1. Joseph V. Rizzi Finance 342, 2013 1

2. A. Main Decisions B. Fundamental Building Blocks C. Separation Principles/Decision Rules D. Statistics E. Financial Markets F. Decisions at Risk (DAR) 2

3. 1. Objective Function – what are we to maximize? 2. Investment Decision – how do we invest and manage, and why? 3. Dividend Decision – level (and form) of funds returned to the shareholders? 4. Capital Structure – how do we fund ourselves? 3

4. 1. Efficient Capital Markets – price behavior in speculative markets. Complex Adaptive Systems Efficient Learning 4

5. 2. Portfolio Theory – optimal security selection procedures. 3. Asset Pricing Models – determining asset prices by investors utilizing portfolio theory. 4. Option Pricing Theory – pricing of contingent claims. 5. Agency Theory – incentive conflict when benefits are concentrated but costs are disbursed. Heightened by moral hazard when you cannot observe behavior. Enhanced by behavioral bias. 5

6. a) Manifestation 1) Insufficient effort 2) Overinvest 3) Entrenchment 4) Self Dealing 6

7. b) Information asymmetries: heightened conflict between agent/managers and principals/investors Disbursement BeforeAfter AdverseMonitoring Costs SelectionMoral Hazard 1) Chance vs. uncertainty 2) Ignorance vs. adverse selection 3) Dishonesty vs. moral hazard 7

8. c) Moral hazard = f (private benefit from misbehaving, 1/verification) d) Adverse Selection e) Responses 1) Signaling – debt levels, dividends, reputation 2) Incentives 3) Monitoring 4) Contracts – warranties, deductibles, pricing 8

9. f) Value implications – wedge between value and income pledge, between opportunity and financing. 1) Value – may not be externally determined 2) Financing – Agency problems/concerns may deprive firms from financing. Borrowers may make concessions to Lender to achieve funding. 3) Pecking Order 9

10. 6. Game Theory: Economics of decision making; uncertainty lies in the intention/reaction of others. Focus on how individuals behave, anticpate and respond. Components – players, action, motives, and rules. 10

11. 7. Behavioral Finance: Prices influenced by herd vs. lead steers. The issue is whether markets are inefficient or just noisy. Requirement: arbitrage limit. Implications: (1) Investors irrational – Shield managers (2) Managers irrational – Limit discretion 11

12. a) Bias: Optimism Overconfidence Confirmation Illusion of Control b) Heuristics: Representation I/n equal weight Availability – overweight recent Anchoring – overweight initial 12

13. c) Framing: Reference points d) Manifestations: Winners curse Gamblers fallacy Sunk cost – regret avoidance (prospect theory) Reputation loss Valuation 13

14. 8. Arbitrage: Law of one price – equal rate of return principle 14

15. 1) Market Value Rule: Maximize shareholder wealth. Separating ownership from management raises conflict issues. Control mechanisms: a)Management incentive compensation contract provisions. b)Management ownership interest. c)Management labor market (Reputation) d)Market for corporate control e)Internal control mechanisms (Board of Directors) 15

16. 2) NPV Rule: Choose projects whose returns exceed their cost of capital (r ≥ c*). Need to consider multiple risk adjusted discount rates and option value of strategic investments. Discount rate is a function of the risk class. 16

17. 3) Dividend Irrelevance: (except for: agency cost, signaling, and option pricing issues). 17

18. 4) Capital Structure Irrelevance: (except for: taxes, agency cost, signaling, and option pricing issues). 18

19. Statistics: beware data mining, which is prevalent in non- experimental sciences lacking controlled experiments. 1. Reliance on past as prolog vs. history. 2. Descriptive vs. predictive. 3. Issues – normality, suvivorship, stationary, independence. 4. Movements – go beyond mean and variance to skew and tails. 5. Beyond the data – out of sample issues. 6. Correlations – state dependent and lack integrating model covering both default and spread widing. 7. VAR – best of worst. Need expected shortfall analysis to get into tail. 19

20. Statistics: beware data mining, which is prevalent in non-experimental sciences lacking controlled experiments – continued. 8. Goodhart’s Law – sociological uncertainty principle – when a measure becomes a target it ceases to be a good measure (behavior change). 20

21. Financial Markets: 1) Merton – neoclassical benchmark anomolies/inhibitions/transactions cost institutional solutions – overcoming inefficiencies to get back to benchmark. Means of creating missing markets. 2) Machines – converting danger (uncontrollable damages) into risk (decision-related controllable damage) which can be traded or transferred. Focus on unintended consequences and conservations of risk principle. 21

22. Decisions at risk (DAR): DAR AgencyAsymmetricBias ProblemInformation 22