1 MN20211: Corporate Finance 2009/10: 1.Revision: Investment Appraisal, Portfolio, CAPM (AB). 2....

1

MN20211: Corporate Finance 2009/10:

1. Revision: Investment Appraisal, Portfolio, CAPM (AB).

2. Investment flexibility, Decision trees, Real Options (RF).

3. Funding (AB)

4. Capital Structure and Value of the Firm (RF).

5. Optimal Capital Structure - Agency Costs, Signalling (RF).

6. Dividend policy/repurchases (RF)

7. Mergers and Acquisitions (AB).

8. Venture Capital and Private Equity (RF).

9. Intro to Behavioural Finance (RF).

10. Revision.

2

RF’s Lectures

• Week 3: Investment flexibility/Real Options

• Week 5: Capital Structure/Dividends

• Week 6: Capital Structure/Dividends

• Week 9: Venture Capital and Private Equity

• Week 10: Introduction to BF/BCF.

• Week 11 Revision

3

Lecture 3: 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• Monte Carlo.• Real Options

4

Lecture 3: 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.

5

$000 Year 1 Year 2 - 6

Revenues 6000Variable Costs -3000Fixed Costs -1791Depreciation -300

Pretax Profit 909Tax (34%) -309

Net Profit 600Cashflow 900

Initial Investment -1500

Date 1 NPV = -1500 +

6

2 )15.1(

900

tt

= 1517

Production Stage: Base Case

6

Decision Tree.

Test

Do Not Test

Success

Failure

Invest

Do not Invest

Do not Invest

Invest

NPV = 1517

NPV = 0

NPV = -3611

Date 0: -$100 Date 1: -1500

Solve backwards: If the tests are successful, SEC should invest, since 1517 > 0.

If tests are unsuccessful, SEC should not invest, since 0 > -3611.

P=0.75

P=0.25

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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 + 15.1

1138 = $890

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).

8

Sensitivity Analysis.

- NPV Calculation for all 3 possibilities of a single variable + expected forecast for all other variables.

NPV Expected Pessimistic or Best Optimistic

Market Size -1802 1517 8154Market Share -696 1517 5942Price 853 1517 2844Variable Cost 189 1517 2844Fixed Cost 1295 1517 1628Investment 1208 1517 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.

9

Real Options.

A digression: Financial Options

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.

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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!

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Factors Affecting Price of European Option (=c).

-Underlying Stock Price S.

-Exercise Price X.

-Variance of of the returns of the underlying asset ,

-Time to maturity, T.

.0,0,0,02

T

cc

X

c

S

c

2

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.

12

Options: Payoff Profiles.

Buying a Call Option.

S

WSelling a put option.

Selling a Call Option. Buying a Put Option.

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Pricing Call Options – Binomial Approach.

S=20

q

1- q dS=13.40

uS=24.00

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 payoffs are the same in both states of nature (13.40): Risk free.

cq

1- q

Cu = 3

Cd=0

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Since hedge portfolio is riskless:

.))(1( uf mcuSmcSr

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.

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Alternative option-pricing method

• Black-Scholes

• Continuous Distribution of share returns (not binomial)

• Continuous time (rather than discrete time).

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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).

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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.

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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.

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Types of Real Option

• Option to Delay (Timing Option).

• Option to Expand (eg R and D).

• Option to Abandon.

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Option to Delay (= call option)

•

Project value

Value-creation

Investment in waiting:

(sunk)

21

Option to expand (= call option)

•

Project value

Value creation

Investment in initial project: eg R and D (sunk)

22

Option to Abandon ( = put option)

•

Project value

Project goes badly: abandon for liquidation value.

23

Valuation of Real Options

• Binomial Pricing Model

• Black-Scholes formula

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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.

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•

Simplified Examples

• Option to Expand (page 241 of RWJ)

Build First Ice

Hotel

If Successful

Expand

If unsuccessful

Do not Expand

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• 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?

Option to Expand (Continued)

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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.

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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.

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Option to delay and Competition (Smit and Ankum).

•-Smit and Ankum present a binomial real option model:

•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).

•Protecting Economic Rent: Innovation, barriers to entry, product differentiation, patents.

•Firm needs too identify extent of competitive advantage.

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Option to delay versus competition: Game-theoretic approach

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

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Option to delay versus competition: effects of legal system

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

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Monte Carlo methods

• BBQ grills example in RWJ.

• Application to Qinetiq (article by Tony Bishop).

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Use of Real Options in Practice

•

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Lecture 5 and 6: Capital Structure and Dividends.

Positive NPV project immediately increases current equity value (share price immediately goes up!)

oo EBV Pre-project announcement

New project: .IVNPV n INew capital (all equity)

I

Value of Debt oBIVE n 0

New Firm Value

Original equity holders

New equity

nVV

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Example:

oo EBV =500+500=1000.

I

IVNPV n 60 -20 = 40.

oB = 500.

IVE n 0 = 500+40 = 540

I = 20

nVV =1000+60=1060.

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Value of Debt

Original Equity

New Equity

Total Firm Value

36

Positive NPV: Effect on share price.

Assume all equity.

Market No of Price per Market No of Price per£K Value Shares Share Value Shares Share

Current 1000 1000 1 1040 1000 1.04

New Project 20 19 1.04

Project Income 60 1060 1019 1.04

Required Investment 20

NPV 40

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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).

38

Value of the Firm = discounted value of future cashflows available to the providers of capital.

-Assume Incomes are perpetuities.

Miller- Modigliani Theorem:

..)1(

.

)1(

d

dDEUL

EU

K

Bk

eK

NIVV

WACC

TNCFBTVV

VTNCF

V

Irrelevance Theorem: Without Tax, Firm Value is independent of the Capital Structure.

Note that ed KequitytKdebtWACC *%)1(*%

39

K

D/E

K

D/E

V

D/E D/E

V

Without Taxes With Taxes

40

Examples

• Firm X

• Henderson Case study

41

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

42

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.

43

Combining Tax Relief and Debt Capacity (Traditional View).

D/E D/E

V

K

44

Section 4: 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.

45

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

46

Jensen and Meckling (1976)

B

V

V*

V1

B1

A

If manager owns all of the equity, equilibrium point A.

Slope = -1

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B

V

Jensen and Meckling (1976)

V*

V1

B1

AB

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.

Slope = -1

Slope = -1/2

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B

V

Jensen and Meckling (1976)

V*

V1

B1

AB

C

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.

V2

B2

Slope = -1

Slope = -1/2

49

Jensen and Meckling - Numerical Example.PROJECT PROJECTA B

EXPECTED INCOME 500 1000

MANAGER'S SHARE:100% 500 1000

VALUE OF PRIVATE 800 500BENEFITS

TOTAL WEALTH 1300 1500

MANAGER'S SHARE:50% 250 500

VALUE OF PRIVATE 800 500BENEFITS

TOTAL WEALTH 1050 1000

Manager issues 100% Debt.

Chooses Project B.

Manager issues some Debt and Equity.

Chooses Project A.

Optimal Solution: Issue Debt?

50

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

Values: Debt 50 25

Equity 50 60

51

OPTIMAL CAPITAL STRUCTURE.

Trade-off: Increasing equity => excess perks.

Increasing debt => potential risk shifting.

Optimal Capital Structure => max firm value.

D/E

V

D/E*

V*

52

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).

53

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)?

54

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.

55

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.

56

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.

57

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.

58

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 the optimal contract?

59 

  Conflict Benefits of Debt Costs of Debt

Breaking MM   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.

60

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.”

61

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

DVCVVrM

DVVVrM

11100

11100

if )1(

if )1(

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.

62

Myers-Majluf (1984).

-managers know the true future cashflow.

They act in the interest of initial shareholders.P = 0.5 Do

Nothing:

Good Bad

IssueEquity

Good BadAssetsin Place

250 130 350 230

NPV ofnewproject

0 0 20 10

Value ofFirm

250 130 370 240

Expected Value 190 305

New investors 0 100

Old Investors 190 205

63

Consider old shareholders wealth:

Good News + Do nothing = 250.

Good News + Issue Equity =

Bad News and do nothing = 130.

.69.248)370(305

205

Bad News and Issue equity = .31.161)240(305

205

64

Donothing

Issueandinvest

GoodNews

250 * 248.69

BadNews

130 161.31*

Old Shareholders’ payoffs EquilibriumDonothing

Issueandinvest

GoodNews

250 * 248.69

BadNews

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.

65

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.

66

Practical Methods employed by Companies (See Damodaran; Campbell and Harvey).

-Trade off models: PV of debt and equity.

-Pecking order.

-Benchmarking.

-Life Cycle.

time

Increasing Debt?

67

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

68

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?)

69

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.

70

Garvey and Hanka (contiuned)

•

D/E

D/E*

V Trade-off: Tax shields/effort levels/FCF/ efficiency/signalling Vs financial distress

71

Practical Capital Structure: case study

•

72

Lecture 6: Dividend Policy

• Miller-Modigliani Irrelevance.

• Gordon Growth (trade-off).

• Signalling Models.

• Agency Models.

• Gordon Growth (trade-off).

• Lintner Smoothing.

• Dividends versus share repurchases.

73

Early Approach.

• Three Schools of Thought-

• Dividends are irrelevant.

• Dividends => increase in stock prices.

• Dividends => decrease in Stock Prices.

74

A. Dividend Irrelevance.

Assume All equity firm.

Value of Firm = Value of Equity = discounted value of future cashflows available to equity holders = discounted value of dividends (if all available cashflow is paid out).

0

0

0

0

)1(

)1(

tt

t

tt

INCFV

DivV

t

t

If everything not reinvested is paid out as dividends, then

75

Miller Modigliani’s Dividend Irrelevance.

NSDivINCF

DivINSNCF

tttt

tttt

Source of Funds = Application of Funds

MM used a source and application of funds argument to show thatDividend Policy is irrelevant:

11

0)1()1( t

ttt

tt

tt INCFNSDivV

76

1

0)1(t

ttt INCF

V

-Dividends do not appear in the equation.

-If the firm pays out too much dividend, it issues new equity to be able to reinvest. If it pays out too little dividend, it can use the balance to repurchase shares.

-Hence, dividend policy irrelevant.

-Key is the availability of finance in the capital market.

77

Example of Dividend Irrelevance using Source and Application of Funds.

Firm invests in project giving it NCF = 100 every year, and it needs to re-invest, I =50 every year.

Cashflow available to shareholders = NCF – I = 50.

Now, NCF – I = Div – NS = 50.

If firm pays dividend of 50, NS = 0 (ie it pays out exactly the cashflow available – no new shares bought or sold).

If firm pays dividend of 80, NS = -30 (ie it sells new shares of 30 to cover dividend).

If firm pays dividend of 20, NS = 30 (ie it uses cashflow not paid out as dividend to buy new shares).

In each case, Div – NS = 50.

78

Dividend irrelevance (from Lease et al book chapter 2

• Appendix 2a.

79

B. Gordon Growth Model.

Where does growth come from?- retaining cashflow to re-invest.

.)1(11

0Kr

KNCFg

DivV

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.

80

Example of Gordon Growth Model.£K 19x5 19x6 19x7 19x8 19x9 Average Profits After Tax (NCF) 2500 2760 2635 2900 3100Retained Profit (NCF.K) 1550 1775 1600 1800 1900

Dividend (NCF(1-K)) 950 985 1035 1100 1200

Share Capital + retentionsB/F 30000 31550 33325 34925 36725C/F (= BF + Retained Profit) 31550 33325 34925 36725 38625

Retention Rate K 0.62 0.64 0.61 0.62 0.61 0.62r on opening capital 0.083 0.087 0.079 0.083 0.084 0.083

g = Kr = 0.05.

How do we use this past data for valuation?

81

Gordon Growth Model (Infinite Constant Growth Model).

Let %12

05.012.0

1260)05.1(1200)1( 100

gg

Div

g

gDivV

= 18000

82

Finite Supernormal Growth.

-Rate of return on Investment > market required return for T years.

-After that, Rate of Return on Investment = Market required return.

)1(

)(.. 1

10

rTNCFK

NCFV

If T = 0, V = Value of assets in place (re-investment at zero NPV).

Same if r = .

83

Examples of Finite Supernormal Growth.

%.10

.1001

NCF

T = 10 years. K = 0.1.

A. Rate of return, r = 12% for 10 years,then 10% thereafter.

1018)1.01(1.0

)1.012.0(10).100.(1.0

1.0

1000

V

B. Rate of return, r = 5% for 10 years,then 10% thereafter.

955)1.01(1.0

)1.005.0(10).100.(1.0

1.0

1000

V

84

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.

85

Div - NS - E (Div - NS) = NCF - I - E (NCF - I)

= NCF - E ( NCF).

Unexpected dividend increase - favourable signal of NCF.

Prob 0.5 0.5

Firm A Firm B E(V)

NCF 400 1400 900

New Investment 600 600 600

Dividend 0 800 400New shares 200 0 100

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).

86

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.

87

Dividends as signals of expected cashflows: Bhattacharya 1979.

• Asymmetric Info about cashflows.

• Investors invest over short horizons.

• Dividends taxed at higher rate than capital gains.

• => signalling equilibria.

• Shorter horizon => higher dividends.

88

Signalling, FCF, and Dividends.Fuller and Thakor (2002)

• Empirical Contest between Signalling and FCF hypotheses.

• Divs’ costly signals: signalling plus FCF.

• If dividend too low: FCF problem (cf Jensen 1986).

• If dividend too high: costly borrowing.

89

Fuller and Thakor (continued).

• 2 types of firm: good and bad.

• Good firm’s future

• Bad firm’s future

}.,{ LHCF

}.0,{LCF

qBLxGHx )/Pr()/Pr(

qBxGLx 1)/0Pr()/Pr(

90

Fuller and Thakor (continued)

• At date 1, outsiders observe signal

• If firm G,

• If firm B,

• Thus, if or mkt knows firm type. Divs used to eliminate FCF.

• If mkt cannot identify type. Thus, divs used to signal type and eliminate FCF.

},,0{ HLS

},{ HLS

},0{ LS

HS ,0S

,LS

91

Fuller and Thakor (continued)

• Firms’ dividend announcement trades-off costly borrowing versus FCF problem.

• Bayesian updating.

divmediumHS .divlowS .0

divHighgoodfirmLS .,

divlowbadfirmLS .,

92

Dividend Signalling: Current Income/future Investment:

Fairchild (2009/10).

• Conflicting signals:

• High/low dividends signal high/low income

• But high/low dividends affect ability to re-invest (cf Gordon Growth)

• If –ve NPV: FCF: High divs good.

• But if +ve NPV: high div bad => ambiguous.

93

Fairchild (2002): continued.

• 2 all-equity firms; manager• Date 0: Project investment.• Date 1: Net income, with• Revealed to the manager, but not to

investors.• Mkt becomes aware of a new project P2,

with return on equity• Manager commits to a dividend

}.,{ bgi

,iN .bg NN

.0,0

iD

94

Fairchild (2002) continued

• Date 1.5: Mgr pays announced dividend

• P2 requires investment

• Mgr cannot take new project.

• Date 2, If P2 taken, achieves net income. Mgr has private benefits

].,( gb NNI

b

.0b

95

Fairchild (2002) continued

• Mgr maximises

• Bayesian Updating.

• Adverse selection:

• Mgr can either signal current income (but no re-investment),

• or re-invest (without signaling current income).

.1 BVM

.bg NIN

g

96

Fairchild (2002) continued

• Signalling (of current income) Equilibria:

• A) Efficient re-investment: Pooling:

• B) Inefficient Non re-investment, or

• C) Efficient Non re-investment: separating:

].,0[],,0[ INDIND gbgg

].,0[],,[ bbgbg NDNND

97

Fairchild 2002 (continued)

• Case 2: Moral Hazard:• Mgr can provide credible signal of type• Effective communication (Wooldridge and Ghosh)• Now, use divs only due to FCF.• Efficient re-investment.• Inefficient re-investment.• Efficient non re-investment.

98

Fairchild 2002: Summary

• Case 1: Adverse selection: inefficiency when mgr refuses to cut dividend to take +ve NPV project.

• Case 2: Moral hazard: mgr reduces dividend to take –ve NPV project.

• Integrated approach: Effective mgrl communication/ increase mgr’s equity stake.

99

Agency Models.

• Jensen’s Free Cash Flow (1986).

• Stultz’s Free Cash Flow Model (1990).

• Easterbrook.

• Fairchild (2009/10): Signalling + moral hazard.

100

D. Lintner Model.

Managers do not like big changes in dividend (signalling).

They smooth them - slow adjustment towards target payout rate.

)..( 11 DivepstTKDivDiv ttt K is the adjustment rate. T is the target payout rate.

Dividend Policy -Lintner Model

0.00

10.00

20.00

30.00

40.00

50.00

1 2 3 4 5 6 7 8

Years

Va

lue

s

FIRM A B CK 0.5 0 1

YEAR EPS DIV DIV DIV

1 30.00 13.25 11.50 15.002 34.00 15.13 11.50 17.003 28.00 14.56 11.50 14.004 25.00 13.53 11.50 12.505 29.00 14.02 11.50 14.506 33.00 15.26 11.50 16.507 36.00 16.63 11.50 18.008 40.00 18.31 11.50 20.00

101

Using Dividend Data to analyse Lintner Model.

In Excel, run the following regression;

ttt cEpsbDivaDiv 1

...)1( 1 epstTKDivKDiv tt

The parameters give us the following information,

a = 0, K = 1 – b, T = c/ (1 – b).

102

Dividends and earnings.

• Relationship between dividends, past, current and future earnings.

• Regression analysis/categorical analysis.

103

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.

• Compare with stochastic time path to determine smoothing policy.

104

Deterministic Dividend Policy.

• Recall

•

• Solving

• We obtain optimal retention ratio

•

.)1)(1(01

0Kr

KrKNg

DivV

,00

K

V

.)1)((

*r

rK

105

Analysis of

• If

• If with

• Constant r over time => Constant K* over time.

*K

],1

,0[

r .0* K

],1

,0[

r ],1,0[*K .0*

r

K

106

Deterministic Case (Continued).

• Recursive solution:t

t rKKND )*1*)(1(0

.*

)*1*)(1( 10

rK

rKKNV

t

t

When r is constant over time, K* is constant. Net Income, Dividends, and firm value evolve deterministically.

107

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.

108

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.

109

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).

110

Dividend/share repurchase irrelevance

• See Fairchild (JAF 2005)

• Kennon’s website

111

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.

112

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.

113

Repurchase signalling.

• Price Support hypothesis: Repurchases signal undervaluation (as in dividends).

• But do repurchases provide the same signals as dividends?

114

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.

115

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.

116

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.

117

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

118

Repurchase timing

• Evidence: repurchase timing (buying shares cheaply.

• But market must be inefficient, or investors irrational.

• Isagawa.

• Fairchild and Zhang.

119

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 post-

announcement.

120

Repurchase Catering.

• Baker and Wurgler: dividend catering

• Fairchild and Zhang: dividend/repurchase catering, or re-investment in positive NPV project.

121

Competing Frictions Model:From Lease et al:

•

Asymmetric Information

Agency Costs

High

Payout

Low

Payout

Taxes

High Payout

Low Payout

High PayoutLow Payout

122

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!!

123

Lecture 9: Venture Capital/private equity

• 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 take them private….

124

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• Our main focus in this course is venture capital,

But will look briefly at PE later.• “Theory of private equity turnarounds” plus PE

leverage article, plus economics of PE articles.

125

C. 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.

126

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.

127

Kaplan and Stromberg

• Empirical analysis, related to financial contract theories.

128

Financial Contracts.

• Debt and equity.

• Extensive use of Convertibles.

• Staged Financing.

• Control rights (eg board control/voting rights).

• Exit strategies well-defined.

129

Fairchild (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:

VCiM eeP

},1,0{iwhere => VC’s value-adding.

130

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.

131

Bargaining stage

• Ex ante Project Value

• Payoffs:.)1( RPPRV

.2

)()(2

mM

eIRIRPS

).Pr(2

)()()1(2

IRe

IRIIRPS mVC

132

Optimal effort levels for given equity stake:

•

,*

me

.)1(

* r

eVC

133

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.

134

Equity Stake

Payoffs

E

VC

0.5

135

E’s choice of VC or angel-financing

• Explain Angels.

• Complementary efforts

• Ex post hold-up/stealing threat

136

To come

• Legal effects: (Fairchild and Yiyuan)

• => Allen and Song

• => Botazzi et al

• Negative reciprocity/retaliation.

137

Ex post hold-up threat

• VC power increases with time.

• Exit threat (moral hazard).

• Weakens entrepreneur incentives.

• Contractual commitment not to exit early.

• => put options.

138

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.

139

Complementary efforts (Repullo and

Suarez).

• Lecture slides to follow…

140

Control Rights.

• Gebhardt.

• Lecture slides to follow

141

Asymmetric Information

• Houben.

• PCP paper.

• Tykvova (lock-in at IPO to signal quality).

142

E’s choice of financier

• VC or bank finance (Ueda, Bettignies and Brander).

• VC or Angel (Chemmanur and Chen, Fairchild).

143

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.

144

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.

145

How to model fairness? Fairness Norms.

• Fair VCs and Es in society.

• 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.

rr1

146

Timeline

• Date 0: VC makes ultimatum offer of equity stake to E;

• Date 1: VC and E exert value-adding effort in running the business

• Date 2 Success Probability• => income R.• Failure probability • =>income zero

1],1,0[

VCEEE eeP

P1

147

• Expected Value of Project

• Represents VCs relative ability (to E).

ReePRV VCEEE )(

]1,0[

148

Fairness Norms

• Fair VC makes fair (payoff equalising) equity offer

• Self-interested VC makes self-interested ultimatum offer

• E observes equity offer. Fair E compares equity offer to social norm. Self-interested E does not, then exerts effort.

F

FU

149

Expected Payoffs

• PRrePR UFEUE )(2

2])1)[(1(])1[( VCFUSUVC eRPrRPr

If VC is fair, by definition, FU

150

Solve by backward induction:

• If VC is fair;

• Since

• for both E types.

• =>

• =>

FU 2

EFE ePR FS PP

2)1( VCFVC ePR

151

VC is fair; continued.

• Given FU

Optimal Effort Levels:

.2

)1(*,

2*

R

eR

e EFVC

EFE

Fair VC’s equity proposal (equity norm):

)1(3

1212

242

F

152

VC is self-interested:

• From Equation (1), fair E’s optimal effort;

•

FSFU PP

.2

)]([*

Rr

e EUFUE

153

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(2

)1(1*

22

22

r

r FU

154

Examples;

• VC has no value-adding ability (dumb money) =>

• =>

•

• r =0 =>

• r => 1 ,

0 3

2F

.2

1U

.3

2 FU

155

Example 2

• VC has equal ability to E; =>

• r =0 =>• r => 1 ,

• We show thatas r => 1

12

1F

.0U

.2

1 FU

],1,0[ FU

156

Table 1.

157

Graph

158

Table of venture performance

159

Graph of Venture Performance.

160

Future Research.

• Dynamic Fairness Game:ex post opportunism (Utset 2002).

• Complementary Efforts.

• Trust Games.

• Experiments.

• Control Rights.

161

Private Equity

• JCF paper: slides to follow…

• PE and leverage: slides to follow….

162

Lecture 10: Introduction to Behavioural Corporate Finance.

•Standard Finance - agents are rational and self-interested.•Behavioural finance: agents irrational (Psychological Biases).•Irrational Investors – Overvaluing assets- internet bubble? Market Sentiment?•Irrational Managers- effects on investment appraisal?•Effects on capital structure?•Herding.

163

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.

164

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.

165

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.

166

Potential biases.

• Overconfidence/optimism • Regret.• Prospect Theory/loss aversion.• Representativeness.• Anchoring.• Gambler’s fallacy.• Availability bias.• Salience….. Etc, etc.

167

Focus in Literature

• Overconfidence/optimism

• Prospect Theory/loss aversion.

• Regret.

168

Prospect Theory.

W

U

Eg: Disposition Effect:

Sell winners too quickly.

Hold losers too long.

Risk-averse in gains

Risk-seeking in losses

169

Overconfidence.

• Too much trading in capital markets.

• OC leads to losses?

• But : Kyle => OC traders out survive and outperform well-calibrated traders.

170

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.

171

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).

172

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.

173

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.

174

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.

175

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.

176

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.

177

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.

178

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).

179

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.

180

Overconfidence/optimism

• Optimism: upward bias in probability of good state.

• Overconfidence: underestimation of asset risk.

• My model =>

• Overconfidence: overestimation of ability.

181

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.

182

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.

183

Behavioral model of overconfidence.

Both Managers issue debt:

.ˆ,ˆ qqpp

.)ˆ1(ˆ2

ˆ bpqp

IpRpM g

.)ˆ1(ˆ2

ˆ bqqp

IqRqM b

184

Good mgr issues Debt, bad mgr issues equity.

.)ˆ1(ˆ

ˆ bpIp

pRpM g

.ˆ

ˆ Iq

qRqM b

Both mgrs issue equity.

,ˆ2

ˆ Iqp

pRpM g

.ˆ2

ˆ Iqp

qRqM b

185

Proposition 1.

a) If

b)

,)ˆ1()ˆ1()(

)(ˆbpbqI

qpq

qpq

}.{ DSS bg

,)ˆ1()(

)(ˆ)ˆ1( bpI

qpq

qpqbq

}.,{ ESDS bg

c) ,)(

)(ˆ)ˆ1()ˆ1( I

qpq

qpqbpbq

}.{ ESS bg

Overconfidence leads to more debt issuance.

186

Overconfidence and Moral Hazard

• Firm’s project: 2 possible outcomes.

• Good: income R. Bad: Income 0.

• Good state Prob:

• True:

• Overconfidence:

• True success prob:

].1,0()( eP .0.0

.eP

187

Manager’s Perceived Payoffs

.)ˆ1()(ˆˆ 2 IPDebPDRPM D

.)1(ˆˆ 2 IPReRPM E

188

Optimal effort levels

2

))((*

bDReD

2

))((*

DReE

189

Effect of Overconfidence and security on mgr’s effort

• Mgr’s effort is increasing in OC.

• Debt forces higher effort due to FD.

190

Manager’s perceived Indirect Payoffs

bIDbDRbDR

M D

2

))((

4

)()(ˆ22

IDDRDR

M E

2

))((

4

)()(ˆ22

.2

)(

4

))(2()(ˆ22

bbDbDRb

M D

191

True Firm Value

.2

))()(()( b

bRbDRbbRPV DD

.2

))((

RDR

RPV EE

192

Effect of OC on Security Choice

024

))(2()0(ˆ

222

bbDbIRb

M D

0ˆ

DM

.0)(ˆ CDM

],,0[ C

,C

Manager issues Equity.

Manager issues Debt.

193

Effect of OC on firm Values

.2

))()(()( b

bRbDRV CD

bDRRbDbbR

VD

2

)()2)(( 22

.2

)()0(

2

RDR

VE

194

Results

• For given security: firm value increasing in OC.• If• Firm value increasing for all OC: OC good.• Optimal OC: • If • Medium OC is bad. High OC is good.• Or low good, high bad.

,0)( CDV

,0)( CDV .* max

195

Results (continued).

• If

• 2 cases: Optimal OC:

•

• Or Optimal OC:

,0)( CDV

.* max

.* C

196

Effect of Overconfidence on Firm Value

-600

-400

-200

0

200

400

600

800

1000

1200

0 0.1 0.2 0.3 0.4 0.5

Overconfidence

Val

ue

Effect of Overconfidence on Firm Value

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

1 2 3 4 5 6 7 8 9 10

Overconfidence

Val

ue

Effect of Overconfidence on Firm Value

-2000

-1500

-1000

-500

0

500

1000

1500

2000

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

OverconfidenceV

alu

e

197

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.

198

Future Research

• Optimal level of OC.

• Include Investment appraisal decision

• Other biases: eg Refusal to abandon.

• Regret.

• Emotions

• Hyperbolic discounting

• Is OC exogenous? Learning.

199

Herding

200

Hyperbolic Discounting

201

Emotional Finance

• Fairchild’s Concorde case study.