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# CFA 2015 Level 3 - SS 3 Behavioral Finance

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## Denis C

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#### Transcript of CFA 2015 Level 3 - SS 3 Behavioral Finance

The Behavioral Finance Perspective

CFA 2015 Level 3
SS 3:
Behavioral
Finance

The Behavioral Biases of Individuals

Behavioral Finance and Investment Process

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

(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
:
Completeness:
Transitivity:
Independence:
Continuity:
individuals know their preferences
if
given choices D,E
=>
preference can be one of D>E, D<E, or D=E
individuals consistently apply rankings
if
D>E and F>D
=>
F>E
if
D, F mutually exclusive; D>F; and J additive
=>
D+x(J)>F+x(J)
continuous utility indifference curves
if
F>D>E
=>
exists a and b,
such that aF+bE=D
Bayes' formla:
where:

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
risk-averse
, 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
Assume:
unlimited perfect knowledge

utility maximization

fully rational decision making

risk-aversion
capacity limitations
on knowledge

satsicficing

conitive limits
on decision making

reference dependence and
cognitive errors
(
Prospect theory only
)
Rational decision making according to Utility Theory
Efficient markets
vs
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:
PV(Budget)
Utility
= "level of relative
satisfaction
received from the consumption of goods and services"

Utility Theory assumes "
diminishing marginal return
", meaning:
(1)
utility function is concave
since REM is risk-averse, and;
(2)
indifference curves are convex
due to diminishing marginal return of substitution
UTILITY THEORY (TF)
Challenges to TF and REM

lack of information
and flaws in decision-making process

personal
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
Side-note:
Indifference curve
shows points at which REM would be equally satisfied between two substitutes
Convex
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.)
Concave
shape means that less utility is gained from each additional unit of Wealth
(1)
(2)
Challenges to Utility Theory and Indifference Curves

individuals often
unable to quantify

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:
Friedman-Savage,
Double-Inflection Utility Function
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
from
expected utility
(later depends on individual preferences)
risk
is defined as RV due to one outcome (measurable)
uncertainty
is unknowable outcomes (immeasurable)
subjective analysis
was added for situations where prob can't be objectively measured
Notion of
Bounded Rationality
knowledge capacity limits

Relaxed assumptions:
perfrect information
fully rational decision making
consistent utility maximization
satisfice

("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
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:

Editing
phase

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

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

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

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

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

Step 5:
Simplification
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
ISOLATION EFFECT
anomaly:
Investors focus on one factor/outcome,but consiously/subconciously ignore others
As a result, different sequence of editing can lead to different decisions
Example:

Scenario 1
A
: 33% chance of \$3000
B
: 20% chance of \$5500

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

E(A) = \$1000
E(B) = \$1100
BUT now most people pick
A
!!!
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
Prob's
explains why investors
over-concentrate
in high-risk and low-risk investments, but
under-concentrate
in medium-risk investmsnts
NOTE:

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

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

e.g.:
Between
A
: sure loss \$75
B
: 50/50 win \$30 or lose \$200 (E=-\$85)

Most pick
B

Most individuals are
risk-averse
when
gains
are likely:

e.g.:
Between
A
: no bet
B
: 50/50 win \$100 or lose \$70 (E=\$30)

Most pick
A

Markets & Portfolio Construction in TF
Efficient Market Hypthesis (
EMH
):

"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
prices
and
volume
data
=> 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
Calendar Anomalies
(violate all three forms of EMH)
stocks (esp. small-cap) have abnormally high returns in
Jan
, 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
TF assumes individuals save early in life to fund retirement later, however, this requires uncommon self-control.

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
to discount rate, thus:

Required return on asset = risk-free rate
+

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
layers
, 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
layer
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.

(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