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


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


Slide3:


Limits to Arbitrage vs. Market Efficiency: 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 =andgt; No Free Lunch No Free Lunch ≠andgt; Correct Prices Why Care?


Theory Supporting Limits to Arbitrage: 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


Theory Supporting Limits to Arbitrage 2: 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 ≠andgt; Predictability


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


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


Evidence Supporting Limits to Arbitrage 3: 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


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


Psychology: Psychology Beliefs Overconfidence 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


Psychology 2: Psychology 2 Beliefs Continued Representativeness Base Rates are Under-Emphasized Relative to Evidence Sample Size Neglect in Learning Distribution (6 Tosses vs. 1000 Tosses) 'Law of Small Numbers' Gambler’s Fallacy Conservatism Base Rates are Over-Emphasized Relative to Evidence


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


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


Psychology 5: Psychology 5 Preferences 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


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


Application 1: Aggregate Stock Market: 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)


Equity Premium: 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


Equity Premium 2: 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


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


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


Volatility: 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 Law of Small Numbers Confusion Between Real and Nominal Rates


Volatility: 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


Application 2:Cross-Section of Average Returns: 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)


Cross-Section of Average Returns: 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


Cross-Section of Average Returns: 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


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


Cross-Section of Average Returns: 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


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