unnumbered figures forprospect theoryfor risk and · web viewunnumbered figures forprospect...

Unnumbered Figures forProspect Theory

for Risk and Ambiguity

by Peter P. Wakker (2010);provided on internet July 2013 (with permission of CUP)

All unnumbered figures were made using only the drawing facilities of MS-Word of 2009. There are no curves.

p. 31:

UNNUMBERED FIGURE 1.6.1

z(s)

y(s)x(s)

s

payoff next month

2.50s

payoff next month

2.50s

payoff next month

2.50

2

p. 47:


12

14

20

2/61/6

3/6

3

p. 47:


101

4

p. 57:


1.5

½

½

5

p. 58:


Elucidation: I left the period to the right of the figure. In my text the figure is part of a sentence and, then, assuming that you can let it be that too, the period at the end of the sentence should be there.

.m

Mq

1qm

Mp

1p

6

p. 63:


.~C

y

1C

x

1

x ~ y implies

7

p. 64:


.x y implies

1 C

y

C

x

1

8

p. 82:


–/2

½

½

9

p. 113:


ELUCIDATION: (4.7.1) is an equation nr. that is part of the equation nrs. in the text.

(4.7.1) ´ =

&

& Ff ~ Fg Ex ~ Ey

& ´Ff ~ FgEx ~ Ey

10

p. 155:


020

406080

11

p. 158:


20

30

80

1/3

1/21/6

12

p. 159:


rank of more than 0

rank of more than 20

rank of more than 30

U(80) + [( + ) ] U(30) + [( + + ) ( + )] U(20)

1

13

p. 159:


....

pn

p1...

xn

x1

14

p. 160:


rank of xj (0 for j = 1)rank of xj+1

j=1;n [(pj + ... + p1) (pj1 + ... + p1)]U(xj).

15

p. 165:


Rewrite

as 20

30

70

⅛

½

⅜

30

20

70

½

⅛

⅜

16

p. 166:


10

80

50

0.5

0.2

0.3

17

p. 166:


10

50

80

0.5

0.3

0.2

18

p. 167:


601/4

20

40

80

1/2

1/12

1/6

(b)(a)

96449

1/21/3

1/6

19

p. 167:


20

8030

1/3

1/6

1/2

20

p. 168:


0

8125

¼

¼

½

21

p. 176:


0.87 25K

0.06s 0.07 25K

25K

0.87 25K

0.06r 0.07 0

75K

0.87 0

0.06s 0.07 25K

25K

0.87 0

0.06r 0.07 0

75K

&

22

p. 177:


w

10 0.93

23

p. 180:


0

106106

1 106

24

p. 197:


FIG. b

y3 = 9

y2 = 16

y1 = 25

q3 = 0.4

q1 = 0.1

q2 = 0.5

x4 = 9

x3 = 16

x2 = 16x1 = 25

p4 = 0.4

p3 = 0.3

p2 = 0.2p1 = 0.1

FIG. a

25

Unnumbered Figures for Elaborations of Exercises

26

p. 408:

UNNUMBERED FIGURE J.3.2.1

FIG. cFIG. bFIG. a

.

.

.

xn

x

n1

x2

pn

p

n1

p2

x1p1

)(

xn1,

xn

.

.

.x

n2

x2

pn1 + pn

p

n2

p2

x1p1

x

n1xn

.

.

.x

n2

x2

pn1 + pn

p

n2

p2

x1p1

27

p. 410:


,+0.05

+2.5 106

0.052.5 106

(2106, 2106) <

(106 , 106) (2.5 106 , 0.05 )

(106 , 106) (0.05 , 2.5 106)

28

p. 410:


$45

$65

$45

utilityoutcome

0

40

$ 0

$ 30

10

31

$ 5

$ 20

18$ 10

EU = 20.5

EU = 20

EU = 18

0 exercised tomorrow


½

½

0 exercised today

1 exercised today

today

$65



½

½

2 exercised today

29

p. 425:


10 106

10 106

0.01

0.89 00.10

0

50 106

0.01

0.89 00.10 and

10 106

10 106

0.01

0.8910 106

0.10

0

50 106

0.01

0.8910 106

0.10

Figs. 2.4.1g and h violate the sure-thing principle for risk.

30

p. 427:


94964

1/21/6

1/3

31

p. 432:


z

y

1P(y U1(t))Outcomes with utility < t

Outcomes with utility tP(y U1(t))

x

1P(x U1(t))Outcomes with utility < t

Outcomes with utility tP(x U1(t))

1

32

p. 435:

UNNUMBERED FIGURE J.7.2.2a

the ⅓ probability mass allocated to the highest outcomes receives this decision weight.

the ⅓ probability mass allocated to the middle outcomes receives this decision weight.

the ⅓ probability mass allocated to the lowest outcomes receives this decision weight.

⅔⅓

33

p. 436:

UNNUMBERED FIGURE J.7.2.2b

the 1/4 probability mass allocated to the highest outcomes receives this decision weight.

the 1/4 probability mass allocated to the lowest outcomes receives this decision weight.

1/4 3/4

34

p. 451:


FIGURE. Various components contributing to risk premium

Separate additions to risk premiumTheoryCE

1.06 istotal risk premium under RDU(U,W)

0.47 is additional risk premium due to w

RDU (U,W)16.44

0

16.94

0

EV17.41

0

EU (U)

0.50 is additional risk premium due to unknown probability

17.50

0RDU (U,w)

0.09 is risk premium due to U

35

pp. 456-460: ALL FIGURES FROM CHAPTER K

36

CH.5

5.5.math intuition

5.4. intuition

5.3.stoch. dom.

5.2.old way

5.1.probabilistic sensitivity

5.6.calculating

3.2.risk aversion

9.2.PT defined

8.4.loss aversion

9.1.symmetry about 0

7.6.bad-news

App.A

CH.3

2.5.EU

3.1.health applica-tion

3.2.risk aversion

3.6.data fit EU

3.5.para-metric U

3.4.indexes

3.3.appli-cations risk aversion

3.8.car-dinal U

3.7.multi-attribute

1.2.basicproperties

1.1.basic definitions

App.A

1.10.Lit-erature

CH. 1

1.8.general nature of behavioral foundations

1.7.dis-cussion

1.9.kinds of preference conditions

1.6.foun-dation EV

1.5.no book

1.4.datafit

1.3.EV

7.10.indexes

7.9.discuss inv-S

App.A

CH.7

7.3.datafit

7.2.parametric w

6.3 .pessimism

7.12.cavex7.11.binary RDU

7.8.insty. region

7.7.inverse-S7.6.bad-news7.5.alternative test

7.1.two components

7.4.testing properties

CH. 4

App.A

3.7. mul-tiat-tri-bute

4.12.Allais

4.11.statistical analysis

4.7.dis-cussion

4.1. 15 ques- tions

3.2.risk aversion

4.10.data-fit EU

4.3.test

4.5.TO

4.2EU

4.9.2.behav.F.

4.6.found.EU

4.9.1.single stage

4.8.further implications

4.4.dec. process

4.9.3.A&A

1.3.EV

2.4.deci-sion trees

2.2 .decision under risk

2.5.EU

CH.2

2.8.basic inconsis-tencies

2.7.inde-pendence

2.6.foundation EU

2.3.risk unc; continued

2.1 risk uncertainty

8.6. Rabin's paradox

CH.8

8.3.initial wealth

3.2.risk aversion

8.1.choice paradox

8.8.pro-blems

8.7.future directions

8.5.fundamen-tal breakaway

8.4.loss aversion

8.2.real culprit

3.2.risk aversion

6.3.pessimism

6.2.ranks discussed

CH.66.9.integral6.8.dw/dp6.7.collapse

4.3 mea-suring U

6.4.RDUEU6.5.1.measuring U

4.6.foun-dation EU

6.1. RDU defined

6.5.2.foundation RDU

6.5.5.implications6.6.RDUEU

6.5.4.measure w6.5.3.example

6.3 pessimism

4.2EU

10.3.1. Ellsberg

10.2.RDU uncertainty

10.1.prob. soph

37

AppA

CH.11


11.11.belief11.10.monot.11.9.discuss

11.8.index amb.att.

11.7.index amb.av.

11.6.literature11.5.MP

11.4.CORE11.3.examples11.2.rank amb.

11.1.Ellsberg

7.2.w.func-tions

10.3.1. Ellsberg

7.2 par.w &App.A 11.8.indexes amb.

10.7.hybrid10.5.3.foundation RDU

12.7.indexes amb.12.6.violations

CH.1210.12.comonotonic10.10.integral

12.5.loss av. amb. 12.4.hybrid

8.4.loss av. def.

12.3.4.foundation PT

12.8.theory-issues

Ch.8.PTRDU

10.5.2.U for RDU12.3.2.measuring U

9.2.PT defined 10.2.RDU uncertainty12.1.PT defined

12.2.PTRDU 10.4&11.2.RDUEU

12.3.1.sign-conditions 10.5.1.rank conditions

9.4.2.U for PT12.3.3.measuring

38

App.G Infinite dimensions

APPENDICES

4.2.EU

4.6.founda-tion EU


6.1.RDU defined

1.1.basicdefinitions

App.I other booksApp.H measure theory

App.E bisymmetry

App.D other fieldsApp.C dynamic

App.B revealed pref.App.A distance measure

App.F nonmonotonic RDU

1.2.basicproperties

2.1.DURDUU


FIGURE K.1. The reading required to under-stand the definition of PT for uncertainty in §12.1

7.6.bad-news

12.1.PT defined

9.2.PT defined

8.4.loss aversion

4.2.EU

2.4.deci-sion trees

2.2.decision under risk

2.5.EU

1.2.basic properties

1.3.EV

3.2.risk aversion

6.3.pessimism

6.1.RDU for risk

10.2.RDU for uncertainty

10.1.prob.soph.

2.1.DURDUU

FIGURE K.2. The reading required to under-stand the pragmatic indexes of ambiguity attitudes based on prospect theory

App.A12.1.PT defined

12.7.PT’s indexes of ambiguity


2.4.deci-sion trees

2.2.decision under risk

2.5.EU

1.2.basic properties

1.3.EV

3.2.risk aversion

7.2.parametric w7.6.bad-news8.4.loss aversion

11.1.Ellsberg

4.2.EU6.1.RDU defined

10.1.prob.soph


9.2.PT defined

6.3.pessimism

11.7.amb.av.11.8.index amb.att.

39

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