james montier 2

7/29/2019 James Montier 2

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Applied Behavioural Finance:

Insights into irrational minds and market


Insights into irrational minds and market

James Montier: Global Equity Strategy

Strictly Private & Confidential


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The brain is my second favourite organ

Woody Allen

The market can stay irrational, longer than you can stay solvent

JMK

There is nothing so dangerous as the pursuit of a rational investment policy in an irrational world

JMK

Economists are people who look at reality, and wonder whether it would work in theoryRonald Reagan


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2Global Strategy Unit

Taxonomy of biases

Taxonomy of biases

Cognitive dissonance

Regret theory

Hindsight bias

Confirmation bias

Self Attribution bias

Overconfidence

Overoptimism

Illusion of control

Illusion of knowledge

Self Deception

(Limits to learning)

Loss aversion/Prospect theory

Cue Competition

Availability bias

Anchoring/Salience

Catergorization

Framing

Representativeness

Ambiguity aversion

Self control

(Hyperbolic discounting)

Mood

Emotion/Affect

Heuristic Simplification

(Information processing errors)

Casacades

Herding

Contaigon

Imitation

Social Interaction

Biases


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The bias blind spot: Everyone else, not meThe bias blind spot: Everyone else, not me

Fundamenta

l

4

5

6

7

8

Selfserving

Selfinterest

Reactive

devaluation

attribution

error

Haloeffect

Biased

assimilation

Cognitive

dissonance

Average American Self


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Dual processing theories of thoughtDual processing theories of thought

System One/ X- system

Intuitive

System Two C- System

Reflective

Process Characteristics

Automatic Controlled

Effortless Effortful

Associative Deductive

Rapid, parallel Slow,serial

Process opaque Self aware

Skilled action Rule application

Content on which processes act

Affective Neutral

Causal propensities Statistics

Concrete, specific Abstract

Prototypes Sets


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Neuropsychology of dual processing (Liberman)Neuropsychology of dual processing (Liberman)

X X-system

X Amygdala

X Basal ganglia

X Lateral temporal cortex

X C-system

XAnterior cingulate cortex

X Prefrontal cortex

X Medial temporal lobe


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Kleins factors for NDM (X-system)Kleins factors for NDM (X-system)

X System X is more likely when:

X The problem is ill-structured & complex

X Information is incomplete, ambiguous and changing

X Goals are ill defined, shifting and competing

X Stress is high (time constraints and/or high stakes)

X Decisions involve multiple participants


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X-system can dominateX-system can dominate

2.5

2.6

2.7

2.8

2.9

3

3.1

1 2

Class B players

Masters

Blitz (6 sec per move) Standard (2.25 mins per move)


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AffectAffect

The rational model

X Perceptions -> attitudes

X I like this person because I think she is smart and honest

X I like this company because it is low risk and high return

The affect model

X Attitude -> perceptions

X Because like this person, I think she is smart and honest

X Because I like this company, it is low risk and high return


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Biased assimilation: When attitudes drive perceptionsBiased assimilation: When attitudes drive perceptions

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

Participants pro death penalty Participants anti death penalty

Studies supporting death penalty

Studies opposing death penalty


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Panda and affectPanda and affect

10

12

14

16

18

20

22

24

1 Panda 4 Panda

Dots

Pictures


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The dark side of emotionThe dark side of emotion

0

10

20

30

40

50

60

70

80

90

No invest Invest and lost Invest and won

Target patients Norm al players Patient controls


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No sign of learningNo sign of learning

40

45

50

5560

65

70

75

80

85

90

1st 5 2nd 5 3rd 5 4th 5

Target patients Normals Patient controls


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Self deception or perception is realitySelf deception or perception is reality


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Self deceptionSelf deception

Over-optimism

X People tend to exaggerate their own abilities

X Illusion of control

X Illusion of knowledge

Over-confidence

X People are surprised more often than they expect. Not well calibrated.

X Confidence intervals around a forecast which should yield 2% error,

actually get a 30-40% error


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OverconfidenceOverconfidence

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Weather men

Doctors


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Overconfidence and investmentOverconfidence and investment

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.55 0.65 0.75 0.85 0.95 1

Lay people

Professionals


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Overconfidence driven by the illusion of knowledgeOverconfidence driven by the illusion of knowledge

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

Previous

month's results

Other knowledge Intuition Guessing

Laypeople Professionals


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Does more information improve your accuracy?Does more information improve your accuracy?


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The walk down to beatable earnings:

average scale of forecast error at the earnings level US (%, 1986-2000)

The walk down to beatable earnings:

average scale of forecast error at the earnings level US (%, 1986-2000)

Source: DrKW Macro research and IBES

-5

0

5

10

15

20

-23 -22 -21 -20 -19 -18 -17 -16 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0

Months

Forec

astError


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Trading is hazardous to your wealthTrading is hazardous to your wealth

0

10

20

30

1 2 3 4 5

Net return Turnover

Low Turnover High turnover


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Should traders be women?Should traders be women?

0

20

40

60

80

100

All Women All Men SingleWomen

Single

Men-8

-6

-4

-2

0

All Women All Men Single

Women

Single

Men


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Bubble echoes in the laboratoryBubble echoes in the laboratory

Source: Ackert and Church

0

1

2

3

4

5

6

7

8

9

10

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Novices

Once experienced

Fundamental value

Mixture of twice experienced and novice players

(Ratio of 4/7)


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Keyness beauty contest and investment professionalsKeyness beauty contest and investment professionals

01

2

3

4

5

6

7

8

9

10

0 510

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Over 1000 players

Average number picked 262/3rds: 17

Average level of thinking 1.6 steps


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Self deceptionSelf deception

E 4 K 7


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Self attribution biasSelf attribution bias

X Good outcomes are a testament to your skill, bad outcomes are sheer bad

luck.

X How often do you say thats just a blip?


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Hindsight biasHindsight bias

X It is a common observation that events in the past appear simple,

comprehensible, and predictable in comparison to events in the future.Everyone has had the experience of believing that they knew all along the

outcome of a football game, a political election or a business investment. The

hindsight bias is the tendency for people with outcome knowledge to believe

falsely that they would have predicted the reported outcome of an event. After

learning of the occurrence of an event, people tend to exaggerate the extent towhich they had foreseen the likelihood of its occurrence.


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II. Heuristic Simplification

Or

There is no such thing as context free decision making

Psychological FoundationsPsychological Foundations


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Heuristic SimplificationHeuristic Simplification

X Conservatism Bias

X Hard to give up a view once it has formed. Leads to:

XAnchoring and slow adjustment

X Depends upon saliency of the anchor

X i.e. analysts will change their views from their forecasts slowly


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Analysts lag realityAnalysts lag reality

-8

-6

-4

-2

0

2

4

6

8

10

12

Jan

-86

Jan

-87

Jan

-88

Jan

-89

Jan

-90

Jan

-91

Jan

-92

Jan

-93

Jan

-94

Jan

-95

Jan

-96

Jan

-97

Jan

-98

Jan

-99

Jan

-00

Jan

-01

Jan

-02

Jan

-03

Earnings

Forecasts


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The Fed modelThe Fed model

Source: Thomson Financial Datastream

85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 020.60

0.70

0.80

0.90

1.00

1.10

1.20

1.30

1.40

1.50

1.60

1.70

0.60

0.70

0.80

0.90

1.00

1.10

1.20

1.30

1.40

1.50

1.60

1.70


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0.0

0.5

1.0

1.5

2.0

2.5

3.0

Apr-53

Apr-56

Apr-59

Apr-62

Apr-65

Apr-68

Apr-71

Apr-74

Apr-77

Apr-80

Apr-83

Apr-86

Apr-89

Apr-92

Apr-95

Apr-98

Apr-01

Apr-04

Equities vs. bonds in the US: the Fed model since the 1950sEquities vs. bonds in the US: the Fed model since the 1950s

Source: DrKW Macro research


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Simple maths leads to anchoringSimple maths leads to anchoring

X 8*7*6*5*4*3*2*1 = median answer 2250

X 1*2*3*4*5*6*7*8 = median answer 512

X Actual answer = 40,320


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Estate agents and anchoringEstate agents and anchoring

80,000

90,000

100,000

110,000

120,000

130,000

140,000

150,000

160,000

1 2

Given Appraisal valueListing Price Lowest acceptable offer


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Anchoring and valuationAnchoring and valuation

0

10

20

30

40

50

60

Cordless

mouse

Cordless

keyboard

Average

Wine

Rare Wine Design

book

Belgian

Chocolates

0

0.5

1

1.5

2

2.5

3

3.5

4

Low SS No.

High SS No.

Ratio


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Cheap? Surely some mistake - USCheap? Surely some mistake - US

Various valuation measures (x)

Current level 1997-200 Long run*

Trailing reported PE 21.1 29.0 14.0

Operating PE 17.5 22.5 14.9

Forward operating PE 15.6 19.7 12.5

PB 3.0 4.0 2.4

PC 13.0 14.9 9.2

Graham and Dodd PE 27.5 37.0 16.4Hussman PE 19.3 23.5 11.0

Trend PE 22.0 29.0 13.9

Source: DrKW Macro research* the term long run refers to the longest run of data we have which varies from starting in the 1870s to starting in the mid 1980s. All long

run measures end at the end of 1996, effectively stripping out the bubble years.


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Psychological foundationsPsychological foundations

X Linda is 31, single, outspoken and

very bright. She majored in

philosophy. As a student she wasdeeply concerned with issues

surrounding equality and

discrimination.

X Is it more likely that Linda is

X Works in a bank

X Works in a bank and is active in

the feminist movement


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Psychological FoundationsPsychological Foundations

Representativeness Heuristic

XAka law of small numbers belief that random samples of a population

will resemble each other and the population more closely than statistical

sampling theory would predict.

X Which is more likely HTHTTH or HHHTTT?


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Earnings growth as representativenessEarnings growth as representativeness

Source: Montier, & Chan et al

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

Q1 Q2 Q3 Q4 Q5

Trailing 5 year Forward 5 year

Actual 1 Actual 3

Actual 5

Source: Montier, and Chan et al


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Great stories Great investmentsGreat stories Great investments

0

2

4

6

8

10

12

14

16

18

Glamour (1) Glamour (2) Value (9) Value (10)


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Under-reaction and Over-reactionUnder-reaction and Over-reaction

X Information is judged in two dimensions strength and weight

X Letter of reference judged by strength i.e. number of appealing traits

X Weight is neglected. i.e. who wrote it


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Over-reaction and Under-reaction : Information analysisOver-reaction and Under-reaction : Information analysis

Over-

reaction

High

Under-

reaction

Low

HighLow

Weight

Strength


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Analysis of over-reaction and under-reactionAnalysis of over-reaction and under-reaction

X Dividend omissions, initiations

X Earnings surprises

X Analyst recommendations

X Z-scores

X Buybacks on value stocks

X Goodwill write-offs

X Valuations

X IPOs, SEOs

X High earnings growth

X Cap ex.

X Buybacks on growth stocks

X Quarterly earnings announcements

Under-reaction Over-reaction

f

f


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Bias of JudgementBias of Judgement

X Availability Bias

X Which is a more likely cause of death in the US being killed by a

lightening strike or as a result of a shark attack?

X Shark attacks receive more publicity, they are easier to imagine (thanks to

Jaws). However, the chance of dying from a lightening strike are 30x

greater than chances of being killed by a shark.

N F i

N F i


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Narrow FramingNarrow Framing

X Context sensitivity. Aka frame

dependence or mental accounting.

X We cant see through how things are

actually framed.

X Separate funds for separate

purposes holiday money, house

keeping

?

?


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When is a buyback not a buy back?

announced, actual and net share buy-backs in the US

When is a buyback not a buy back?

announced, actual and net share buy-backs in the US


-50,000

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

Announced

Completed

Net

R h & th i i t

R h & th i i t


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Repurchases & their impact:

dividend, repurchase & total yield for the S&P500 (%)

Repurchases & their impact:

dividend, repurchase & total yield for the S&P500 (%)


-1.00

0.00

1.00

2.00

3.00

4.00

5.00

6.00

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

Total yield

Dividend yield

Net repurchase y ield

Prospect Theory

Prospect Theory


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Prospect TheoryProspect Theory

X People value changes not states.

Rational man tries to maximise the

utility of wealth.

X Real people worry far more about

gains and losses than levels.

-12

-10

-8

-6

-4

-2

0

2

4

-20 -15 -10 -5 0 5 10 15 20

Stock broker Sample

Stock broker Sample


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Stock broker SampleStock broker Sample

0

5

10

15

20

25

50100

101

110

150

201

320

500

1000

100

000

Prospect theory

Prospect theory


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Prospect theoryProspect theory

Leads to

Endowment effect

Status quo bias

Disposition effect

Endowment effect/Status quo bias

Endowment effect/Status quo bias


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Endowment effect/Status quo biasEndowment effect/Status quo bias

0

1

2

3

4

56

7

8

1 2 3

Sellers Choosers Buyers

US mutual fund managers and the disposition effect (1980-2002)

US mutual fund managers and the disposition effect (1980-2002)


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US mutual fund managers and the disposition effect (1980 2002)US mutual fund managers and the disposition effect (1980 2002)

Source: Frazzini (2004)

0

5

10

15

20

25

Low return 2 3 4 High

return

All

Proportion of losses realized

Proportion of gains realized

Top tips for better decision making

Top tips for better decision making


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Top tips for better decision makingTop tips for better decision making

X This applies to me, you and everyone else

X You know less than you think you do

X Be less certain in your views, aim for timid forecast and bold choices

X Dont get hung up on one technique tool, approach or view flexibility and

pragmatism are the order of the day

X Listen to those who dont agree with you

Top tips for better decisions



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Top tips for better decisionsTop tips for better decisions

X You didnt know it all along, you just think you did

X Forget relative valuation, forget market prices, work out what the stock is worth

(Use reverse DCFs)

X Dont take information at face value, think carefully about how it was presented

to you

X Dont confuse good firms with good investments, or good earnings growth with

good returns




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Top tips for better decisionsTop tips for better decisions

X Vivid, easy to recall events are less likely than you think they are, subtle

causes are underestimated

X Try to focus on facts, not stories

X Sell your losers and ride your winners

Beating the biases

Beating the biases


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gg

X Being aware of the biases is not enough. It is just an important first step.

X Need to create a framework that incorporates mental best practice. Easier said

than done. Mental bad habits are persistent.

X The good news, we continue to create new brain cells throughout our lives.

St i tl P i t & C fid ti l


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Are two heads better than one?

The psychology of group decisions


Are two heads better than one?

The psychology of group decisions

James Montier: Global Equity Strategy

Strictly Private & Confidential

Madness is a rare thing in individuals but in groups...it is the rule


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Friedrich Nietzsche

To associate with other like-minded people in small, purposeful groups is for the great majority of

men and women a source of profound psychological satisfaction..

Aldous Huxley

Deliver us from committees

Robert Frost

Committees are groups of people who keep minutes but waste hours

Berle Milton

A committee is an animal with four back legs

John le Carre

A committee is a group of the unwilling, chosen from the unfit, to do the unnecessary

Unknown

Types of groups

Types of groups


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Statistical groups = large number of people asked for an answer, take the mean.

Deliberative groups = discussion is necessary

Evidence suggests that statistical groups outperform deliberative groups and

individuals

E.g. when judging the number of beans in a jar, the group average is almost alwaysbetter than the vast majority of the individual members. In one such experiment, a

group of 56 students was asked about a jar containing 850 beans; the group estimate

was 871, a better guess than all but one of the students

Statistical groups

Statistical groups


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Only work when:

People are unaffected by others decisions (errors are uncorrelated)

Probability of being correct must be independent of the probability of

everyone else being correct

The participants must be unaffected by their own vote possibly beingdecisive

When participants have some idea of the answer.

Anchors are avoided

Deliberative groups

Deliberative groups


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Such groups seem to amplify:

Representativeness

Framing

Overconfidence (simple repetition of views leads to people having greater

confidence)

Anchoring

Availability

The establishment of norms (Sherif 1936)

The establishment of norms (Sherif 1936)


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0

1

2

3

4

5

6

7

8

Alone Session 1 Session 2 Session 3

1

23

Conformity (Asch 1955)

Conformity (Asch 1955)


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On 12 of the 18 rounds, confederates unanimously agreed on a wrong answer

of participants agreed with the confederates in at least one round. Halfagreed in 6 or more rounds. Only 25% resisted in all rounds!

Does group size matter? (% conforming to wrong answers)

Does group size matter? (% conforming to wrong answers)


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0

5

10

15

20

25

30

35

1 2 3 4 15

Herding when uncertain Baron et al

Herding when uncertain Baron et al


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0

0.5

1

1.5

2

2.5

3

3.5

4

Unimportant Important

Low uncertainity

High uncertainty

Sharing information (Stasser et al 1989)

Sharing information (Stasser et al 1989)


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0

10

20

30

40

50

60

70

80

Unstructured Structured

Shared

Unshared

Why are we so bad at sharing information?

Why are we so bad at sharing information?


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Shared information is more likely to be discussed and repeated and this will

influence the individuals in the group, and hence influence the groups eventual

outcome.

Social pressure

Cascades

Social pressure : Those who conform are rewarded (Wittenbaum et al 1999)

Social pressure : Those who conform are rewarded (Wittenbaum et al 1999)


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5

5.2

5.4

5.6

5.8

6

6.2

6.4

6.6

6.8

7

Shared Unshared

Self

Others

Cascades

Cascades


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Private

signal

a a b b b b

Source: Anderson and Holt (2004)

Cascade creation: Actual pot used B

Player 1 2 3 4 5 6

Decision A A A A A A

Group polarisation

Group polarisation


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Group polarization is the tendency for members of a group to end up in a more

extreme position in line with their original beliefs after talking to one another.

The increased confidence in view mentioned earlier, begins to create feedbackinto the extremity of view, generally creating a loop of increased confidence in

more and more extreme views

Groupthink

Groupthink


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A tendency to examine too few alternatives

A lack of critical assessment on each others ideas

A lack of contingency plans

Poor decisions are often rationalized

Illusion of group invulnerability and shared morality

True feelings and beliefs are suppressed

Illusion of unanimity is maintained

Mind guards are appointed to protect the group from negative information

Solutions

Solutions


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Secret ballots

Devils advocates

Authentic dissent

Respect for other group members

Beware of authority Milgram experiments

Beware of authority Milgram experiments


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Banduras driving forces turning good people bad

Banduras driving forces turning good people bad


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Moral justification

Euphemistic labelling

Advantageous comparison

Displacement of responsibility

Diffusion of responsibility

Disregard or distortion of consequences

Dehumanisation


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