MN50324: Corporate Finance 2011/12:
1. Investment flexibility, Decision trees, Real Options
2. Asymmetric Information and Agency Theory
3. Capital Structure and Value of the Firm.
4. Optimal Capital Structure - Agency Costs, Signalling
5. Dividend policy/repurchases
6. Mergers and Acquisitions/corporate control
7. Venture Capital/Private Equity/hedge funds
8. Behavioural Corporate Finance.
9. Emotional Corporate Finance
10. Revision.
1
1: Investment Flexibility/ Real
options.
• Reminder of Corporation’s Objective :
Take projects that increase shareholder
wealth (Value-adding projects).
• Investment Appraisal Techniques: NPV,
IRR, Payback, ARR
• Decision trees
• Real Options
• Game-theory approach!
2
Investment Flexibility, Decision Trees, and Real
Options
Decision Trees and Sensitivity Analysis.
•Example: From Ross, Westerfield and Jaffe: “Corporate Finance”.
•New Project: Test and Development Phase: Investment
$100m.
•0.75 chance of success.
•If successful, Company can invest in full scale
production, Investment $1500m.
•Production will occur over next 5 years with the
following cashflows.
3
Production Stage: Base Case
$000
Year 1
Year 2 - 6
Revenues
Variable Costs
Fixed Costs
Depreciation
6000
-3000
-1791
-300
Pretax Profit
Tax (34%)
909
-309
Net Profit
Cashflow
600
900
Initial Investment
-1500
6
900
Date 1 NPV = -1500 + 
t
(
1
.
15
)
t 2
= 1517
4
Decision Tree.
Date 1: -1500
Date 0: -$100
P=0.75
Success
Test
Invest
NPV = 1517
Do not Invest
NPV = 0
Do not Invest
Failure
P=0.25
Do Not Test
Invest
NPV = -3611
Solve backwards: If the tests are successful, SEC should invest,
since 1517 > 0.
If tests are unsuccessful, SEC should not invest, since 0 > -3611.
5
Now move back to Stage 1.
Invest $100m now to get 75% chance of $1517m one year later?
Expected Payoff = 0.75 *1517 +0.25 *0 = 1138.
NPV of testing at date 0 = -100 + 1138 = $890
1.15
Therefore, the firm should test the project.
Sensitivity Analysis (What-if analysis or Bop analysis)
Examines sensitivity of NPV to changes in underlying
assumptions (on revenue, costs and cashflows).
6
Sensitivity Analysis.
- NPV Calculation for all 3 possibilities of a single variable +
expected forecast for all other variables.
NPV
Market Size
Market Share
Price
Variable Cost
Fixed Cost
Investment
Pessimistic
-1802
-696
853
189
1295
1208
Expected
or Best
1517
1517
1517
1517
1517
1517
Optimistic
8154
5942
2844
2844
1628
1903
Limitation in just changing one variable at a time.
Scenario Analysis- Change several variables together.
Break - even analysis examines variability in forecasts.
It determines the number of sales required to break even.
7
Real Options.
A digression: Financial Options (revision)
A call option gives the holder the right (but not the obligation) to
buy shares at some time in the future at an exercise price agreed
now.
A put option gives the holder the right (but not the obligation) to
sell shares at some time in the future at an exercise price agreed
now.
European Option – Exercised only at maturity date.
American Option – Can be exercised at any time up to maturity.
For simplicity, we focus on European Options.
8
Example:
• Today, you buy a call option on Marks and
Spencer’s shares. The call option gives you the
right (but not the obligation) to buy MS shares at
exercise date (say 31/12/10) at an exercise price
given now (say £10).
• At 31/12/10: MS share price becomes £12. Buy at
£10: immediately sell at £12: profit £2.
• Or: MS shares become £8 at 31/12/10: rip option
up!
9
Factors Affecting Price of European Option (=c).
-Underlying Stock Price S.
-Exercise Price X.
-Variance of of the returns of the underlying asset ,

2
-Time to maturity, T.
c
c
c
c
 0,
 0, 2  0,
 0.
S
X

T
The riskier the underlying returns, the greater the probability that
the stock price will exceed the exercise price.
The longer to maturity, the greater the probability that the stock
price will exceed the exercise price.
10
Options: Payoff Profiles.
Selling a put option.
Buying a Call Option.
W
S
Selling a Call Option.

Buying a Put Option.
11
Pricing Call Options – Binomial Approach.
Cu = 3
uS=24.00
q
q
c
S=20
1- q
dS=13.40
1- q
Cd=0
S = £20. q=0.5. u=1.2. d=.67. X = £21.
1 + rf = 1.1.
Risk free hedge Portfolio: Buy One Share of Stock and write m
call options.
uS - mCu = dS – mCd => 24 – 3m = 13.40.
M = 3.53.
By holding one share of stock, and selling 3.53 call options, your
12
payoffs are the same in both states of nature (13.40): Risk free.
Since hedge portfolio is riskless:
(1  rf )( S  mc)  uS  mcu .
1.1 ( 20 – 3.53C) = 13.40.
Therefore, C = 2.21.
This is the current price per call option. The total present value of
investment = £12 .19, and the rate of return on investment is
13.40 / 12.19 = 1.1.
13
Alternative option-pricing method
• Black-Scholes
• Continuous Distribution of share returns
(not binomial)
• Continuous time (rather than discrete time).
14
Real Options
• Just as financial options give the investor the right
(but not obligation) to future share investment
(flexibility)
• Researchers recognised that investing in projects
can be considered as ‘options’ (flexibility).
• “Real Options”: Option to delay, option to
expand, option to abandon.
• Real options: dynamic approach (in contrast to
static NPV).
15
Real Options
• Based on the insights, methods and
valuation of financial options which give
you the right to invest in shares at a later
date
• RO: development of NPV to recognise
corporation’s flexibility in investing in
PROJECTS.
16
Real Options.
• Real Options recognise flexibility in
investment appraisal decision.
• Standard NPV: static; “now or never”.
• Real Option Approach: “Now or Later”.
• -Option to delay, option to expand, option
to abandon.
• Analogy with financial options.
17
Types of Real Option
• Option to Delay (Timing Option).
• Option to Expand (eg R and D).
• Option to Abandon.
18
Option to Delay (= call option)
•
Investment in
waiting:
Valuecreation
Project
value
(sunk)
19
Option to expand (= call option)
Value creation
•
Investment in
initial project:
eg R and D
(sunk)
Project
value
20
Option to Abandon ( = put option)
•
Project goes
badly: abandon
for liquidation
value.
Project
value
21
Valuation of Real Options
• Binomial Pricing Model
• Black-Scholes formula
22
Value of a Real Option
• A Project’s Value-added = Standard NPV
plus the Real Option Value.
• For given cashflows, standard NPV
decreases with risk (why?).
• But Real Option Value increases with risk.
• R and D very risky: => Real Option element
may be high.
23
Comparing NPV with Decision
Trees and Real Options (revision)
E ( FCF1 )
NPV   I  t 1
0
t
(1  WACC )
N
•Dixit and Pyndyck (1994): Simple Example: Decide
today to:
•Invest in a machine at end of year: I = £1,600.
•End of year: project will be worth 300 (good state
forever) or 100 (bad state forever) with equal probability.
•WACC = 10%.
•Should we invest?
24
Dixit and Pyndyck example
• Either pre-commit today to invest in a
machine that will cost £1,600 at year end.
• Or defer investment to wait and see.
• Good state of nature (P = 0.5): product will
be worth £300.
• Bad state of nature (P = 0.5): product will
be worth £100.
25
NPV of project under precommitment
•
NPV1  1,600  0.5(300  100)  t 1

 1,600  200 
0.5(300  100)
(1.1) t
200
 600
0.1
=>
600
NPV0 
 545.5
1.1
26
Value with the option to defer
• Suppose cost of investment goes up to £1,800 if
we decide to wait (so, cost of waiting).
• Year end good state:
•
300
NPV  1800  300 
 1500
0.1
• Year-end bad state:
100
NPV  1800  100 
 700
0.1
27
Value with option to defer
(continued)
•
0.5(1500)
NPV0 
 681.80
1.1
Therefore, deferring adds value of £136.30.
Increasing uncertainty; eg price in good or bad state =
400 or zero (rather than 300 or 100)
=> Right to defer becomes more valuable.
28
Comparing NPV, decision trees and
Real Options (continued)
•
0.5
300 
300
 1,600
0.1
545.5
Invest 0.5
300 
100
 1,600
0 .1
Pre-commitment to invest
29
Comparing NPV, decision trees and
Real Options (continued)
•
0.5
Invest
V= 681.8
Defer
Max{1500,0}
0.5
Max {-700,0}
Don’t Invest
Value with the option to defer
30
Simplified Examples
• Option to Expand (page 241 of RWJ)
If Successful
Expand
Build First Ice
Hotel
Do not Expand
If unsuccessful
31
Option to Expand (Continued)
•
•
•
•
•
•
•
NPV of single ice hotel
NPV = - 12,000,000 + 2,000,000/0.20 =-2m
Reject?
Optimistic forecast: NPV = - 12M + 3M/0.2
= 3M.
Pessimistic: NPV = -12M + 1M/0.2 = - 7m
Still reject?
32
Option to expand (continued)
• Given success, the E will expand to 10
hotels
• =>
• NPV = 50% x 10 x 3m + 50% x (-7m) =
11.5 m.
• Therefore, invest.
33
Option to abandon.
•
•
•
•
•
•
•
NPV(opt) = - 12m + 6m/0.2 = 18m.
NPV (pess) = -12m – 2m/0.2 = -22m.
=> NPV = - 2m. Reject?
But abandon if failure =>
NPV = 50% x 18m + 50% x -12m/1.20
= 2.17m
Accept.
34
Real Option analysis and Game
theory
• So far, analysis has assumed that firm
operates in isolation.
• No product market competition
• Safe to delay investment to see what
happens to economy.
• In real-world, competitors (vultures)
• Delay can be costly!
35
Option to delay and Competition
• Smit and Ankum model (1993)
• Option to defer an investment in face of
competition
• Combines real options and Game-theory.
• Binomial real options model: lends itself
naturally to sequential game approach (see
exercise 1).
36
Option to delay and competition
(continued)
• Smit and Ankum incorporate game theory
(strategic behaviour) into the binomial pricing
model of Cox, Ross and Rubinstein (1979).
• Option to delay increases value (wait to observe
market demand)
• But delay invites product market competition:
reduces value (lost monopoly advantage).
• cost: Lost cash flows
• Trade-off: when to exercise real option (ie when to
delay and when to invest in project).
37
Policy implications of Smit and
Ankum analysis.
• How can firm gain value by delaying
(option to delay) in face of competition?
• Protecting Economic Rent: Innovation,
barriers to entry, product differentiation,
patents.
• Firm needs too identify extent of
competitive advantage.
38
Real Options and Games (Smit and
Trigeorgis 2006)
• Game theory applied to real R and
D/innovation cases:
• Expanded (strategic) NPV = direct (passive)
NPV + Strategic (commitment) value +
flexibility Value.
• Innovation race between Philips and Sony
=> Developing CD technology.
39
P\S
Wait
Invest
Wait
300, 300
0, 400
Invest
400, 0
200, 200
Each firm’s dominant strategy: invest early: =>
Prisoner’s dilemma.
How to collaborate/coordinate on wait, wait?
40
Asymmetric Innovation Race/
Pre-emption
• Asymmetry: P has edge in developing technology,
but limited resources.
• S tries to take advantage of this resource weakness
• Each firm chooses effort intensity in innovation
• Low effort: technology follower, but more
flexibility in bad states
• High effort: technology leader, higher
development costs, more risk in bad state.
41
•
P\S
Low effort
High
Low
200, 100
10, 200
High
100, 10
-100, -100
“Grab the dollar” game
42
Sequential Investment Game
•
High effort
-100m,-100m
S
High effort
Low effort
100m, 10m
P
High effort
10m, 200m
Low effort
S
Low effort
200m, 100m
43
European Airport Expansion Case:
Real Options Game (Smit 2003)
•
44
Two-stage Investment Game (Imai
and Watanabe 2004)
•
45
Option to delay versus competition:
Incorporating contracts/ Legal system (RF)
Firm 1\Firm 2
Invest early
Delay
Invest early
NPV = 500,NPV = 500
NPV = 700, NPV = 300
Delay
NPV = 300, NPV = 700
NPV = 600,NPV = 600
46
Option to delay versus competition:
Incorporating contracts/ Legal system
(continued)
Firm 1\ Firm 2
Invest early
Delay
Invest early
NPV = 500,NPV = 500
NPV = 700- 300, NPV =
300+300
Delay
NPV = 300+300, NPV =
700-300
NPV = 600,NPV = 600
47
Use of Real Options in Practice
48
• In practice, NPV not always used:Why Not?.
• -Agency (incentive) problems: eg Short-term
compensation schemes => Payback.
• Behavioural:• Managers prefer % figures => IRR, ARR
• Managers don’t understand NPV/ Complicated
Calculations.
• Payback simple to calculate.
• Other Behavioural Factors (see later section on
Behavioural Finance!!)
• Increase in Usage of correct DCF techniques
(Pike):
• Computers.
• Management Education.
49
Game-theoretic model of NPV.
• Israel and Berkovitch RFS 2004.
• NPV is seen as standard value-maximising
technique.
• But IB’s game-theoretic approach considers
the impact of agency and assymetric
information problems
50
Israel and Berkovitch (continued)
•
•
•
•
A firm consisting of two components:
1: Top management (Headquarters)
2. divisional managers (“the manager”).
Objective of headquarters: Maximisation of
shareholder value.
• Objective of manager: maximise her own
utility.
51
Israel and Berkovitch (continued)
• HQ needs to design a monitoring and
incentive mechanism to deal with these
conflicting objectives.
• => capital allocation system specifying:
• A capital budgeting rule (eg NPV/IRR) and
a wage compensation for divisional
managers.
52
Israel and Berkovitch
• Paper demonstrates the ingredients of a
game-theoretic approach.
• Players.
• Objectives (utility functions to maximise)
• Strategies.
• Payoffs.
53
2. Information Asymmetry/Agency
Theory
• Chapter 12 CWS.
• We will see that info assymetry and agency
theory play a large role in CF analysis.
• Investment appraisal, capital structure,
dividend policy
• => Game theory
54
Game theory
• Players (eg managers/investors: or competing
companies)
• Actions (eg invest in a project, issue debt, pay
dividends etc)
• Strategies
• Payoffs/ optimisation.
• Equilibrium: eg good firm issues high debt, bad
firm issues low debt.
• Or Good firm pays high dividends, bad firm pays
low dividends.
55
Information Asymmetry
• Insiders/managers better informed than
investors about projects, prospects etc.
• Managerial actions (eg capital structure
choices: debt/equity issues, dividends,
repurchases) may reveal information to the
market
• Signalling models of debt, dividends,
repurchases
56
Asymmetric info/signalling models
• Typically, two types of firm: High quality/low
quality.
• Type unobservable to outside investors
• Manager of High quality firm would like to signal
his type to market.
• Costly signals
• Cheap-talk signals.
• Eg level of investment, amount of debt, size of
dividend.
57
Pooling versus separating equilibria
• Separating equilibrium: good firm can separate for
bad firm eg by higher debt
• Cost of signal: eg expected financial distress
• Separation requires cost of signal => bad firm
cannot (or is unwilling) to mimic good firm’s debt
level.
• Separation: outsiders can determine firm types
• Pooling: outsiders cannot differentiate between the
two types
58
Corporate Finance: Signalling
Models
• Based on models from Informational
Economics.
• Eg Akerlof (1970): price signals of quality
in used car market (mkt for Lemons!)
• Spence (1973): education as signals of skill
in job market.
• Myers-Majluf (1984): equity-signalling
model based on Akerlof’s Lemons market!
59
Major CF signalling models
• Signalling project quality with investment
(Leland and Pyle 1977)
• Signalling firm quality with debt (Ross
1977)
• Signalling expected cashflows with
dividends (Bhattacharya 1979)
• Signalling and the equity issue-invest
decision (Myers-Majluf 1984)
60
Stock Split signalling
• Copeland and Brennan 1988
• Brennan and Hughes 1991.
• Debt/equity Heinkel 1982
61
CF and Agency Theory
• Standard CF statement: the firm aims to
maximise shareholder wealth => NPV rule.
• But agency theory =>
• Separation of Ownership and control
• Principal/agent relationship
• Outside investors = Principal
• Manager = agent
62
Agency theory (contiuned)
• Manager self-interested.
• he may takes private benefits (perks) out of the
firm
• Invest in favourite (pet) projects: empire-builder
(eg rapid value-destroying growth => mergers?)
• Effort-shirking
• Capital structure/dividends may serve to align
managers’ and investors’ interests.
63
2. Cost of Capital/discount
rate/investors’ required return.
• What discount rate to use in NPV/
valuation?
• Portfolio analysis => Investors’ required
return as a compensation for risk
• => CAPM (capital asset pricing model) =>
cost of equity (risk-averse equity-holders’
required return): increases with risk.
64
Cost of Capital/discount rate/investors’
required return (continued).
• Cost of debt (debt-holders’ required return).
• Capital structure (mix of debt and equity).
• => discount rate/cost of capital/investors’
required return=>
WACC  %debt * K d  %equity * Ke .
65
Example
• New project: initial investment I  £1000
• Project expected to generate £150 per year forever
(perpetuity)
• Kd=5%, Ke = 15% (Capital structure =50%
debt/50% equity)
• Consider Market Value of firm’s debt = market value
of firms equity=> WACC = 10%.
NPV  1000 
150
 500
0.10
66
Firm Valuation (CWS Chapter 14)
• Formula Approach for Valuing Companies
t0
V0
t1
t2
EBIT1 (1  T )  I1
tN
EBIT1 (1  T )  t 1 rt I t  I N
N 1
EBIT2 (1  T )  I 2
 EBIT1 (1  T )  r1 I1  I 2
67
Valuation of all-equity firm with
growth
EBIT1 (1  T )  I1
V1
V0 

1  KU
1  KU
=>
EBIT N (1  TC )  I N
EBIT1 (1  T )  I1 EBIT2 (1  T )  I 2
V0 

 ... 
2
1  KU
(1  KU )
(1  KU ) N
68
Valuation of all-equity firm with
growth (continued)
EBITt (1  T )  I t
V0  t 1
(1  kU )t
N
•Present value of the firm is the sum of discounted
cashflows from operations less new investments
required for growth
•Fundamental Value (= market value? Efficient mkts/
BCF)
•Dividend policy (dividends versus investment for
growth)
69
Valuation of all-equity firm with
growth (continued)
I t (rt  KU )
EBIT1 (1  T )

V0 
 t 1
t
KU
KU (1  KU )
V0 = value of assets in place + value of future
growth
70
Infinite constant growth model
I t  K ( EBITt (1  T ))
EBITt (1  T )  EBITt 1 (1  T )  rI t 1
 EBIT (1  T )  rK ( EBITt 1 (1  T ))
 EBITt 1 (1  T )(1  rK )
=>
EBITt (1  T )  EBIT1 (1  T )(1  rK )t 1
=>
EBITt (1  T )  EBIT1 (1  T )(1  g )t 1
71
By substitution:
K (r  kU )  1  rK t
EBIT1 (1  T )
V0 
[1 
(
)]

t 1
KU
1  rK
1  kU
But:
1  rK t
1  rK
t 1 ( 1  k ) ]  k  rK
U
U

=>
V0 
EBIT1 (1  T )(1  K )
Div1

kU  Kr
kU  g
Gordon Growth
Model:
Consider later in
div policy lecture
72
3. Capital Structure.
Positive NPV project immediately increases current equity
value (share price immediately goes up!)
Pre-project announcement
V  Bo  Eo
I
New capital (all equity)
New project:
Value of Debt
Original equity holders
New equity
New Firm Value
NPV  Vn  I .
Bo
E0  Vn  I
I
V  Vn
73
Example:
V  Bo  Eo
I
=500+500=1000.
20
NPV  Vn  I 
60 -20 = 40.
Bo
Value of Debt
Original Equity
E0  Vn  I
New Equity
I
= 20
V  Vn
=1000+60=1060.
Total Firm Value
= 500.
= 500+40 = 540
74
Positive NPV: Effect on share price.
Assume all equity.
£K
Current
Market
Value
No of
Shares
1000
New Project
Project Income
60
Required Investment
20
NPV
40
1000
Price per
Share
1
Market
Value
No of
Shares
Price per
Share
1040
1000
1.04
20
19
1.04
1060
1019
1.04
75
Value of the Firm and Capital Structure
Value of the Firm = Value of Debt + Value of Equity = discounted
value of future cashflows available to the providers of capital.
(where values refer to market values).
Capital Structure is the amount of debt and equity: It is the way a firm
finances its investments.
Unlevered firm = all-equity.
Levered firm = Debt plus equity.
Miller-Modigliani said that it does not matter how you split the cake
between debt and equity, the value of the firm is unchanged (Irrelevance
Theorem).
76
Value of the Firm = discounted value of future cashflows available to
the providers of capital.
-Assume Incomes are perpetuities.
Miller- Modigliani Theorem:
VU 
NCF (1  T )

 VE
NCF (1  T )
VL  VU  T .B 
 VE  VD
WACC

NI kd .B

.
K
Kd
e
Irrelevance Theorem: Without Tax, Firm Value is
independent of the Capital Structure.
Note that
WACC  %debt * K d (1  t )  %equity * K e
77
K
K
Without Taxes
D/E
With Taxes
D/E
V
V
D/E
78
D/E
Examples
• Firm X
• Henderson Case study
79
MM main assumptions:
- Symmetric information.
-Managers unselfish- maximise shareholders wealth.
-Risk Free Debt.
MM assumed that investment and financing decisions
were separate. Firm first chooses its investment projects
(NPV rule), then decides on its capital structure.
Pie Model of the Firm:
D
E
E
80
MM irrelevance theorem- firm can use any mix of
debt and equity – this is unsatisfactory as a policy tool.
Searching for the Optimal Capital Structure.
-Tax benefits of debt.
-Asymmetric information- Signalling.
-Agency Costs (selfish managers).
-Debt Capacity and Risky Debt.
Optimal Capital Structure maximises firm value.
81
Combining Tax Relief and Debt Capacity (Traditional View).
K
V
D/E
82
D/E
3: Optimal Capital Structure, Agency
Costs, and Signalling.
Agency costs - manager’s self interested actions.
Signalling - related to managerial type.
Debt and Equity can affect Firm Value because:
- Debt increases managers’ share of equity.
-Debt has threat of bankruptcy if manager shirks.
- Debt can reduce free cashflow.
But- Debt - excessive risk taking.
83
AGENCY COST MODELS.
Jensen and Meckling (1976).
- self-interested manager - monetary rewards V private
benefits.
- issues debt and equity.
Issuing equity => lower share of firm’s profits for
manager => he takes more perks => firm value
Issuing debt => he owns more equity => he takes less
perks => firm value
84
Jensen and Meckling (1976)
V
V*
Slope = -1
A
V1
B1
B
If manager owns all of the equity, equilibrium point A.
85
Jensen and Meckling (1976)
V
V*
Slope = -1
A
B
V1
Slope = -1/2
B1
B
If manager owns all of the equity, equilibrium point A.
If manager owns half of the equity, he will got to point B if he
can.
86
Jensen and Meckling (1976)
V
V*
Slope = -1
A
B
V1
Slope = -1/2
V2
C
B1
B2
B
If manager owns all of the equity, equilibrium point A.
If manager owns half of the equity, he will got to point B if he
can.
Final equilibrium, point C: value V2, and private benefits B1.87
Jensen and Meckling - Numerical Example.
PROJECT
A
EXPECTED INCOME
500
MANAGER'S SHARE:
100%
VALUE OF PRIVATE
BENEFITS
TOTAL WEALTH
MANAGER'S SHARE:
50%
VALUE OF PRIVATE
BENEFITS
TOTAL WEALTH
PROJECT
B
1000
500
1000
800
500
1300
1500
250
500
800
500
1050
1000
Manager issues
100% Debt.
Chooses Project B.
Manager issues
some Debt and
Equity.
Chooses Project A.
Optimal Solution: Issue Debt?
88
Issuing debt increases the manager’s fractional
ownership => Firm value rises.
-But:
Debt and risk-shifting.
State 1
100
0
0.5
State 2
100
170
0.5
100
85
Debt
50
25
Equity
50
60
Values:
89
OPTIMAL CAPITAL STRUCTURE.
Trade-off: Increasing equity => excess perks.
Increasing debt => potential risk shifting.
Optimal Capital Structure => max firm value.
V
V*
D/E*
D/E
90
Other Agency Cost Reasons for Optimal Capital
structure.
Debt - bankruptcy threat - manager increases effort level.
(eg Hart, Dewatripont and Tirole).
Debt reduces free cashflow problem (eg Jensen 1986).
91
Agency Cost Models – continued.
Effort Level, Debt and bankruptcy (simple example).
Debtholders are hard- if not paid, firm becomes bankrupt, manager
loses job- manager does not like this.
Equity holders are soft.
Effort
Level
High
Low
Required
Funds
Income
500
100
200
What is Optimal Capital Structure (Value Maximising)?
92
Firm needs to raise 200, using debt and equity.
Manager only cares about keeping his job. He has a fixed
income, not affected by firm value.
a) If debt < 100, low effort. V = 100. Manager keeps job.
b) If debt > 100: low effort, V < D => bankruptcy.
Manager loses job.
So, high effort level => V = 500 > D. No bankruptcy =>
Manager keeps job.
High level of debt => high firm value.
However: trade-off: may be costs of having high debt
levels.
93
Free Cashflow Problem (Jensen 1986).
-Managers have (negative NPV) pet projects.
-Empire Building.
=> Firm Value reducing.
Free Cashflow- Cashflow in excess of that
required to fund all NPV projects.
Jensen- benefit of debt in reducing free cashflow.
94
Jensen’s evidence from the oil industry.
After 1973, oil industry generated large free cashflows.
Management wasted money on unnecessary R and D.
also started diversification programs outside the industry.
Evidence- McConnell and Muscerella (1986) – increases
in R and D caused decreases in stock price.
Retrenchment- cancellation or delay of ongoing projects.
Empire building Management resists retrenchment.
Takeovers or threat => increase in debt => reduction in
free cashflow => increased share price.
95
Jensen predicts:
young firms with lots of good (positive NPV) investment
opportunities should have low debt, high free cashflow.
Old stagnant firms with only negative NPV projects should
have high debt levels, low free cashflow.
Stultz (1990)- optimal level of debt => enough free
cashflow for good projects, but not too much free cashflow
for bad projects.
96
Income Rights and Control Rights.
Some researchers (Hart (1982) and (2001), Dewatripont and
Tirole (1985)) recognised that securities allocate income rights
and control rights.
Debtholders have a fixed first claim on the firm’s income, and
have liquidation rights.
Equityholders are residual claimants, and have voting rights.
Class discussion paper: Hart (2001)- What is the optimal
allocation of control and income rights between a single investor
and a manager?
How effective are control rights when there are different types of
investors?
Why do we observe different types of outside investors- what is
97
the optimal contract?
Conflict
Breaking MM
Benefits of Debt
Costs of Debt
Tax Relief
Fin’l Distress/
Debt Capacity
Agency Models
JM (1976)
Managerial
Perks
Increase Mgr’s
Ownership
Risk Shifting
Jensen (1986)
Empire Building
Reduce Freecash
Unspecified.
Stultz
Empire Building
Reduce Freecash
Underinvestment
.
Dewatripont and
Tirole, Hart.
Low Effort level
Bankruptcy threat
=>increased effort
DT- Inefficient
liquidations.
98
Signalling Models of Capital Structure
Assymetric info: Akerlof’s (1970) Lemons Market.
Akerlof showed that, under assymetric info, only bad things may be
traded.
His model- two car dealers: one good, one bad.
Market does not know which is which: 50/50 probability.
Good car (peach) is worth £2000. Bad car (lemon) is worth £1000.
Buyers only prepared to pay average price £1500.
But: Good seller not prepared to sell. Only bad car remains.
Price falls to £1000.
Myers-Majuf (1984) – “securities may be lemons too.”
99
Asymmetric information and Signalling Models.
- managers have inside info, capital structure has signalling
properties.
Ross (1977)
-manager’s compensation at the end of the period is
M  (1  r )  0 V 0   1V 1 if V 1  D
M  (1  r )  0 V 0   1V 1  C if V 1  D
D* = debt level where bad firm goes bankrupt.
Result: Good firm D > D*, Bad Firm D < D*.
Debt level D signals to investors whether the firm is good or bad.
100
Myers-Majluf (1984).
-managers know the true future cashflow.
They act in the interest of initial shareholders.
P = 0.5
Do
Nothing:
Issue
Equity
Good
Bad
Good
Assets
in Place
250
130
350
230
NPV of
new
project
Value of
Firm
0
0
20
10
250
130
370
240
Expected Value
190
305
New investors
0
100
Old Investors
190
205
Bad
101
Consider old shareholders wealth:
Good News + Do nothing = 250.
205
(370)  248.69.
Good News + Issue Equity =
305
Bad News and do nothing = 130.
Bad News and Issue equity =
205
(240)  161.31.
305
102
Old Shareholders’ payoffs
Good
News
Bad
News
Do
Issue
nothing and
invest
250 *
248.69
130
161.31*
Equilibrium
Good
News
Bad
News
Do
Issue
nothing and
invest
250 * 248.69
130
140 *
Issuing equity signals that the bad state will occur.
The market knows this - firm value falls.
Pecking Order Theory for Capital Structure => firms
prefer to raise funds in this order:
Retained Earnings/ Debt/ Equity.
103
Evidence on Capital structure and firm value.
Debt Issued - Value Increases.
Equity Issued- Value falls.
However, difficult to analyse, as these capital structure
changes may be accompanied by new investment.
More promising - Exchange offers or swaps.
Class discussion paper: Masulis (1980)- Highly
significant Announcement effects:
+7.6% for leverage increasing exchange offers.
-5.4% for leverage decreasing exchange offers.
104
Practical Methods employed by Companies (See
Damodaran; Campbell and Harvey).
-Trade off models: PV of debt and equity.
-Pecking order.
-Benchmarking.
-Life Cycle.
Increasing Debt?
time
105
Trade-off Versus Pecking Order.
• Empirical Tests.
• Multiple Regression analysis (firm size/growth
opportunities/tangibility of assets/profitability…..
• => Relationship between profitability and leverage
(debt): positive => trade-off.
• Or negative => Pecking order:
• Why?
• China: Reverse Pecking order
106
Capital Structure and Product
Market Competition.
• Research has recognised that firms’ financial
decisions and product market decisions not made
in isolation.
• How does competition in the product market affect
firms’ debt/equity decisions?
• Limited liability models: Debt softens
competition: higher comp => higher debt.
• Predation models: higher competition leads to
lower debt. (Why?)
107
Capital Structure and Takeovers
• Garvey and Hanka:
• Waves of takeovers in US in 1980’s/1990’s.
• Increase in hostile takeovers => increase in
debt as a defensive mechanism.
• Decrease in hostile takeovers => decrease in
debt as a defensive mechanism.
108
Garvey and Hanka (contiuned)
Trade-off: Tax shields/effort
levels/FCF/ efficiency/signalling
Vs financial distress
V
•
D/E
D/E*
109
Practical Capital Structure: case
study
•
110
Game Theoretic Approach to Capital
Structure.
• Moral Hazard Model.
• Asymmetric Information Model.
• See BCF section 8 for incorporation of
managerial overconfidence.
111
Cash-flow Rights and Control Rights
• Debt-holders: first fixed claim on cashflows (cash-flow rights); liquidation rights
in bas times (control rights)- hard investors.
• Equity-holders: residual claimants on cashflows (cash-flow rights): voting rights in
good times (control rights) – soft investors.
• => minority shareholder rights versus
blockholders.
112
Equity-holders’ control rights
•
•
•
•
•
•
•
•
Voting rights.
Soft: free-rider problems.
Minority holders versus block-holders.
Minority –holders versus insiders.
Separation of ownership and control.
Corporate Charter.
Dual class of shares.
Pyramids/tunelling etc.
113
Capital/corporate structure in
emerging economies.
•
•
•
•
•
•
Separation of ownership and control.
Corporate Charter.
Dual class of shares.
Pyramids/tunelling etc.
Weak Legal Systems.
Cultural differences.
114
Game-theoretic approaches.
• JFE special issue 1988 (Grossman and Hart,
Stultz, Harris and Raviv).
• Bebchuk (lecture slides to follow).
• Garro Paulin and Fairchild (2006) Lecture
slides to follow.
115
Mergers and Acquisitions
116
Mergers and Acquisitions
•
•
•
•
Acquisitions
Divestitures
Restructuring
Corporate Governance
117
Growth Strategies
• Mergers: one economic unit formed from 2
or more previous units
• A) Tender offer
118
Merger
Acquisition
Stock
Acquisition
Takeovers
•
Proxy Contest
1. Merger- must be approved by stockholders’ votes.
2. Stock acquisition- No shareholder meeting, no vote required.
-bidder can deal directly with target’s shareholders- bypassing
target’s management.
- often hostile => target’s defensive mechanisms.
-shareholders may holdout- freerider problems.
3. Proxy Contests- group of shareholders try to vote in new
directors to the board.
119
Growth Strategies
• Mergers: one economic unit formed from 2
or more previous units
• A) Tender offer
• B) Pooling of Interest
• Joint Ventures
• Other collaborations (supplier networks,
alliances, investments, franchises)
120
Shrinkage strategies
•
•
•
•
Divestitures
Equity carveouts
Spin-offs
Tracking stock
121
Theories of M and A.
•
•
•
•
•
•
Efficiency increases (restructuring)
Operating Synergies
Financial Synergy
Information
Hubris and the Winner’s curse
Agency Problems (changes in
ownership/managerialism/FCF)
• Redistribution (tax, mkt power, …)
122
Synergy Value of a Merger
V AB  (V A  V B ).
Synergy comes from increases in cashflow form
the merger:
CFt  REVt  Costst
123
Example: Market Value after
Merger.
• Firm A (bidder): cashflows = £10m, r = 20%.
V = £50m.
• Firm B (target): cashflows = £6m, r = 15%.
=
£40m.
• If A acquires B: Combined Cashflows are
expected to increase to £25m P.A. New Discount
rate 25%.
• Synergy cashflows = £9m.
• Total value = £100m.
• Synergy Value = £10m.
124
Who gets the gains from mergers?
•
Depends on what the bidder has to pay!
(bid premium)
NPVBidder  VAB  VA  I
NPVt arg et  I  VB
If
I  VB , Bidder gets all of the positive NPV.
If
I  VAB  VA ,
Target gets all of the positive NPV.
125
Why a Bid premium?
• Hostile Bid: defensive (anti-takeover)
mechanisms (leverage increases, poison
pills, etc):
• Bidding wars.
• Market expectations.
126
Effects of takeovers on stock prices of bidder
and target.
Successful Bids
Unsuccessful Bids
Takeover Target
Technique
Tender
30%
Offer
Merger
20%
Bidders
Proxy
Contest
n.a
•
8%
4%
0
Takeover Target
Technique
Tender
-3%
Offer
Merger
-3%
Bidders
Proxy
Contest
n.a
8%
-1%
-5%
Jensen and Ruback JFE 1983
127
Game Theoretic Approach to M and A.
• Grossman and Hart (Special Issue on Corporate
Control 1982).
• Harris and Raviv (Special Issue on Corporate
Control 1982).
• Bebchuk (Special Issue on Corporate Control
1982)..
• Burkart (JOF 1995).
• Garvey and Hanka.
• Krause.
128
Garvey and Hanka paper
• Lecture slides to follow.
129
Grossman and Hart free-rider paper
• Lecture slides to follow.
130
Convertible Debt
•
•
•
•
•
-Valuation of Convertibles.
-Impact on Firm Value.
-Why firms issue convertibles.
-When are they converted (call policy)?
Convertible bond -holder has the right to
exchange the bond for common stock (equivalent
to a call option).
• Conversion Ratio = number of shares received
for each bond.
• Value of Convertible Bond = Max{ Straight bond
131
value, Conversion Value} +option value.
Value of Convertible Bond.
V
Face
Value
Straight Bond Value
Conversion Value
•
Firm Value
Firm Value
Total Value of Convertible Bond
Firm Value
132
• Conflict between Convertible Bond holders and
managers.
• Convertible Bond = straight debt + call option.
• Value of a call option increases with:
• Time.
• Risk of firm’s cashflows.
• Implications: Holders of convertible debt
maximise value by not converting until forced to
do so => Managers will want to force conversion
as soon as possible.
• Incentive for holders to choose risky projects =>
managers want to choose safe projects.
133
Reasons for Issuing Convertible Debt.
Much real world confusion.
Convertible debt - lower interest rates than straight debt.
=> •Cheap form of financing?
No! Holders are prepared to accept a lower interest rate because
of their conversion privilege.
N
IC
PR

.

t
N
(1  K C )
t 1 (1  K C )
CD = N
ID
M

.

t
N
D = t 1 (1  K D ) (1  K D )
I D  I C , PR  M , K D  KC  CD  D.
134
•
•
•
•
•
•
•
•
•
Example of Valuation of Convertible Bond.
October 1996: Company X issued Convertible Bonds at
October 1996: Coupon Rate 3.25%, Each bond had face
Value £1000.
Bonds to mature October 2001.
Convertible into 21.70 Shares per per bond until October
2001.
Company rated A-. Straight bonds would yield 5.80%.
Now October 1998:
Face Value £1.1 billion.
Convertible Bonds trading at £1255 per bond.
The value of the convertible has two components; The
straight bond value + Value of Option.
135
Valuation of Convertible Bond- Continued.
If the bonds had been straight bonds: Straight bond value =
PV of bond =
•
t 3
16.25
1000

 932.83

t
3
(1.058)
t 0.5 (1.058)
Price of convertible = 1255.
Conversion Option = 1255 – 933 = 322.
Oct 1998 Value of Convertible = 933 + 322 = 1255.
= Straight Bond Value + Conversion Option.
136
Alternative Analysis of Irrelevance of Convertible Debt.
Firm Does
Badly.
•
Firm Does
Well.
Convertible Debt.No Conversion. Conversion.
Compared with: CD cheaper
CD expensive,
Straight Bonds. financing, lower Bonds are
coupon rate.
converted,
Existing Equity
Dilution.
Equity.
CD expensive. CDs cheaper.
Firm Indifferent between issuing CD, debt or equity.
-MM.
137
•
•
•
•
•
•
•
•
•
Why do firms issue convertible debt?
If convertible debt is not a cheap form of financing, why is it
issued?
A. Equity through the Back Door (Stein, Mayers).
-solves asymmetric information problems (see MyersMajluf).
-solves free cashflow problems.
B. Convertible debt can solve risk-shifting problems.
- If firm issues straight debt and equity, equity holders have
an incentive to go for risky (value reducing) NPV projects.
Since CD contains an option feature, CD value increases with
risk.
-prevents equity holders’ risk shifting.
138
Convertible Debt and Call Policy.
Callable Convertible debt =>firms can force conversion.
When
• the bond is called, the holder has 30 days to either:
a) Convert the bond into common stock at the conversion
ratio, or
b) Surrender the bond for the call price.
When should the bond be called?
Option Theory: Shareholder wealth is maximised/ CD holders
wealth is minimised if
Firm calls the bond as soon as value = call price.
139
• Call Puzzle.
• Manager should call the bond as soon as he can force
conversion.
• Ingersoll (1977) examined the call policies of 124
firms 1968-1975.
• - He found that companies delayed calling far too
long.
• - median company waited until conversion value was
44% above call price - suboptimal.
• Call Puzzle addressed by Harris and Raviv.
• - signalling reasons for delaying calling.
• - early calling might signal bad news to the market.
140
4: Dividend Policy
•
•
•
•
•
•
•
Miller-Modigliani Irrelevance.
Gordon Growth (trade-off).
Signalling Models.
Agency Models.
Lintner Smoothing.
Dividends versus share repurchases.
Empirical examples
141
Early Approach.
• Three Schools of Thought• Dividends are irrelevant (MM).
• Dividends => increase in stock prices
(signalling/agency problems).
• Dividends => decrease in Stock Prices (negative
signal: non +ve NPV projects left?).
• 2 major hypotheses: Free-cash flow versus
signalling
142
Important terminology
• Cum Div: Share price just before dividend
is paid.
• Ex div: share price after dividend is paid <
Cum div.
P
CD
ED
CD
CD
ED
ED
Time
143
Example
• A firm is expecting to provide dividends every
year-end forever of £10. The cost of equity is
10%.
• We are at year-end, and div is about to be paid.
Current market value of equity = 10/0.1 + 10 =
£110
• Div is paid. Now, current market value is
• V = 10/0.1 = £100.
• So on…
144
P
•
CD =
110
ED = 100
CD
CD
ED
ED
Time
145
Common Stock Valuation Model
• You are considering buying a share at price Po,
and expect to hold it one year before selling it
ex-dividend at price P1: cost of equity = r.
d1
P1
P0 

(1  r ) (1  r )
What would the buyer be prepared to pay to you?
d2
P2
P1 

(1  r ) (1  r )
146
Therefore:
d1
d2
p2
P0 


2
2
1  r (1  r ) (1  r )
Continuing this process, and re-substituting in
(try it!), we obtain:
d1
p0  t 1
(1  r )t

Price today is discounted value of all future dividends to
infinity (fundamental value = market value).
147
Dividend Irrelevance (MillerModigliani)
• MM consider conditions under which
dividends are irrelevant.
• Investors care about both dividends and
capital gains.
• Perfect capital markets:• No distorting taxes
• No transactions costs.
• No agency costs or assymetric info.
148
Dividend Irrelevance (MM):
continued
• Intuition: Investors care about total return
(dividends plus capital gains).
• Homemade leverage argument
• Source and application of funds argument
=> MM assumed an optimal investment
schedule over time (ie firm invests in all
+ve NPV projects each year).
149
Deriving MM’s dividend irrelevance
• Total market value of our all-equity firm is
•
Dt
S0  t 1
t
(1  r )
T
Sources = Uses
CFt  Ft  Dt  I t  (1  r ) Ft 1
150
Re-arranging:
Dt  CFt  Ft  I t  (1  r ) Ft 1
Substitute into first equation:
CF1  F1  I1  (1  r ) F0
T
S0  CF0  F0  I 0  (1  r ) F1 
 t 2 ...
(1  r )
At t =0,
CF0  F1  0
S0  F0  I 0 
CF1  F1  I1  (1  r ) F0
T
 t 2 ...
(1  r )
151
Successive substitutions
(CFt  I t )
S 0  t 0
(1  r ) t
T
•Current value of all-equity firm is present value of operating
cashflows less re-investment for all the years (residual
cashflow available to shareholders) Dividends do not appear!
•Assn: firms make optimal investments each period (firm
invests in all +ve NPV projects).
•Firms ‘balance’ divs and equity each period: divs higher
than residual cashflow => issue shares.
•Divs lower than free cashflow: repurchase shares.
152
Irrelevance of MM irrelevance
(Deangelo and Deangelo)
• MM irrelevance based on the idea that all
cash will be paid as dividend in the end (at
time T).
• Deangelo argues that even under PCM, MM
irrelevance can break down if firm never
pays dividend!
153
Irrelevance of MM irrelevance
(continued)
• Consider an all-equity firm that is expected to produce
residual cashflows of £10 per year for 5 years.
• Cost of equity 10%.
• First scenario: firm pays no dividends for the first 4 years.
Pays all of the cashflows as dividends in year 5.
10
V0  t 1
?
t
(1.1)
5
• Now it is expected to pay none of the cashflows in any year:
Vo = 0 !
154
“Breaking” MM’s Irrelevance
•
•
•
•
•
MM dividend irrelevance theorem based on:
PCM
No taxes
No transaction costs
No agency or asymmetric information
problems.
155
Gordon Growth Model.
• MM assumed firms made optimal investments out
of current cashflows each year
• Pay any divs it likes/ balanced with new
equity/repurchases.
• What if information problems etc prevent firms
easliy going back to capital markets:
• Now, real trade-off between investment and
dividends?
156
Gordon Growth Model.
Where does growth come from?- retaining
cashflow to re-invest.
Constant fraction, K, of earnings retained for reinvestment.
Rest paid out as dividend.
Average rate of return on equity = r.
Growth rate in cashflows (and dividends) is g = Kr.
Div 0
Div 1
NCF 0 (1  Kr )(1  K )


.
V0 
g g
  Kr
157
Example of Gordon Growth Model.
£K
19x5
Profits After Tax (NCF)
Retained Profit (NCF.K)
19x6
19x7
19x8
19x9
Average
2500
1550
2760
1775
2635
1600
2900
1800
3100
1900
950
985
1035
1100
1200
Share Capital + retentions
B/F
C/F (= BF + Retained Profit)
30000
31550
31550
33325
33325
34925
34925
36725
36725
38625
Retention Rate K
r on opening capital
0.62
0.083
0.64
0.087
0.61
0.079
0.62
0.083
0.61
0.084
Dividend (NCF(1-K))
0.62
0.083
g = Kr = 0.05.
How do we use this past data for valuation?
158
Gordon Growth Model (Infinite Constant
Growth Model).
Let
  12%
Div 0 (1  g ) Div1 1200(1.05)
1260
V0 



g
g
g
0.12  0.05
= 18000
159
Finite Supernormal Growth.
-Rate of return on Investment > market required return for T
years.
-After that, Rate of Return on Investment = Market required
return.
V0 
NCF1

(r   )
 K . NCF1.T
 (1   )
If T = 0, V = Value of assets in place (re-investment at zero
NPV).
Same if r =  .
160
Examples of Finite Supernormal Growth.
NCF1  100.
  10%.
T = 10 years. K = 0.1.
A. Rate of return, r = 12% for 10 years,then 10% thereafter.
100
(0.12  0.1)
V0 
 0.1.(100).10
 1018
0.1
0.1(1  0.1)
B. Rate of return, r = 5% for 10 years,then 10% thereafter.
100
(0.05  0.1)
V0 
 0.1.(100).10
 955
0.1
0.1(1  0.1)
161
Dividend Smoothing V optimal
re-investment (Fairchild 2003)
• Method:• GG Model: derive optimal retention/payout
ratio
• => deterministic time path for dividends,
Net income, firm values.
• => Stochastic time path for net income: how
can we smooth dividends (see Lintner
smoothing later….)
162
Deterministic Dividend Policy.
Div
N
1
0 (1  K )(1  Kr )

.
• Recall V 0 
g
  Kr
•
• Solving V0
 0,
K
• We obtain optimal retention ratio
•
K* 
  (   r )(   1)
r
.
163
Analysis of K *

• If r  [0, 1   ],
K*  0.


K
*
], K * [0,1], with
• If r  [0,
 0.
1 
r
• Constant r over time => Constant K* over
time.
164
Deterministic Case (Continued).
• Recursive solution:
Dt  N 0 (1  K *)(1  K * r )
t
• => signalling equilibria.
• Shorter horizon => higher dividends.
When r is constant over time, K* is constant. Net
Income, Dividends, and firm value evolve
deterministically.
165
Stochastic dividend policy.
• Future returns on equity normally and
independently distributed, mean r.
• Each period, K* is as given previously.
• Dividends volatile.
• But signalling concerns: smooth dividends.
• => “buffer” from retained earnings.
166
Agency problems
• Conflicts between shareholders and
debtholders: risk-shifting: high versus low
dividends => high divs => credit rating of
debt
• Conflicts between managers and
shareholders: Jensen’s FCF, Easterbrook.
167
Are Dividends Irrelevant?
- Evidence: higher dividends => higher value.
- Dividend irrelevance : freely available capital for reinvestment. If too much dividend, firm issued new shares.
- If capital not freely available, dividend policy may matter.
C. Dividend Signalling - Miller and Rock (1985).
NCF + NS = I + DIV: Source = Uses.
DIV - NS = NCF - I.
Right hand side = retained earnings. Left hand side higher dividends can be covered by new shares.
168
Div - NS - E (Div - NS) = NCF - I - E (NCF - I)
= NCF - E ( NCF).
Unexpected dividend increase - favourable signal of NCF.
Prob
0.5
Firm A
0.5
Firm B
E(V)
NCF
400
1400
900
New Investment
600
600
600
Dividend
New shares
0
200
800
0
400
100
E(Div - NS) = E(NCF - I) = 300.
Date 1 Realisation: Firm B: Div - NS - E (Div - NS) = 500 = NCF - E
( NCF).
Firm A : Div - NS - E (Div - NS) = -500 = NCF - E ( NCF).
169
Dividend Signalling Models.
•
•
•
•
•
•
•
Bhattacharya (1979)
John and Williams (1985)
Miller and Rock (1985)
Ofer and Thakor (1987)
Fuller and Thakor (2002).
Fairchild (2009/10).
Divs credible costly signals: Taxes or borrowing costs.
170
Competing Hypotheses.
• Dividend Signalling hypothesis Versus Free
Cashflow hypothesis.
• Fuller and Thakor (2002; 2008): Consider
asymmetric info model of 3 firms (good, medium,
bad) that have negative NPV project available
• Divs used as a) a positive signal of income, and b)
a commitment not to take –ve NPV project
(Jensen’s FCF argument).
• Both signals in the same direction (both +ve)
171
Signalling, FCF, and Dividends.
Fuller and Thakor (2002)
• Signalling Versus FCF hypotheses.
• Both say high dividends => high firm value
• FT derive a non-monotonic relationship
between firm quality and dividends.
Divs
Firm
Quality
172
Fairchild (2009, 2010)
• Signalling Versus FCF hypotheses.
• But, in contrast to Fuller and Thakor, I
consider +ve NPV project.
• Real conflict between high divs to signal
current income, and low divs to take new
project.
• Communication to market/reputation.
173
Cohen and Yagil
• New agency cost: firms refusing to cut
dividends to invest in +ve NPV projects.
• Wooldridge and Ghosh
• 6 roundtable discussions of CF.
174
Agency Models.
•
•
•
•
Jensen’s Free Cash Flow (1986).
Stultz’s Free Cash Flow Model (1990).
Easterbrook.
Fairchild (2009/10): Signalling + moral
hazard.
175
Behavioural Explanation for
dividends
• Self-control.
• Investors more disciplined with dividend
income than capital gains.
• Mental accounting.
• Case study from Shefrin.
• Boyesen case study.
176
D.
Lintner Model.
Managers do not like big changes in dividend (signalling).
They smooth them - slow adjustment towards target payout rate.
Div t  Div t 1  K .(T . epst  Div t 1)
K is the adjustment rate. T is the target payout rate.
FIRM
K
EPS
Dividend Policy -Lintner Model
YEAR
50.00
A
B
0.5
DIV
C
0
DIV
1
DIV
Values
40.00
30.00
20.00
10.00
0.00
1
2
3
4
5
Years
6
7
8
1
2
3
4
5
6
7
8
30.00
34.00
28.00
25.00
29.00
33.00
36.00
40.00
13.25
15.13
14.56
13.53
14.02
15.26
16.63
18.31
11.50
11.50
11.50
11.50
11.50
11.50
11.50
11.50
15.00
17.00
14.00
12.50
14.50
16.50
18.00
20.00
177
Using Dividend Data to analyse Lintner Model.
Div t  (1  K ) Div t 1  K .T . epst .
In Excel, run the following regression;
Div t  a  bDiv t 1  cEpst
The parameters give us the following information,
a = 0, K = 1 – b, T = c/ (1 – b).
178
Dividends and earnings.
• Relationship between dividends, past,
current and future earnings.
• Regression analysis/categorical analysis.
179
Dividends V Share Repurchases.
• Both are payout methods.
• If both provide similar signals, mkt reaction
should be same.
• => mgrs should be indifferent between
dividends and repurchases.
180
Dividend/share repurchase
irrelevance
• Misconception (among practitioners) that
share repurchasing can ‘create’ value by
spreading earnings over fewer shares
(Kennon).
• Impossible in perfect world:
• Fairchild (JAF).
181
Dividend/share repurchase
irrelevance (continued)
• Fairchild: JAF (2006):
• => popular practitioner’s website argues
share repurchases can create value for nontendering shareholders.
• Basic argument: existing cashflows/assets
spread over fewer shares => P !!!
• Financial Alchemy !!!
182
The Example:….
•
•
•
•
•
•
Kennon (2005): Eggshell Candies Inc
Mkt value of equity = $5,000,000.
100, 000 shares outstanding
=> Price per share = $50.
Profit this year = £1,000,000.
Mgt upset: same amount of candy sold this
year as last: growth rate 0% !!!
183
Eggshell example (continued)
• Executives want to do something to make
shareholders money after the disappointing
operating performance:
• => One suggests a share buyback.
• The others immediately agree !
• Company will use this year’s £1,000,000
profit to but stock in itself.
184
Eggshell example (continued)
• $1m dollars used to buy 20,000 shares (at
$50 per share). Shares destroyed.
• => 80,000 shares remain.
• Kennon argues that, instead of each share
being 0.001% (1/100,000) of the firm, it is
now .00125% of the company (1/80)
• You wake up to find that P from $50 to
$62.50. Magic!
185
Kennon quote
• “When a company reduces the amount of
shares outstanding, each of your shares
becomes more valuable and represents a
greater % of equity in the company … It is
possible that someday there may be only 5
shares of the company, each worth one
million dollars.”
• Fallacy! CF: no such thing as a free lunch!
186
MM Irrelevance applied to Eggshell
example
At beginning of date 0:
N 0 (1  g )
V0 
g
At end of date 0, with N0 just achieved, but still in the
business (not yet paid out as dividends or repurchases:
N1 (1  g )
V0  N 0 
g
187
Eggshell figures
N1 (1  g )
1,000,000
V0  N 0 
 1,000,000 
 5,000,000
g

   0.25
Cost of equity will not change: only way to increase value
per share is to improve company’s operating performance, or
invest in new positive NPV project. Repurchasing shares is a
zero NPV proposition (in a PCM).
Eggshell has to use the $1,000,000 profit to but the shares.
188
Eggshell irrelevance (continued)
• Assume company has a new one-year zero
NPV project available at the end of date 0.
• 1. Use the profit to Invest in the project.
• 2. Use the profit to pay dividends, or:
• 3. Use the profit to repurchase shares.
189
Eggshell (continued)
1,000,000
 5,000,000  P  $50
0.25
1.
V0  1,000,000 
2.
1,000,000
V0 
 4,000,000  P  $40
0.25
Ex div
Each year –end: cum div = $50, ex div = $40
3.
1,000,000
V0 
 4,000,000  P  $50
0.25
190
Long-term effects of repurchase
• See tables in paper:
• Share value pre-repurchase = $5,000,000 each
year.
• Share value-post repurchase each year =
$4,000,000
• Since number of shares reducing, P .by 25%, but
this equals cost of equity.
• And is same as investing in zero NPV project.
191
Conclusion of analysis
• In PCM, share repurchasing cannot increase share
price (above a zero NPV investment) by merely
spreading cashflows over smaller number of
shares.
• Further, if passing up positive NPV to repurchase,
not optimal!
• Asymmetric info: repurchases => positive signals.
• Agency problems: FCF.
• Market timing.
• Capital structure motives.
192
Dividend/share repurchase
irrelevance
• See Fairchild (JAF 2005)
• Kennon’s website
193
Evidence.
• Mgrs think divs reveal more info than
repurchases (see Graham and Harvey
“Payout policy”.
• Mgrs smooth dividends/repurchases are
volatile.
• Dividends paid out of permanent
cashflow/repurchases out of temporary
cashflow.
194
Motives for repurchases
(Wansley et al, FM: 1989).
•
•
•
•
•
•
•
Dividend substitution hypothesis.
Tax motives.
Capital structure motives.
Free cash flow hypothesis.
Signalling/price support.
Timing.
Catering.
195
Repurchase signalling.
• Price Support hypothesis: Repurchases
signal undervaluation (as in dividends).
• But do repurchases provide the same signals
as dividends?
196
Repurchase signalling:
(Chowdhury and Nanda Model: RFS 1994)
• Free-cash flow => distribution as
commitment.
• Dividends have tax disadvantage.
• Repurchases lead to large price increase.
• So, firms use repurchases only when
sufficient undervaluation.
197
Open market Stock Repurchase
Signalling:
McNally, 1999
• Signalling Model of OM repurchases.
• Effect on insiders’ utility.
• If do not repurchase, RA insiders exposed to
more risk.
• => Repurchase signals:
• a) Higher earnings and higher risk,
• b) Higher equity stake => higher earnings.
198
Repurchase Signalling :
Isagawa FR 2000
• Asymmetric information over mgr’s private
benefits.
• Repurchase announcement reveals this info
when project is –ve NPV.
• Repurchase announcement is a credible
signal, even though not a commitment.
199
Costless Versus Costly Signalling:
Bhattacharya and Dittmar 2003
• Repurchase announcement is not
commitment.
• Costly signal: Actual repurchase: separation
of good and bad firm.
• Costless (cheap-talk): Announcement
without repurchasing. Draws analysts’
attention.
• Only good firm will want this
200
Repurchase timing
• Evidence: repurchase timing (buying shares
cheaply.
• But market must be inefficient, or investors
irrational.
• Isagawa.
• Fairchild and Zhang.
201
Repurchases and irrational
investors.
Isagawa 2002
• Timing (wealth-transfer) model.
• Unable to time market in efficient market
with rational investors.
• Assumes irrational investors => market
does not fully react.
• Incentive to time market.
• Predicts long-run abnormal returns postannouncement.
202
Repurchase Catering.
• Baker and Wurgler: dividend catering
• Fairchild and Zhang: dividend/repurchase
catering, or re-investment in positive NPV
project.
203
Competing Frictions Model:
From Lease et al:
Taxes
•
Low
Payout
Low Payout
Agency
Costs
High
Payout
High Payout
Asymmetric
Information
High
Low Payout
Payout
204
Dividend Cuts bad news?
•
•
•
•
•
•
•
•
•
Fairchild’s 2009/10 article.
Wooldridge and Ghosh:=>
ITT/ Gould
Right way and wrong way to cut dividends.
Other cases from Fairchild’s article.
Signalling/FCF hypothesis.
FCF: agency cost: cutting div to take –ve NPV project.
New agency cost: Project foregone to pay high dividends.
Communication/reputation important!!
205
Venture Capital/private
equity/Hedge Funds
• Venture capitalists typically supply start-up
finance for new entrepreneurs.
• VC’s objective; help to develop the venture over 5
– 7 years, take the firm to IPO, and make large
capital gains on their investment.
• In contrast, private equity firms invest in later
stage public companies to a) take them private:
Turnarouds, or b) Growth capital.
• Hedge Funds: Privately-owned institutions that
invest in Financial markets using a variety of
strategies.
206
Hedge Funds
• Privately-owned institutions
• Limited range of High net worth (wealthy)
investors => HF => invests in FMs
• Each fund has its own investment strategy
• Largely unregulated (in contrast to mutual
funds); => debate.
207
HF strategies
• HF mgr typically commits to a strategy, using
following elements
• Style
• Market
• Instrument
• Exposure
• Sector
• Method
• Diversification
208
HF Strategies (continued)
• Style: Global Macro, directional, event driven….
• Market: equity, fixed income, commodity,
currency
• Instrument: long/short, futures, options, swaps
• Exposure: directional, market neutral
• Sector: emerging markets, technology, healthcare
• Method: Discretionary/qualitative (mgr selects
investments): systematic/quantitative (quants)
209
Leverage:
• HFs are marketed on the promise of making
‘absolute returns’ regardless of mkt
• May involve hedging (long-short) plus high
levels of leverage
• => very risky?
• Risk-shifting incentives made worse by HF
mgr fee structure!
210
HF fee structure
• Asymmetric fees (in mutual fund,
symmetric or fulcrum fees).
• HF mgr gets a percentage of assets under
management plus a performance bonus on
the upside: no loss on the downside
(investor loses there!)
• => systemic risk? Regulation debate.
211
Fairchild and Puri (2011)
• Brand new paper on SSRN!
• HF mgr/ Investor negotiate (bargain) over form of
contract: asymmetric or symmetric)
• HF mgr then chooses safe or risky strategy.
• He then exerts effort in trying to make strategy
succeed.
• Paper looks at effects of BP and incetnives on
contract, strategy and HF performance and risk!
212
Activist HFs
• Passive HFs just invest in FMs, an d look at
portfolio decisions
• Activist HFs actually get involved in the
companies that they invest in
• Members on the board
• Assist/interfere in mgt decisions
• Debate: do they add or destroy value?
• Myopic?
213
Private Equity.
• PE firms generally buy poorly performing
publically listed firms.
• Take them private
• Improve them (turn them around).
• Hope to float them again for large gains
• Theory of private equity turnarounds” plus
PE leverage article, plus economics of PE
articles.
214
Theory of PE-turnarounds (Cuny and
Talmor JCF 2007)
• Explores advantage of PE in fixing
turnaround
• Would poorly performing mgrs want to
involve PEs when they may lose their jobs?
215
Venture capitalists
• Venture capitalists provide finance to start-up
entrepreneurs
• New, innovative, risky, no track-record…
• Hence, these Es have difficulty obtaining finance
from banks or stock market
• VCs more than just investors
• Provide ‘value-adding’ services/effort
• Double-sided moral hazard/Adverse selection
216
Venture capital process
• Investment appraisal stage: seeking out good
entrepreneurs/business plans: VC overconfidence?
• Financial contracting stage: negotiate over
cashflow rights and control rights.
• Performance stage: both E and VC exert valueadding effort: double-sided moral hazard.
• Ex post hold-up/renegotiation stage? Double
sided moral hazard
• => exit: IPO/trade sale => capital gains (IRR)
217
VC process (continued)
• VCs invest for 5-7 years.
• VCs invest in a portfolio of companies: anticipate
that some will be highly successful, some will not
• Value-adding? Visit companies, help them
operationally, marketing etc.
• Empirical evidence on hours/year spent at each
company
• => attention model of Gifford.
218
Venture Capital Financing
•
•
•
•
Active Value-adding Investors.
Double-sided Moral Hazard problem.
Asymmetric Information.
Negotiations over Cashflows and Control
Rights.
• Staged Financing
• Remarkable variation in contracts.
219
Features of VC financing.
• Bargain with mgrs over financial contract
(cash flow rights and control rights)
• VC’s active investors: provide value-added
services.
• Reputation (VCs are repeat players).
• Double-sided moral hazard.
• Double-sided adverse selection.
220
Kaplan and Stromberg
• Empirical analysis, related to financial
contract theories.
221
Financial Contracts.
•
•
•
•
Debt and equity.
Extensive use of Convertibles.
Staged Financing.
Control rights (eg board control/voting
rights).
• Exit strategies well-defined.
222
Game-theoretic models of Venture
Capitalist/entrepreneur contracting
• Double-sided moral hazard models (ex ante
effort/ ex post holdup/renegotiation/stealing) – self-interest
• Behavioural Models (Procedural justice,
fairness, trust, empathy)
223
Fairchild (JFR 2004)
• Analyses effects of bargaining power,
reputation, exit strategies and value-adding
on financial contract and performance.
• 1 mgr and 2 types of VC.
• Success Probability depends on effort:
P  eM   i eVC
where
 i {0,1},
=> VC’s valueadding.
224
Fairchild’s (2004) Timeline
• Date 0: Bidding Game: VC’s bid to supply
finance.
• Date 1: Bargaining game: VC/E bargain
over financial contract (equity stakes).
• Date 2: Investment/effort level stage.
• Date 3: Renegotiation stage: hold-up
problems
• Date 4: Payoffs occur.
225
Bargaining stage
• Ex ante Project Value
V  PR  (1  P).0  PR.
• Payoffs:
2
em
S M  PR  
.
2
2
eVC
SVC  (1   ) PR  
.
2
226
Optimal effort levels for given
equity stake:
•

em *  ,

 (1   )
eVC * 
.

227
Optimal equity proposals.
• Found by substituting optimal efforts into
payoffs and maximising.
• Depends on relative bargaining power, VC’s
value-adding ability, and reputation effect.
• Eg; E may take all of the equity.
• VC may take half of the equity.
228
Payoffs
 0
Dumb VC!
E
VC
0.5
Equity Stake
229
Tykvova’s review paper of VC
• Problem is: more equity E has, less equity
VC has: affects balance of incentives.
• Problem for VC is giving enough equity to
motivate E, while keeping enough for
herself
230
Ex post hold-up problem
• In Fairchild (2004): VC can force
renegotiation of equity stakes in her favour
after both players have exerted effort.
• She takes all of the equity
• How will this affect rational E’s effort
decision in the first place?
231
E’s choice of financier
•
•
•
•
Growing research on E’s choice of financier
VC versus banks
VC versus angels
VCs are formal funds with legal contracts
etc
• Angels are wealthy individuals, often ex
entrepreneurs, sometimes relations of the E!
232
Other Papers
• Casamatta: Joint effort: VC supplies
investment and value-adding effort.
• Repullo and Suarez: Joint efforts: staged
financing.
• Bascha: Joint efforts: use of convertibles:
increased managerial incentives.
233
E’s choice of financier
• VC or bank finance (Ueda, Bettignies and
Brander).
• VC or Angel (Chemmanur and Chen,
Fairchild).
• See slides on my paper….
234
Fairness Norms and Self-interest in VC/E
Contracting: A Behavioral Game-theoretic
Approach
• Existing VC/E Financial Contracting Models
assume narrow self-interest.
• Double-sided Agency problems (both E and VC
exert Value-adding Effort) (Casamatta JF 2003,
Repullo and Suarez 2004, Fairchild JFR 2004).
• Procedural Justice Theory: Fairness and Trust
important.
• No existing behavioral Game theoretic models of
VC/E contracting.
235
My Model:
• VC/E Financial Contracting, combining
double-sided Moral Hazard (VC and E
shirking incentives) and fairness norms.
• 2 stages: VC and E negotiate financial
contract.
• Then both exert value-adding efforts.
236
How to model fairness?
Fairness Norms.
• r Fair VCs and Es in society.
• 1  r self-interested VCs and Es in society.
• Matching process: one E emerges with a
business plan. Approaches one VC at
random for finance.
• Players cannot observe each other’s type.
237
Timeline
• Date 0: VC makes ultimatum offer of equity
stake to E;   [0,1],1  
• Date 1: VC and E exert value-adding effort
in running the business
• Date 2 Success Probability P   E eE   E eVC
• => income R.
• Failure probability 1  P
• =>income zero
238
• Expected Value of Project
V  PR  ( E eE   E eVC ) R
  [0,1]
• Represents VCs relative ability (to E).
239
Fairness Norms
• Fair VC makes fair (payoff equalising)
equity offer  F
• Self-interested VC makes self-interested
ultimatum offer U   F
• E observes equity offer. Fair E compares
equity offer to social norm. Self-interested
E does not, then exerts effort.
240
Expected Payoffs
•
E  U PR  eE  r(F  U ) PR
2
VC  r[(1  U ) PS R]  (1  r)[(1  U ) PF R]  eVC
If VC is fair, by definition,
2
U   F
241
Solve by backward induction:
•
•
•
•
•
If VC is fair;
Since U   F
 E   F PR  eE
2
for both E types.
=> PS  PF
=>   (1   ) PR  e 2
VC
F
VC
242
VC is fair; continued.
• Given U   F
Optimal Effort Levels:
 F E R
(1   F ) E R
eE * 
, eVC * 
.
2
2
Fair VC’s equity proposal (equity norm):
1  2 2  1   4   2
F 
3(1   2 )
243
VC is self-interested:
U   F  PS  PF
• From Equation (1), fair E’s optimal effort;
•
[U  r ( F  U )] E R
eE * 
.
2
244
Self-interested VC’s optimal
Equity proposal
• Substitute players’ optimal efforts into V=
PR, and then into (1) and (2). Then, optimal
equity proposal maximises VC’s indirect
payoff =>
1    r (1   F )
U * 
.
2
2
2(1  r )  
2
2
245
Examples;
• VC has no value-adding ability (dumb
money) =>
2
•   0 =>  F 
3
•
1
• r =0 => U  .
2
2
• r => 1 , U   F  3 .
246
Example 2
• VC has equal ability to E;
1
=>
 1
F 
2
• r =0 => U  0.
1
• r => 1 , U   F  .
2
• We show that   [0,1],
U   F
as r => 1
247
VCs
Equity
offer
1
•
Fairness
0
248
Firm
Value
•
Fairness
0
249
8. Behavioural Corporate Finance.
•Standard Finance - agents are rational and selfinterested.
•Behavioural finance: agents irrational
(Psychological Biases).
•Irrational Investors – Overvaluing assetsinternet bubble? Market Sentiment?
•Irrational Managers- effects on investment
appraisal?
•Effects on capital structure?
•Herding.
250
Development of Behavioral Finance I.
• Standard Research in Finance: Assumption:
Agents are rational self-interested utility
maximisers.
• 1955: Herbert Simon: Bounded Rationality:
Humans are not computer-like infinite
information processors. Heuristics.
• Economics experiments: Humans are not
totally self-interested.
251
Development of Behavioral Finance II.
•
•
•
•
•
Anomalies: Efficient Capital Markets.
Excessive volatility.
Excessive trading.
Over and under-reaction to news.
1980’s: Werner DeBondt: coined the term
Behavioral Finance.
• Prospect Theory: Kahnemann and Tversky
1980s.
252
Development III
• BF takes findings from psychology.
• Incorporates human biases into finance.
• Which psychological biases? Potentially
infinite.
• Bounded rationality/bounded
selfishness/bounded willpower.
• Bounded rationality/emotions/social factors.
253
Potential biases.
•
•
•
•
•
•
•
•
Overconfidence/optimism
Regret.
Prospect Theory/loss aversion.
Representativeness.
Anchoring.
Gambler’s fallacy.
Availability bias.
Salience….. Etc, etc.
254
Focus in Literature
• Overconfidence/optimism
• Prospect Theory/loss aversion.
• Regret.
255
Prospect Theory.
U
Risk-averse in
gains
W
Eg: Disposition Effect:
Risk-seeking in losses
Sell winners too quickly.
Hold losers too long.
256
Overconfidence.
• Too much trading in capital markets.
• OC leads to losses?
• But : Kyle => OC traders out survive and
outperform well-calibrated traders.
257
Behavioral Corporate Finance.
• Much behavioral research in Financial
Markets.
• Not so much in Behavioral CF.
• Relatively new: Behavioral CF and
Investment Appraisal/Capital
Budgeting/Dividend decisions.
258
Forms of Irrationality.
a) Bounded Rationality (eg Mattson and Weibull 2002, Stein
1996).
- Limited information: Information processing has a cost of
effort.
- Investors => internet bubble.
b) Behavioural effects of emotions:
-Prospect Theory (Kahneman and Tversky 1997).
-
Regret Theory.
-
Irrational Commitment to Bad Projects.
-
Overconfidence.
C) Catering – investors like types of firms (eg high dividend). 259
Bounded rationality (Mattson and Weibull 2002).
-Manager cannot guarantee good outcome with probability of 1.
-Fully rational => can solve a maximisation problem.
-Bounded rationality => implementation mistakes.
-Cost of reducing mistakes.
-Optimal for manager to make some mistakes!
-CEO, does not carefully prepare meetings, motivate and monitor
staff => sub-optimal actions by firm.
260
Regret theory and prospect theory (Harbaugh 2002).
-Risky decision involving skill and chance.
-manager’s reputation.
Prospect theory: People tend to favour low success probability
projects than high success probability projects.
-Low chance of success: failure is common but little reputational
damage.
-High chance of success: failure is rare, but more embarrassing.
Regret theory: Failure to take as gamble that wins is as
embarrassing as taking a gamble that fails.
=> Prospect + regret theory => attraction for low probability
gambles.
261
Irrational Commitment to bad project.
-Standard economic theory – sunk costs should be ignored.
-Therefore- failing project – abandon.
-But: mgrs tend to keep project going- in hope that it will improve.
-Especially if manager controlled initial investment decision.
-More likely to abandon if someone else took initial decision.
262
Real Options and behavioral aspects of ability to revise (Joyce
2002).
-Real Options: Flexible project more valuable than an inflexible
one.
-However, managers with an opportunity to revise were less
satisfied than those with standard fixed NPV.
263
Overconfidence and the Capital Structure (Heaton 2002).
-Optimistic manager overestimates good state probability.
-Combines Jensen’s free cashflow with Myers-Majluf Assymetric
information.
-Jensen- free cashflow costly – mgrs take –ve NPV projects.
-Myers-Majluf- Free cashflow good – enables mgs to take +ve
NPV projects.
-Heaton- Underinvestment-overinvestment trade-off without
agency costs or asymmetric info.
264
Heaton (continued).
-Mgr optimism – believes that market undervalues equity =
Myers-Majluf problem of not taking +ve NPV projects => free
cash flow good.
-But : mgr optimism => mgr overvalues the firms investment
opportunities => mistakenly taking –ve NPV project => free cash
flow bad.
-Prediction: shareholders prefer:
-Cashflow retention when firm has both high optimism and good
investments.
- cash flow payouts when firm has high optimism and bad
investments.
265
Rational capital budgeting in an irrational world. (Stein 1996).
-Manager rational, investors over-optimistic.
- share price solely determined by investors.
-How to set hurdle rates for capital budgeting decisions?
- adaptation of CAPM, depending on managerial aims.
- manager may want to maximise time 0 stock price (short-term).
-May want to maximise PV of firm’s future cash flows (long term
rational view).
266
Effect of Managerial overconfidence, asymmetric Info, and
moral hazard on Capital Structure Decisions.
Rational Corporate Finance.
-Capital Structure: moral hazard + asymmetric info.
-Debt reduces Moral Hazard Problems
-Debt signals quality.
Behavioral Corporate Finance.
-managerial biases: effects on investment and financing decisions
-Framing, regret theory, loss aversion, bounded rationality.
-OVERCONFIDENCE/OPTIMISM.
267
Overconfidence/optimism
• Optimism: upward bias in probability of
good state.
• Overconfidence: underestimation of asset
risk.
• My model =>
• Overconfidence: overestimation of ability.
268
Overconfidence: good or bad?
• Hackbarth (2002): debt decision: OC good.
• Goel and Thakor (2000): OC good: offsets
mgr risk aversion.
• Gervais et al (2002), Heaton: investment
appraisal, OC bad => negative NPV
projects.
• Zacharakis: VC OC bad: wrong firms.
269
Overconfidence and Debt
• My model: OC => higher mgr’s effort
(good).
• But OC bad, leads to excessive debt (see
Shefrin), higher financial distress.
• Trade-off.
270
Behavioral model of overconfidence.
pˆ  p, qˆ  q.
Both Managers issue debt:
2 pˆ I
M g  pˆ R 
 (1  pˆ )b.
pq
2qˆI
M b  qˆR 
 (1  qˆ )b.
pq
271
Good mgr issues Debt, bad mgr issues equity.
pˆ
M g  pˆ R  I  (1  pˆ )b.
p
qˆ
M b  qˆR  I .
q
Both mgrs issue equity.
2 pˆ
M g  pˆ R 
I,
pq
2qˆ
M b  qˆR 
I.
pq
272
Proposition 1.
a) If
qˆ ( p  q)
I  (1  qˆ )b  (1  pˆ )b,
q( p  q )
{S g  Sb  D}.
b)
qˆ ( p  q)
(1  qˆ )b 
I  (1  pˆ )b,
q( p  q )
{S g  D, Sb  E}.
c)
qˆ ( p  q)
(1  qˆ )b  (1  pˆ )b 
I,
q( p  q )
{S g  Sb  E}.
Overconfidence leads to more debt issuance.
273
Overconfidence and Moral
Hazard
•
•
•
•
•
•
Firm’s project: 2 possible outcomes.
Good: income R. Bad: Income 0.
Good state Prob: P  (    )e  (0,1].
True:
  0.
Overconfidence:
  0.
True success prob: P  e.
274
Manager’s Perceived Payoffs
2
ˆ
ˆ
ˆ
M D  P( R  D )  (1  P )b  e  PD  I .
2
ˆ
ˆ
M E  PR  e  (1   ) PR  I .
275
Optimal effort levels
(   )( R  D  b)
eD * 
2
(   )( R  D )
eE * 
2
276
Effect of Overconfidence and
security on mgr’s effort
• Mgr’s effort is increasing in OC.
• Debt forces higher effort due to FD.
277
Manager’s perceived Indirect
Payoffs
2
2
(



)
(
R

D

b
)
 (   )( R  D  b) D
ˆ
MD 

 I b
4
2
2
2
(



)
(
R

D
)
 (   )( R  D) D
ˆ
ME 

I
4
2
2
2
(



)
(
2
b
(
R

D
)

b
)  (   )bD
ˆ
M D 

 b.
4
2
278
True Firm Value
 (   )( R  D  b)( R  b)
VD  PD ( R  b)  b 
 b.
2
 (   )( R  D ) R
VE  PE R 
.
2
279
Effect of OC on Security Choice
2
2
2

(
2
b
(
R

I
)

b
)

bD
ˆ
M D (  0) 

b 0
4
2
Mˆ D
0


 Mˆ D (   C )  0.
  [0,  C ],
  C,
Manager issues Equity.
Manager issues Debt.
280
Effect of OC on firm Values
2 ( R  D) R
VE (  0) 
.
2
 (   )( R  D  b)( R  b)
VD (   C ) 
 b.
2
(2   )( 2bR  Db  b2 )  R( R  D)
VD 
b
2
281
Results
•
•
•
•
•
•
•
For given security: firm value increasing in OC.
If VD (   C )  0,
Firm value increasing for all OC: OC good.
Optimal OC:  *   max .
If VD (   C )  0,
Medium OC is bad. High OC is good.
Or low good, high bad.
282
Results (continued).
• If
VD (   C )  0,
• 2 cases: Optimal OC:  *   max .
•
• Or Optimal OC:  *   C   .
283
Effect of Overconfidence on Firm Value
1200
1000
800
Value
600
400
200
0
0
-200
0.1
0.2
0.3
0.4
Effect of Overconfidence on Firm Value
0.5
-400
2000
-600
1500
Overconfidence
1000
Value
500
Effect of Overconfidence on Firm Value
-500
2500
Value
0
2000
-1000
1500
-1500
1000
-2000
500
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Overconfidence
0
-500
1
2
3
4
5
6
7
8
9
10
-1000
-1500
-2000
Overconfidence
284
0.9
Conclusion.
•
•
•
•
Overconfidence leads to higher effort level.
Critical OC leads to debt: FD costs.
Debt leads to higher effort level.
Optimal OC depends on trade-off between
higher effort and expected FD costs.
285
Future Research
•
•
•
•
•
•
•
Optimal level of OC.
Include Investment appraisal decision
Other biases: eg Refusal to abandon.
Regret.
Emotions
Hyperbolic discounting
Is OC exogenous? Learning.
286
Overconfidence and life-cycle debt
•
287
Reverse effect of OC on debt in
China?
•
288
Herding
289
Hyperbolic Discounting
290
9. Emotional Finance
• Fairchild’s Concorde case study.
291