A Survey of Behavioral Finance

Nicholas BarberisRichard Thaler

Presented by Ryan Samson

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

Behavioral Finance

Limits to Arbitrage Psychology

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?

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

• Implementation Costs– Commission– Bid/Ask Spread– Price Impact– Short Sell Costs

• Fees• Volume Constraints• Legal Restraints

– Identification Cost• Mispricing ≠> Predictability

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

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.

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

• Why?

• Very Few Shares of Palm available to Short

• Arbitrage was Limited

• Mispricing Persisted

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

• 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

• 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

• Beliefs, Final Notes

– People Display Poor Learning in Application

– Experts Often do Worse

– Increasing Incentives Doesn’t Help

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

• 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

• 3 Puzzles:

– Equity Premium

– High Volatility in Returns and P/D Ratios

– Predictable Returns (D/P alone R2 = 0.27)

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

• 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

• 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

Equity Premium 4

• Explanations Under Ambiguity Aversion– Max[Min[E[U]]] (i.e. Playing Malevolent

Opponent)– Requires High Equity Premium

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

• 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

• 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

• 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

• 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

• Belief Based Continued– Positive Feedback

• Momentum• Post Earnings Drift• Long Term Reversal• A Result of Law of Small Numbers?

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

• Preference Based Explanations– Same BHS Model Applied to Individual

Stocks• Price Reversal (Not Momentum)