Prospect Theory

Question 1

What is the expected utility of a prospect in EUT given by?

Answer 1

EU=EpU(x)

Asset integration is assumed - you add initial income to payoffs

Question 2

What is the expected utility of a prospect in PT given by?

Answer 2

EU=Ew(p)v(x-r)
where w(p) is the weighted probability (mental distortions of p)
v(.) is the value function
r is reference level (given utility depends on context)

Question 3

What is the coding stage of editing?

Answer 3

Assets are perceived as gains or losses relative to a relative to a reference level (usually current asset position).
Take an individual with income £2 facing the prospect (-1,0.5;1,0.5) under EUT the outcomes are U(1) and U(3), Under PT the outcomes are V(-1) and V(1)

Question 4

What is the combination stage of editing?

Answer 4

Prospects are simplified by combining probabilities associated with identical outcomes

Question 5

What is the segregation stage of editing?

Answer 5

Some prospects contain a risky component that is segregated from a riskless component

Question 6

What is the cancellation stage of editing?

Answer 6

The discarding of components that are shared by the offered prospects (2 aspects of the gamble that are transparently identical where you can easily detect the common element and psychologically eliminate it).

Question 7

What are the properties of the PT value function (see notes for more detail)

Answer 7

Loss Aversion - losses loom larger that gains (value function steeper for losses)

Diminishing sensitivity - MU falls as you move further away from the reference point (become less and less sensitive to outcomes)

Reference point - neutral point on utility scale, outcomes judged as gains and losses based on this reference point

Question 8

What are the properties of the weighting function in PT? (see notes for more details)

Answer 8

w(0)=0 and w(1)=1 - no distortions of probabilities at extreme values
Not defined close to 0 & 1
Overweighting for small p and underweighting for large p

Question 9

What is subcertainty?

Answer 9

Probabilities must sum to one, but decision weights must sum to less than one
w(p)+w(1-p)<1
Allias’ paradox implies subcertainty

Question 10

How is reflection effect explained by PT

Answer 10

Reflection effect shows that we can be risk averse for gains and risk loving for losses.

Question 11

How is the isolation effect explained by PT?

Answer 11

It is explained by the segregation effect of editing phase.

If you can win £200 or £300, gambler is definitely getting £200 and therefore isolates this gain from the gamble

Question 12

How is the ESE explained by PT?

Answer 12

The full version of PT is unable to account for ESE.
This is because 2 events with payoff b would be combines under the combination operation of editing phase.
Can only be explained with stripped down PT (see notes)