1. A Survey of Behavioral Finance
Nicholas Barberis
Richard Thaler
Presented by Ryan Samson

2. Traditional vs. Behavioral
Rational
Correct Bayesian Updating
Choices Consistent with Expected Utility
Behavioral
Some are Not Fully Rational
Relax One or Both Tenets of Rationality

4. Limits to Arbitrage vs. Market Efficiency
EMH
Prices Reflect Value
Mispricings Corrected by Arbitrageurs
Limits to Arbitrage
Strategies May not be Arbitrage
Problems Entering Position?
Correct Prices => No Free Lunch
No Free Lunch ≠> Correct Prices
Why Care?

5. Theory Supporting Limits to Arbitrage
Fundamental Risk – Negative Shock and no Perfect Substitute (e.g. Ford and GM)
Noise Trader Risk – Continued Widespread Irrationality
Forced Liquidation (Separation of Brains and Capital)
Horizon Risk
Trading in the Same Direction

6. Theory Supporting Limits to Arbitrage 2
Implementation Costs
Commission
Bid/Ask Spread
Price Impact
Short Sell Costs
Fees
Volume Constraints
Legal Restraints
Identification Cost
Mispricing ≠> Predictability

7. Evidence Supporting Limits to Arbitrage
Mispricings Hard to Identify
Test of Mispricing => Test of Discount Rate Model
Twin Shares
Royal Dutch (60%) and Shell (40%)
Only Risk is Noise Traders
=> PriceRD = 1.5*PriceS

8. Evidence Supporting Limits to Arbitrage 2
Index Inclusions
Stock Price Jumps Permanently
3.5% Average
Fundamental Risk
Poor Substitutes (best R2 < 0.25)
Noise Trader Risk
Index Fund Purchases etc.

9. Evidence Supporting Limits to Arbitrage 3
Internet Carve-Outs
3Com Sells 5% of Palm in IPO, Will Spin Off Remainder in 9 Months
1 Share of 3Com will own 1.5 Shares of Palm
PPalm = $95
3Com should be ≥ $142
P3Com = $81
Value of 3Com Excluding Palm = -$60

10. Evidence Supporting Limits to Arbitrage 4
Why?
Very Few Shares of Palm available to Short
Arbitrage was Limited
Mispricing Persisted

11. Psychology Beliefs Overconfidence Optimism / Wishful Thinking
98% CI only captures 60%
100% is actually 80% and 0% is actually 20%
Optimism / Wishful Thinking
Unrealistic View of Personal Abilities / Prospects
90% of Drivers Claim Above Average Skill
99% of Freshman Claim Superior Intelligence

12. Psychology 2 Beliefs Continued Representativeness Conservatism
Base Rates are Under-Emphasized Relative to Evidence
Sample Size Neglect in Learning Distribution
(6 Tosses vs Tosses)
“Law of Small Numbers”
Gambler’s Fallacy
Conservatism
Base Rates are Over-Emphasized Relative to Evidence

13. Psychology 3 Beliefs Continued Belief Perseverance Anchoring
Search for Contradictory Evidence
Treatment of Contradictory Evidence
Anchoring
Initial Arbitrary Value and Make Adjustments
Availability Biases
Recent or Salient Events

14. Psychology 4 Beliefs, Final Notes
People Display Poor Learning in Application
Experts Often do Worse
Increasing Incentives Doesn’t Help

15. Psychology 5 Preferences Prospect Theory
Expected Utility vs. Prospect Theory or Ambiguity Aversion
Prospect Theory
Value of a Gamble is: π(p)*v(x)+π(q)*v(y)
Utility Defined over Gains and Loses
Concave over Gains, Convex over Losses
Nonlinear Probability Transformation
Especially Large Weight on Certain Outcomes

16. Psychology 6 Ambiguity Aversion
People Avoid Uncertain Probability Distributions
Aversion Changes Based on Perceived Competence at Assessing Relevant Distribution
Preference for Familiar

17. Application 1: Aggregate Stock Market
3 Puzzles:
Equity Premium
High Volatility in Returns and P/D Ratios
Predictable Returns (D/P alone  R2 = 0.27)

18. Equity Premium Risk Premium Seems too High
Possible Explanations Under Prospect Theory
Benartzi and Thaler
Eπv[(1-w)Rf,t+1 + wRt+1 – 1], π and v as before
Given Historical Returns, Investors are Indifferent to w = 1 and w = 0
Calculate Implied Length of t
1 Year (Taxes? Annual Reports?)
Result is Myopic Loss Aversion

19. Equity Premium 2 Possible Explanations Under Prospect Theory Continued
Need Intertemporal Model
Barberis, Huang, Santos
Utility From Consumption (Source 1) AND Utility From Changes in Value of Risky Assets (Source 2)
Utility From Source 2 Captures Loss Aversion (Not Convexity, Concavity, or Nonlinearity of π)
Explanatory power based on weight of Source 2

20. Equity Premium 3
Possible Explanations Under Prospect Theory, Final Notes
Why?
Regret
Bounded Rational:
P(C(Labor Income, Stock Returns) < Habit)
P(C(Stock Returns) < Habit)
t = 1 Year Based on Presentation

21. Equity Premium 4 Explanations Under Ambiguity Aversion
Max[Min[E[U]]] (i.e. Playing Malevolent Opponent)
Requires High Equity Premium

22. Volatility
Rational Approaches Must Focus on Changing Risk Aversion to Explain Volatility
Explanations Under Beliefs
Overreaction to Dividend Growth  Volatile Prices
Law of Small Numbers
Overconfidence in Opinion
Overreaction to Returns
Confusion Between Real and Nominal Rates

23. Volatility Explanations Under Preferences
Same Model as Used for Equity Premium
Add zt, a State Variable, to Source 2 of Utility
Several Price Increases  Less Scared
Price Decreases  Scared

24. Application 2: Cross-Section of Average Returns
You Can Form Groups of Stocks w/ Different Average Returns, Not Explained by CAPM
Size Premium (Small Stocks +0.74%/month)
Long Term (3 Yr) Reversal (8%/Yr)
Price Ratios
B/M (High B/M +1.53%/month)
P/E (High P/E +0.68%/month)
Momentum (6 Month Winners +10%/Yr)

25. Cross-Section of Average Returns
Anomalies Continued
Earnings Announcements (Over 60 Days +4% for Good Over Bad)
Dividend Initiation / Omission
Stock Repurchases
Problems w/ Anomalies
Difficult Statistics (Cross-Sectional Correlation)
Data-Mining (Test Out of Sample)
Multi-Factor Models

26. Cross-Section of Average Returns
Explanations Under Beliefs
Conservatism (Underweight New Info)
React Slowly to Earnings Reports
Representativeness
Overreact Now, Reversal Later
Overconfidence
Ignore Unfavorable Public Info  Reversal
Too Much Attention to Favorable Public Info  Momentum
All Imply P Around Earnings Report

27. Cross-Section of Average Returns
Belief Based Continued
Positive Feedback
Momentum
Post Earnings Drift
Long Term Reversal
A Result of Law of Small Numbers?

28. Cross-Section of Average Returns
Belief Based w/ Institutional Friction (i.e. Short Sell Constraints)
Bearish Cannot Short  Reversal or Momentum
Effect of Higher Incentives on Short Prices

29. Cross-Section of Average Returns
Preference Based Explanations
Same BHS Model Applied to Individual Stocks
Price Reversal (Not Momentum)