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CFA 2015 Level 3 - SS 3 Behavioral Finance

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Denis C

on 28 September 2015

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Transcript of CFA 2015 Level 3 - SS 3 Behavioral Finance

Reading #6
The Behavioral Finance Perspective

CFA 2015 Level 3
SS 3:

Reading #7
The Behavioral Biases of Individuals

Reading #8
Behavioral Finance and Investment Process

Traditional Finance (TF)
Behavioral Finance (BF)
normative: focuses on how individual
descriptive: focuses on how individuals
(1) Micro BF:
how & why
deviate from TF theory
(2) Macro BF:
how & why
deviate from "efficient"
Individual investors are Rational Ecomonic Men
In TF, investors are

(Rational Economic Men) aka "Homo Economicus":

TF assumes that REM investors:
are risk-averse
have perfect information
focus on maximizing their personal utility function

Moreover, in decision making:
REM follows "4 axioms"
REM uses Bayes' formula

As a result, REM behaviour leads to
Efficient Markets
In making utility maximizing decisions, REM investor follows
4 Axioms of Utility
individuals know their preferences
given choices D,E
preference can be one of D>E, D<E, or D=E
individuals consistently apply rankings
D>E and F>D
rankings are additive and proportional
D, F mutually exclusive; D>F; and J additive
continuous utility indifference curves
exists a and b,
such that aF+bE=D
Given new information, REM investor updates beliefs about probabilities using
Bayes' formla:

P(A) - unconditional prob. of event A
P(B) - unconditional prob. of event B
P(A|B) - conditional prob. of event A, given B occured
P(B|A) - conditional prob. of event B, given A occured
TF assumes REM investors are
, and prefer greater certainty to less certainty
For risk-averse person, utility funciton is concave, meaning for 1 unit fall in Wealth, Utility decreases more than it increases for 1 unit gain in Wealth.
Summary so far
TF Assumes:
Bounded Ratioinality and
Prospect Theory
unlimited perfect knowledge

utility maximization

fully rational decision making

capacity limitations
on knowledge


conitive limits
on decision making

reference dependence and
loss aversion leading to possble
cognitive errors
Prospect theory only
Rational decision making according to Utility Theory
Efficient markets
Individual investors not alway rational and subject to biases
Decision making according to Prospect Theory
Markets are not always efficient
Individual Investors in TF
It is the foundation of TF
People maximize objective:
Expected value of PV(Utility)
subject to constraint:
= "level of relative
received from the consumption of goods and services"

Utility Theory assumes "
diminishing marginal return
", meaning:
utility function is concave
since REM is risk-averse, and;
indifference curves are convex
due to diminishing marginal return of substitution
Challenges to TF and REM

lack of information
and flaws in decision-making process

inner conflicts
lead to poor prioritization (i.e. short-term "spending" goals over long-term "saving" goals)

lack of perfect knowledge
(i.e. can people correctly assess impact of central bank policy?)

wealth utility may not always be concave as assumed by utility theory, as
individuals not always "risk-averse"
Individual Investors in BF
Recognizes that real individual are not like REM
Individuals can be any of:
(1) risk-averse; (2) risk-neutral; (3) risk seeking
Satisfaction from +$100
Dissatisfaction from -$100
Satisfaction from +$100
Dissatisfaction from -$100
Satisfaction from +$100
Dissatisfaction from -$100
Indifference curve
shows points at which REM would be equally satisfied between two substitutes
shape means that too much of either W or L is not as good as a combination of the two.
Utility Function
shows how much utility REM derives from additional unit of Good (Wealth/Leisure/etc.)
shape means that less utility is gained from each additional unit of Wealth
Challenges to Utility Theory and Indifference Curves

individuals often
unable to quantify
mathematical trade-offs

indifference curves
do not explicitly consider risk
(i.e. during recessions, when jobs are scarce and trade-off between W and L may change)
Utility Functions in BF
In real life, risk evaluation is sometimes reference-dependent (e.g. depends on Wealth), meaning individuals sometimes exhibit
both risk-seeking and risk-averse behavior
, for example:
Double-Inflection Utility Function
e.g. buying lottery ticket
e.g. buying life insurance
Decision Theory
Theory on how to make ideal decisions for informed / mathematical / rational decision maker.

Decision Theory evolved over time:
initially, selecting
highest prob-weighted payoff
later, separated
expected value
expected utility
(later depends on individual preferences)
is defined as RV due to one outcome (measurable)
is unknowable outcomes (immeasurable)
subjective analysis
was added for situations where prob can't be objectively measured
Notion of
Bounded Rationality
Added assumption:
knowledge capacity limits

Relaxed assumptions:
perfrect information
fully rational decision making
consistent utility maximization
, instead, Individuals

("satisfy" + "suffice") - outcomes with sufficient satisfaction, but not optimal utility, are sufficient
Prospect Theory
Challenges to Decision Theory

According to TF, all investors are assumed to possess the same information and interpret it accurately and instantly, without bias, in evaluating investments and in making utility-maximizing decision.........this is UNREALISTIC
Takes Bounded Rationality further, by
relaxing key Utility Theory assumption:
risk aversion
, instead proposes
loss aversion
, (i.e. pain of -
100 > pleasure of +
100, note:
not in

Prospect Theory is suited for analyzing investment decisions and risk. It assumes
choices are made in 2 phases:


Kahneman and Tversky (1979)
Editing Phase
Evaluation Phase
People simplify number of choices before making final decision

Step 1:
Select reference point, then list and code proposals as gain or loss + assign probability to each outcome (i.e. E(R))

Step 2:
Combine probabilities for identical outcomes (E(R))

Step 3:
separate each outcome (E(R)) into "risk-free" and "risky" components

Step 4:
remove overlapping outcomes commmon to two proposals (i.e. net probabilities for same outcomes)

Step 5:
simplify small differences in probabiliities (i.e. round up or down, etc)

Step 6:
Detection of dominance
discard proposals that are clearly dominated (i.e. have lower max/min/avg)
Steps 4-6: If comparing 2 or more proposals
Steps 1-3: apply to individual proposals
Editing phase can give rise to
preference anomalies

One example is
Investors focus on one factor/outcome,but consiously/subconciously ignore others
As a result, different sequence of editing can lead to different decisions

Scenario 1
: 33% chance of $3000
: 20% chance of $5500

E(A) = $1000
E(B) = $1100
So, most people pick
Scenario 2
First Stage:
67% chance of $0
33% chance of Second Stage
Second Stage:
: 100% chance of $3000
: 60% chance of $5500

E(A) = $1000
E(B) = $1100
BUT now most people pick
People focus on
loss aversion
and behave as though they compute expected utility by placing values on alternatives for probability-weighted outcomes, and selecting alternative with the highest utility:
Value Function
reflects tendency of individuals to
overreact to small
Prob's and
underreact to large
explains why investors
in high-risk and low-risk investments, but
in medium-risk investmsnts

(1) value function is based on
, not level of wealth!

(2) it is S-shaped and asymmetric reflecting loss aversion
Most individuals are
are likely:

: sure loss $75
: 50/50 win $30 or lose $200 (E=-$85)

Most pick

Most individuals are
are likely:

: no bet
: 50/50 win $100 or lose $70 (E=$30)

Most pick

Markets & Portfolio Construction in TF
Efficient Market Hypthesis (

"Markets fully, accurately, and instanteneously incorporate all available information into market prices."

Two implications:
"Price is right" - prices reflect all available info
"No Free Lunch" - efficient prices reflect intrinsic value, so there are no excess, risk-adjusted returns after transction costs (i.e. no arbitrage)

Three types of efficiencies:
Weak-form efficient
- prices reflect past
=> implies
technical analysis
is ineffective
Semi-strong form efficient
- prices reflect
all public information
=> implies
fundamental analysis
is inffective
Strong-form efficient
- prices reflect
all information
(insider and public)
=> implies
no analysis
is effective
strong-form is not generally accepted
Tests of Weak-form Efficiency

Historical studies show zero serial correlation, which is consistent with weak-form, so price changes appear random (e.g. Fama, 1965)
Tests of Semi-strong form Efficiency

(1) Event studies
Some event studies show that stock splits are associated with abnormal rise in prices pre split, which is consistent with semi-strong (but not strong)

(2) Manager studies
Several studies of active management showed that
majority have alpha <0%,
also consistent
Challenges to EMH

Some studies found market anomalies contradictory to EMH.
Anomalies can be temporary or can persist due to limits to arbitrage activity or ability of investors to withrdraw funds from managers (i.e. manager must sell and forego arb if investor redeems)

Fundamental Anomalies
(violate both semi & strong forms)
some studies show that
value stocks
(low P/E, P/B, P/S and high E/P, B/P, div yield) outperform
growth stocks
some studies show abnormal returns for small-cap stocks
Technical Anomalies
(violate all three forms of EMH)
studies showed that
ST moving average
(1,2,5 days) moves above
LT moving average
(50,150,200 days) it signals a buy
studies showed that
price rise above resistance
also signals a buy
Calendar Anomalies
(violate all three forms of EMH)
stocks (esp. small-cap) have abnormally high returns in
, in
last 1 and first 4 days of each month
Behavioral Alternatives to EMH
If prices do not correctly reflect intrinsic value, then traditional approach to portfolio management is falwed.

No unified BF theory yet, but BF proposes 4 alternative behavioral models:

Consumption & Savings
Behavioral asset pricing
(BPT) Behavioral Portfolio Theory
(AMH) Adaptive markets hypothesis
TF assumes individuals save early in life to fund retirement later, however, this requires uncommon self-control.

Instead, Consumption & Savings proposes
behavioral life-cycle model
, in which individuals:
lack self-control
(usually only partially overcome)
exhibit mental accounting of wage by source
(less likely to spend from assets currently owned and PV of future income, more likely to spend from current income)
framing bais (e.g. if bonus is framed as "current income", more likely to spend; but if as "future income", les likely to spend)
TF asset pricing models (i.e. CAPM) assume prices determined through unbiased analysis of risk & return.

Behavioral asset pricing model adds a
sentiment premium
to discount rate, thus:

Required return on asset = risk-free rate
+ fundamental risk premium
sentiment premium

Sentiment premium can be estimated from dispersion of analysts' forecasts:
high dispersion => high sentiment premium
TF prescribes construction of well-diverified optimal portfolio.
In reality, many individuals construct portfolio by
, where each layer has different expected risk & return:
if high return key for goal => more $ to
high-risk layer
if low risk key for a goal => more $ to
low-risk layer
asset selection done by
risk layer
if investor risk-averse => higher # of assets in a
if investor has info advantage => more concentrated
if investor is loss-avers => larger cash position
As a result individuals tend to concentrate holdings
in low-risk and high-risk assets.

results in sub-optimal portfolio
vs TF optimal portfolio
AMH = EMH + bounded rationality + satisficing + evolution
(efficiency depends on competition/profits/flexibility of participants)
AMH assumes that success in the market is an
evoluitonary process
=> investors use heuristics until they don't work, then adjust. Investors satisfice, not maximize utility. Based on suffiient information, they aim for subgoals to reach goals, making not necessarily optimal decisions. As successful heuristics become widely adopted, they become reflected in market pricing, and no longer work. Markets evolve.

AMH leads to 5 conclusions:

(1) risk & return relationship is not stable => MRP changes
(2) active management can find arbitrage and add value
(3) no strategy should work all the time
(4) innovation essential to continued success
(5) survivors change & adapt
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