Fair Prices - PowerPoint Presentation

Slide1

Fair PricesAdverse SelectionMoral HazardContract Design : Costly State Verification

Jeffrey H. Nilsen

http://video.ft.com/4051985681001/Impact-of-negative-yields/editorschoice

Slide2

Share Return and “Fair Price”Common stock promises share of firm’s future profits (residual since creditors repaid first)

1

st

term: expected dividend yield

2

nd

term: expected capital gain

At t0: uncertain dividend & sale P

Rearrange equation for simplest estimate of security’s “

fair price”

Use return on similar shares as discount rate (required rate of return) indicating share’s risk

Expected return for holding equity for 1 period

NB: similar to coupon bond held for 1 periodSlide3

Gordon Dividend Growth Model estimates “fair” share P

True value of share is PV (expected future cash flows)

Assume constant dividend growth (at rate g):

Next slide manipulates eqn (*) to derive Gordon’s model

(as n gets large, influence

of P

n

evaporates)Slide4

Gordon (equation manipulation)

Multiply

both

sides by

eqn (**) - (*)

=>

“Gordon’s Model”

Assume r > g so

last term disappears

SimplifySlide5

Gordon Model’s Macro ImplicationMonetary Policy Easing (rise in MS): P0 rises for 2 reasons:req

falls (investors earn less on bonds)g rises as GDP rises If recession (slower GDP growth), g falls => P0 fallsShiller uses Gordon model to argue share prices are not rational since are more volatile than their (Gordon-determined) fundamentals

(assume r > g)Slide6

Direct Finance Subject to Adverse Selection (Lemons) Saver can’t evaluate asset quality, will pay only avg. P for asset

Firm selling good asset knows savers pay only avg. market P Won’t sell its good asset on market since asset undervalued=> few good assets in market, so market quality declines and few transactionsSo few firms with good assets issue shares & bonds (direct finance is not frequently utilized)Slide7

Mitigating Adverse Selectionin Direct Finance: Provide Info ?Free-riding & mimicking => info under-providedS&P e.g. charges for info on issuing firms: but savers pass it on to friends who “free ride”. S&P can’t profit from publishing info

If gov’t requires issuing firms to publish info, bad firms will copy info to look good (e.g. Enron)Borrowers always better informed than saversBank’s specialty to find good borrowers. Traditionally kept loan on balance sheet so no saver could free ride on bank’s infoSlide8

Mitigating Adverse Selectionin Direct Finance: Other Mechanisms?Collateral is something of value given to bank if borrower

defaultsBorrower’s NW => borrower also suffers loss if project fails => aligns her incentives with those of lenderSlide9

Moral Hazard in Equity (Principal – Agent problem)Managers (agents) are hired by owners (principals) but may not act to maximize owner’s profits.E.g. managers exert low effort contributing to low profits suffered by owner

Extreme case e.g. Enron: corrupt managers receive lavish pay, “cooked the books” to avoid detectionSlide10

Principal – Agent ProblemWith Costly Monitoring (MON)Owner or lender pays costs (attention & hired expertise) to MON borrowerLender designs loan contract to cover cost of MON:

Bank takes share of residual profits, entrepreneur can easily cheat by reporting smaller amount, so bank must always MONBank takes fixed payment, MON only when don’t receive it If MON costs high gives reason for “standard debt contract” SDC) to be optimal contract Known in economic literature as “costly state verification”Slide11

Townsend (1979):Costly State Verification (CSV) ModelRisk-neutral entrepreneur has project but no funds Costlessly observes project outcomeProject outcome depends on SONOnly resources are from project (can’t give collateral)

Risk-neutral bank (lends)Can’t directly observe outcome Verify entrepreneur’s claimed SON by paying fixed cost γLends if E(return)= I (cost of funds)First choose which SON to MON & which SON to NOT

Eichenberger & Harper 6.2Slide12

Bank Wants Contract that’s Incentive Compatible (IC)An IC contract doesn’t give borrower incentive to lie about SON (bank learns SON from borrower’s claim)Z is return paid to bank

z

NOT

= R (a constant); otherwise entrepreneur would always claim lowest repayment SON

z

MON

<

z

NOT

: IF borrower pays bank more when MON, borrower would always claim NOTSlide13

Assign to MON state if project return < bank’s cost of funds (this is approximately correct)If project fails, entrepreneur must give whatever remains of project to bank (has no other resources)Example PreliminariesSlide14

MON costs are passed from lender to entrepreneur !!

E(project return

) – (repay in MON) – (repay in NOT)

SON

L

M

H

Probability

0.25

0.50

0.25

f(SON)

½

2

3

I = 1

Mon Cost

Bank’s cost

of funds

Project outcomes in all SON

Borrower gives bank project outcome if can’t pay promised R

Repay

bank if project succeedsSlide15

The Bank’s Profits

E(return in NOT) + (repay in MON) - (MON costs)

SON

A

B

C

Probability

.25

.50

.25

f(s)

½

2

3

=

0.75R+1/16

I = 1

S

pecific MON costs

c

ut bank profitsSlide16

The Bank’s Participation Constraint (PC)

E(return) + (repaid in MON) = cost of funds + E(MON cost)

SON

A

B

C

Probability

.25

.50

.25

f(s)

½

2

3

PC determines value for R !!

> I

Motivate entrepreneur’s high finance costs:

t

o compensate bank for risk of bad SON + MON costsSlide17

Assign Bank MON costs but it passes them on to Entrepreneur

So Entrepreneur pays bank’s cost of funds + MON costsSlide18

Optimal ContractR > I => must compensate bank for SON where f(s) < I(with higher γ, need higher

R)

MON

NOT

(constant

R

)

I is cost of funds

z

return to bank Slide19

Lessons from Costly State Verification (CSV)If Mon costs zero, R > I compensates bank only for SON when outcome lower than fixed paymentIf MON costs > 0, asymmetric info raises cost of funds to entrepreneur, dampens investment

 SDC is real-world loan contract: bank asks for R, if it receives less, it declares entrepreneur bankrupt to recover as much as possibleSlide20

Moral Hazard if DebtIf lender buys debt, riskier project tempts entrepreneurEntrepreneur likes: earns more if win Lender dislikes: less likely to be repaid

Example $10 loan:

If succeed

If fail

Entrepreneur expects

Probability of non-payment to lender

Planned Project

90%

$20

10%

$0

Risky Project

50%

$50

50%

$0

Expected value = prob win * (amt win) + prob lose * (amt lose)Slide21

Moral Hazard if DebtIf a lender buys debt, riskier project can tempt entrepreneurEntrepreneur likes: earns more if win Lender dislikes: less likely to be repaid

Example $10 loan:

If succeed

If fail

Entrepreneur expects

Probability of non-payment to lender

Planned Project

90%

$20

10%

$0

$18

10%

Risky Project

50%

$50

50%

$0

$25

50%

Expected value = prob win * (amt win) + prob lose * (amt lose)Slide22

Solving Moral Hazard in DebtInclude Restrictive Covenant in Contract to ensure entrepreneur uses funds in specific projectNW or Collateral aligns borrower’s incentives with lender’s

Lender seizes NW or collateral if borrower defaultsBank specializes in loan monitoring and enforcement