Lecture 1 – 16 May
Article 1: Judgement under Uncertainty: Heuristics and Biases
This landmark cognitive science paper lead to prospect theory, behavioral economics and
eventually Nobel Prize in Economics to the authors. Hypothesis of this paper is presented very
well: humans rely on a set of heuristics for decision-making and these useful yet incomplete
heuristics lead to cognitive biases in judgement. These heuristics are (i) Representativeness:
probability of an event which resembles a class is judged to be high. This leads to insensitivity to
priors, sample size etc. (ii) Availability: probability of an event is judged by its imaginability. This
leads to biases such as illusory correlation (iii) Anchoring and adjustment: people adjust estimates
from an initial anchor. Insufficient adjustment leads to under or over estimation. Note that these
heuristics and biases are distinct from motivational biases such as wishful thinking.
https://chsasank.com/classic_papers/judgement-uncertainty.html#
https://astrofella.wordpress.com/2019/04/05/judgement-under-uncertainty-heuristics-andbiases-amos-tversky-daniel-kahneman/
How do people assess the probability of uncertain events or the value of it?
 People use limited numbers of heuristics (three) principles to reduce complex thinking and
tasks of assessing probabilities and predict values to simpler judgmental operations.
 Heuristics = A heuristic is a mental shortcut that allows people to solve problems and make
judgments quickly and efficiently. These rule-of-thumb strategies shorten decision-making
time and allow people to function without constantly stopping to think about their next
course of action
o Can lead to error.
 The judgement of probability is based on data of limited validity, processed by heuristic: See
example with distance.
o E.g., biases (error) are found in intuitive judgement of probability too, like distance
example.
Three heuristics:
1. Representativeness (“similar to”)
2. Availability
3. Adjustment and Anchoring
Representativeness
 Example Steve (librarian and shy).
o People see Steve as librarian; take-away = people order the occupations by
probability and similarity in same way.
 This approach to the judgement of probability leads to ERRORS.
Similarity/representativeness is not influenced by factors that affect
judgements of probability. Following factors have NO effect on
representativeness but should have =
1. Insensitivity of prior probability of outcomes (example engineer/lawyer probability
judgement)
o
When no specific evidence is given, prior probabilities are
properly utilized, when worthless (sketches; example)
evidence is given, prior probabilities are ignored
2. Insensitivity to sample size (2 examples; babies/hospitals & urn red/white balls)
o Not taking into account the sample size when coming to a
conclusion.
3. Misconceptions of chance (example: roulette = gamblers’ fallacy & “law of small numbers”)
o people expect that a sequence of events generated by a
random process will represent the essential characteristics
of that process even when the sequence is short
4. Insensitivity to predictability (example: firm valuation & teacher evaluation = evaluate vs.
predict)
5. The illusion of validity
o People often predict by selecting an outcome (occupation)
that is most representative of the input (description person).
 The confidence they have in their prediction is based
on the degree of representativeness. = quality of the
match between the selected outcome and the input.
 E.g., librarian stereotype; based on intel, good or
bad, people think they are right. That Steve is a
librarian.
 This is ILLUSION OF VALITIDITY = confidence of
prediction, due to good fit between input info and
predicted outcome.
 -> example: grade; greater confidence
wehen inputs variables are redundant
(more)
o Redundancy
among
inputs,
decreases accuracy but increases
confidence.
6. Misconceptions of regression
o People often fail to recognize a regression.
o “Regression toward the mean”, often not see it =
 First; do not expect regression in many context
 Second; when they do, they invent causal
explanation that are not right.
 See example Pilots, rewards/punishment and
regression. -> leads to only punishment.
Availability
The availability heuristic, also known as availability bias, is a mental shortcut that relies on immediate
examples that come to a given person's mind when evaluating a specific topic, concept, method or
decision. The availability heuristic operates on the notion that if something can be recalled, it must be
important, or at least more important than alternative solutions which are not as readily recalled.
Subsequently, under the availability heuristic, people tend to heavily weigh their judgments toward
more recent information, making new opinions biased toward that latest new.
The reliance on availability leads to predictable biases =
1. Biases due to retrievability of instances (example: car accident)
2. Biases due to effectiveness of a search set (example: word -> letter R recognition)
3. Biases of imaginability
a. Hereby frequency is assessed by not based on memory but that can be generated
according to a given rule.
i. So, one uses the ease of constructing instances, but this does not reflect the
actual frequency = bias.
ii. And, imagination plays important role in the evaluation of probilities in reallife situations. Example = expedition, often thought of as dangerous, but
likelihood that it happens is something different. People think of all the
dangerous things that can happen.
4. Illusory correlation
a. Co-occurrence of events (mental illness and color of eyes)
i. Depends on availability
ii. And if there is a strong bond between them. If the bond is strong, people think
they occur more frequently together.
iii. And that associative connections between events are strengthened when the
events frequently occur.
Adjustment and Anchoring
Anchoring and adjustment refers to a cognitive heuristic that influences how people assess
probabilities in an intuitive manner. According to the anchoring and adjustment heuristic, people
employ a certain starting point (“the anchor”) and make adjustments until they reach an acceptable
value over time.
 People keep adjusting initial value until it fits the outcome.
1. Insufficient adjustment
o Familiarity
o Salience
2. Biases in the evaluation of conjunctive and disjunctive events
o People overestimate the probability of conjunctive events
(often optimism) and underestimate the probability of
disjunctive events (often risks).
 E.g., new product development
 Often in complex, there are many components, so if
one component in the system has slight chance to
fail, the total system if quite vulnerable.
3. Anchoring in the assessment of subjective probability distributions
o E.g., Dow-Jones average
 Probability distribution
 Calibration
 Confidence interval of 98% between X1 and
X99.
 People often state overly narrow confidence
intervals that is justified by their knowledge = BIAS
 Often related to naïve and complex subjects
o Related to ANCHORING
 See green exclamation mark
 THE STARTING POINT INFLUENCES HOW
THEY COME TO THE OUTCOME.

E.g., two groups, whereby second group was able to
better judge the true value, as they received the
judgment of group 1 as starting point.
 So; the degree of calibration depends on
the procedure of elicitation.
Discussion
 Subjective probability (modern decision theory)
o
People will try to make probability judgement compatible with their own knowledge
about the subject, the laws of probilities, and his/her own judgmental heuristics and
biases.
Summary
This article describes 3 heuristics that are used in making judgements under uncertainty:
1. Representativeness, which is employed when people are asked to judge the probability that
object/event A belongs to class/process B.
2. Availability of instances/scenarios, which is often employed when people are asked to assess
the frequency of a class or the plausibility of a particular development.
3. Adjustment from an anchor, which is usually employed in numerical prediction when a
relevant value is available.
These heuristics are highly economically and effective, BUT lead to systematic and predictable errors.
If we understand these heuristics and the biases they lead to, we can improve judgements and
decision in uncertain situations.
 This article leads to the “prospect theory”; which is explained in the next article.
Lecture 2
Article: A survey of behavioral finance (SECTION 2)
There are some financial phenomena that can only be understood by using the models, in
which some people are not fully rational. This field has two building blocks:
1. Limits to arbitrage = SECTION 2
a. Hard for traditional traders to undo the dislocations caused by less rational
traders
2. Psychology = SECTION 3
a. Catalogues the kinds of deviations from full rationality we might expect to see.
Most traditional finance paradigms assume agents to be rational.
Rationality =
1. When people get new info, they update their beliefs correctly – Bayes’ law
2. According to their beliefs, people make the acceptable choices, in line with Subjective
Expected Utility (SEU).
Traditional framework, does not work that well -> so behavioral finance tries to explain these
difficulties.
 Some situations are better understood, assuming agents are not fully rational
Main OBJECTION to behavioral finance = ARBITRAGE = some agents are not fully rational, but
rational agents prevent them from influencing prices for very long, through a process of
arbitrage.
 But one the building blocks of BF, and recent successive papers, show that irrational
traders CAN have a long-term impact on prices. And that rational traders do not make
up for that.
WE FOCUS ON SECTION 2 ONLY = LIMITS TO ARBITRAGE
2.1 Market efficiency
Traditional framework = agents are rational, and security’s prices equal fundamental value
(meaning the discount rate is correct, all info is there etc.)
 = the hypotheses that actual prices reflect fundamental values = EMH (prices reflect
all information).
o EMH = “prices are right”

Set by agents who understand Bayes’ law and sensible preferences

In efficient market; there is no “free lunch” = no investment strategy
can earn excess risk-adjusted average returns, or average return > are
warranted for its risk. = NO EASY PROFITS FOR THE TAKING.
 Opposite view = Behavioral Finance
o Deviations from fundamental value, and that these deviations are bought by
traders who are not fully rational.

Friedman (1953) says BF is not right -> backs-up the EMH principle

Friedman view = rational traders quickly undo dislocations/mistakes
from irrational traders – Ford example $20

Friedman theory is based on two statements/assertions:

1) when there is a mispricing, attractive investment opportunity is
created.

2) rational traders will immediately snap up the opportunity ->
correcting the mispricing.
o BF does not believe Friedman’s first point; it believes the second though.
o Argument = even when an asset is mispriced, strategies designed to correct
mispricing can be both risky and costly – making them unattractive and unused/unchallenged. -> see 2.2 & 2.3
 Arbitrage = investment strategy offering riskless profits at no costs = rational traders
o This is what Friedman says: rational traders are arbitrageurs; due to the belief
that mispriced assets create opportunity of riskless profit

BF does not believe this: strategies that the traders in Friedman’s
model adopt are not necessarily arbitrages, BUT often very RISKY!

A conclusion/corollary from this statement = “prices are right” and
“there is no free lunch” (= EMH) are no equal statements.

Both are true in efficient markets -> “no free lunch” can be true in an
inefficient market as well. -> if the market is not perfect; there can still
be excess risk adjusted returns for the taking (can still be done).

IMPORTANT DISTINCTION
2.2 Theory
When mispricing occurs, strategies designed to correct it can be both risky and costly,
allowing mispricing to survive. Not as Friedman believes, riskless (arbitrage). Here are some
of the identified risks and costs:
a) FUNDAMENTAL RISK
b) NOISE TRADER RISK
c) IMPLEMENTATION COSTS
Because (real-world) arbitrage includes 1) costs and 2) risks, arbitrage is limited and allow
deviations from fundamental value to continue/persist. There are conditions under which this
happens (limit arbitrage):
1) Mispriced securities do not always have a close substitute, the arbitrageur is then
exposed to fundamental risk. In this case, the following conditions limit arbitrage:
a. Arbitrageurs are risk averse; and
b. That the fundamental risk is systematic = cannot be diversified (spread risks)
i. Condition a = due to this mispricing not wiped out by single arbitrageur,
because risk averse, they also hesitate to invest in lower Ford stock.
ii. Condition b = mispricing not be wiped out by large number of investors
each adding small positions in the mispriced security to their current
holdings.
 Noise trader risk & implementation costs only further limit arbitrage.
Substitutes protect arbitrageurs against fundamental risk.
BUT: even with the perfect substitute, arbitrage can still be limited.
Some arbitrageurs -> exploit noise trading -> moving in the same direction. Page 1058/1059.
2.3 Evidence
 See page 1059: explains that arbitrage is limited, as persistent mispricing already is
evidence for limited arbitrage, otherwise there would be no mispricing.
o And see “joint hypothesis problem” =
 The joint hypothesis problem is the problem that testing for market
efficiency is difficult, or even impossible. Any attempts to test for
market (in)efficiency must involve asset pricing models so that there
are expected returns to compare to real returns.
2.3.1 Twin shares
Short selling = lending shares from a party, selling them on the market, betting that shares
will drop further. In the meantime, people on the market bought the share for $5 and you
only must repay $3, if the stock keeps decreasing. If the stock suddenly goes to $10, then
the short seller loses big time.
The main conclusion from this part is that NOISE TRADER RISK = the only risk (1 out of the 3)
that limits arbitrage. KEY LEARNING PONTS:
 Whatever investor sentiment is causing one share to be undervalued relative to the
other could also cause that share to become even more undervalued in the short
term.
 As discussed earlier, when a mispriced security has a perfect substitute, arbitrage
can still be limited if (i) arbitrageurs are risk averse and have short horizons and (ii)
the noise trader risk is systematic, or the arbitrage requires specialized skills, or
there are costs to learning about such opportunities. It is very plausible that both (i)
and (ii) are true, thereby explaining why the mispricing persisted for so long.
 The only risk that remained = NOISE TRADER RISK.
2.3.2 Index inclusions
 Ask during office hour/ or lecture??? Not clear.
2.3.3 Internet carve-outs
In this case investors could earn by shorting 1.5 shares of Palm. But this was very expensive,
as demand for shorting was very high and not legal, therefore arbitrage was limited and
mispricing persisted. So, the only risk here = Implementation costs (VERY HIGH)
Lecture 3
Article: A model of investor sentiment
Research focuses on (found): underreaction of stock prices to news such as earnings
announcements, and overreac- tion of stock prices to a series of good or bad news.
Pervasive regularities = sterke regelmatigheden. = under and overreaction.
This paper explains from a behavioural aspect how investors form beliefs that lead to
underreaction or overreaction.
- On short-term = underreaction = post-earnings
announcement drift
- On long-term (reversal) = overreaction = winner-loser
effect (in short-term good performers do well, in longterm they underperform. High valuations will
eventually return to the mean.
This study explains how investor sentiment (form believes/how people form expectations)
that lead to under or overreaction; consistent with statistical evidence.
1. Main results are consistent with heuristic = REPRESENTATIVENESS (ignore th laws of
probability)
a. In the stock market, for example, investors might classify some stocks as growth stocks
based on a history of consistent earnings growth, ignoring the likelihood that there are
very few companies that just keep growing.
2. And relates to CONSERVATISM = slow updating of beliefs (models) when new
evidence (news) arrives. = mainly linked to UNDERREACTION.
Important reason why arbitrage is limited according to this paper = NOISE TRADER RISK =
hat movements in investor sentiment are in part unpredictable, and therefore arbitrageurs
betting against mispricing run the risk, at least in the short run, that investor sentiment
becomes more extreme and prices move even further away from fundamental value.
Model:
Asset follow random walk; investor does not know that. Investor believes that behavior of
firm’s earnings moves between two states.
1) Earnings are mean reverting
2) Earnings trend (increase further)
Investor thinks that the transition probabilities between two regimes are fixed; and believe
that in a given period the earnings of a firm only stay within one regime.
Overreaction occurs when decision makers respond disproportionately to new
information. Underreaction means that investors do not react enough to
information.
2.1 Underreaction (they should have responded more as the stock return is higher than
bad news)
Based on news announcement.
 Z = new an investor hears
o Z = G (good news)
o Z = B (bad news)
 Underreaction means that average return of firm stock in the period after the
announcement of good news is higher than the average stock return following the
bad news. It is higher than expected, they underreacted to this trend.
 Thus the stock underreacts to the good news, a mistake which is corrected in the
following period.
2.2 overreaction (they should have responend less, as the stock return is lower
Return (stock) is lower when there is lots of good news announcement, compared to stock
return following a series of bad news -> logical; investors respond too much on the good
news increasing stock prices, but subsequent announcement are likely to contradict his
optimism, leading to lower returns instead
- Here they overreacted, optimism, should have led to
higher stock return, but lead to lower stock returns
instead, as bad news follows. Not impermanently good
news.
Workshop 1b:
Article Investors Inattention and Friday Earnings Announcements (Dellavigna & Pollet,
2009)
Does limited attention among investors affect stock returns?

Friday announcements have 15% lower immediate response and a 70% higher delayed
response = less immediate response and more drift (deviation/appreciation or
depreciation) for Friday announcements.
o You can use this to your advantage by investing in these differential Friday
drifts and earn substantial returns as other investors are lacking.
o The findings supports the explanation of post-earning announcement drift is
based on underreaction to information caused by limited attention.
o DRIFT = stock’s abnormal returns to drift in a direction of an sudden earnings
surprise for several weeks following the announcement.

Bad news = drift downwards for at least 60 days; it should be
immediately/quickly digested by investors in the stock price (efficient
market) but this is not the case as we know.

Good news = drift upwards for at least 60 days following the earnings
announcement.
Lecture 6: Application: Corporate Finance – biased managers
Article: Who makes acquisitions? CEO overconfidence and the market’s reaction
RQ = does CEO help to explain merger decisions? = Does CEO overconfidence helps to explain
the losses of acquirors?
Findings:

Odds of making an acquisition is 65% higher when CEO is overconfident
o This effect is largest when the merger is diversifying, and no external financing
is needed.
o Market reacts more negative (-90 basis points) to merger announcement from
overconfident CEO, compared to non-overconfident CEO (only -12 basis
points).
Hypotheses:

Overconfident CEOs also overestimate returns they generate internally and believe
outside investors undervalue their firm.
o Result of this: they do not want to raise outside capital, even when it is
required for a merger. They let the merger slide. = the effect on merger
frequency is then ambiguous.

Therefor, CEOs are unambiguously (only open for one thought) more
likely to only conduct mergers if there is internal financing.
o And, if overconfidence increases merger frequency, it lowers the deal quality
and results to lower average market reaction to announcement of merger bids.
Measurement:

Personal portfolio decisions of CEOs from 394 large U.S. firms.
o Some CEOs fail to exercise or use stock options, assuming they are risk averse.

They make losses from holding their options relative to a diversification
strategy.

The beliefs CEOs have in their personal portfolio (and the choices they make) are
linked to the merger decisions these CEOs have.
o RESULT: CEOs who fail to diversify their personal portfolios are significantly
more likely to conduct mergers at any point in time.

These results are the strongest when firms have enough internal
financing and for diversifying acquisitions.

Where diversification is a proxy for value destruction
o = confirm overconfidence hypothesis.