exchange companies are more
optimistic about how exchange rate moves
will affect their firm than how they will affect
others.
Delayed cost cutting.
Stock bubbles
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Overconfidence

People are overconfident in their abilities and
knowledge.
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Overconfidence Examples


Confidence intervals people assign to their
estimates of quantities–the level of the Dow
in a year, say–are far too narrow. Their 98%
confidence intervals, for example, include the
true quant.
People poorly estimate probabilities:


Events they think are certain to occur actually
occur only around 80% of the time, and
Events they deem impossible occur approximately
20% of the time.
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Overconfidence Examples


Expertise, too, is often a hindrance rather
than a help
Experts, armed with their sophisticated
models, have been found to exhibit more
overconfidence than laymen, particularly
when they receive only limited feedback
about their predictions.
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Overconfidence and Corporate
Finance



Research shows that professionals from
many fields exhibit overconfidence in their
judgments, including investment bankers,
engineers, entrepreneurs, lawyers,
negotiators, and managers.
Overconfidence can lead to investment
distortions, predominantly overinvestment.
Economic overconfidence, e.g., forecasting
business cycles.
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Confirmation Bias

People put too much confidence in
information that supports their own view.
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Confirmation Bias Examples



People are reluctant to search for evidence
that contradicts their beliefs.
Even if they find such evidence, they treat it
with excessive skepticism.
Some studies have found an effect whereby
people misinterpret evidence that goes
against their hypothesis as actually being in
their favor.
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Confirmation Bias and Corporate
Finance


"Investors tend to seek out information that
supports their existing point of view while
avoiding information that contradicts their
opinion.” (Rappaport and Mauboussin, 2001)
Many executives of companies, cocooned in
their own little worlds and rarely receiving
negative feedback, develop their own
intransigent views that are impervious to
disconfirming evidence.
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Illusion of Control

People overestimate their ability to control
events.
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Illusion of Control Examples



Being in control makes us feel happy.
The absence of control produces withdrawal
and depression.
In a 1975 study Yale University students
were asked to predict the results of coin
tosses

A significant number of presumably intelligent
Yalies believed their performance could improve
through practice, and would have been hampered
if they’d been distracted.
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Illusion of Control and Corporate
Finance

Managers tend to overestimate their ability to
lead a project to success.

Online Traders

Excessive belief in the control of risk.
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Representativeness

People make decisions based on stereotypes
or typical/representative examples.
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Representativeness Examples


Description: Linda is 31 years old, single,
outspoken, and very bright. She majored in
philosophy. As a student, she was deeply
concerned with issues of discrimination and
social justice, and also participated in antinuclear demonstrations.
Which is more likely: “Linda is a bank teller”
or “Linda is a bank teller and is active in the
feminist movement”
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Representativeness and
Corporate Finance



Gambler's Fallacy: If a quarter lands on
heads five times, a person incorrectly
believes that the probability tails increases.
It may give too much emphasis to the
similarities between events (or samples), but
not to the probability that they will occur.
Representativeness may reduce the
importance of variables that are critical in
determining the event's probability.
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Availability

People put too much confidence in
information that is available and more easily
understood.
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Availability Examples


When judging the probability of an event
people often search their memories for
relevant information.
More recent events and more salient events
will weigh more heavily and distort the
estimate.
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Availability and Corporate
Finance



Availability causes us to frequently misread
probabilities, and get into investment
difficulties as a result.
Saliency and emotional events can dominate
decision-making in the stock market.
The tendency of recent and salient events to
move people away from the base-rate or
long-term probabilities cannot be
exaggerated.
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Anchoring

People use an initial value in making an
estimation, but do not adjust it sufficiently or
use an irrelevant number.
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Anchoring Example


Take the last three numbers of your Social
Security number and add 400.
Now answer this question…

Attila and the Huns invaded Europe and
penetrated deep into what is now France
where they were defeated and forced to return
eastward. In what year did Attila’s defeat occur?
Anchoring Example
Correct Answer: 451 AD
Experiment Results:






Anchor
400-599
600-799
800-999
1000-1199
1200-1399
Mean
626
660
789
865
988
The artificial and irrelevant calculation
affects the estimate!
Anchoring and Corporate Finance



Some investors invest in the stocks of
companies that have fallen considerably in a
very short amount of time anchoring on a
recent "high" that the stock has achieve.
Many time investors will cling to an
investment waiting for it to "break even," to
get back to what they paid for it.
Securities get anchored on their own
estimates of a earnings or on last year's
earnings.
Framing


People allow the way a problem is described
to influence their decision.
Such effects are powerful. There are
numerous demonstrations of a 30 to 40%
shift in preferences depending on the wording
of a problem.
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Framing Examples


Asian Flue (above)
Suppose that you have flipped a coin five
times but you don’t yet know your wins and
losses. Would you play the gamble a sixth
time?

60% don’t suggesting that some subjects are
framing the sixth gamble narrowly, segregating it
from the other gambles.
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Framing and Corporate Finance


Investments decisions are considered
individually rather than in a broader
framework.
Investors care about annual changes in
financial wealth even if they have longer
investment horizons.
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