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Behavioral Finance

Alok Kumar

Yale School of Management8 December 1999

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Agenda

Efficient Market Hypothesis (EMH)

Expected Utility; Rational Expectations

Few Examples

Prospect Theory (Kahneman and Tversky)

Behavioral Heuristics and Biases inDecision Making

Implications for Financial Markets

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Market Efficiency

Fama: The market price at any time instantreflects all available information in the market.

Cannot make money using stale information.

Three forms Weak form:past prices and returns.

Semi-strong form:all public information.

Strong form:all public AND private information. Michael Jensen: there is no other proposition in

economics which has more empirical support than the

EMH.

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Challenges to EMH

Investors are not fully rational. They

exhibit biases and use simple heuristics

(rules of thumb) in making decisions. Empirical Evidence on investor behavior:

investors fail to diversify.

investors trade actively (Odean).Investors may sell winning stocks and hold

onto losing stocks (Odean).

extrapolative and contrarian forecasts.

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Expected Utility Theory

A theory of choice under uncertainty for a

single decision-maker.

Expected Utility = p1*u1 + p2*u2 + +pn*un.

p: probability of an event

u: utility derived from the event

Based on several strong assumptions about

preferences. Example: transitivity, cancellation.

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Rational Expectations Paradigm

All investors are identical.

All investors are utility maximizers.

All investors use Bayes rule to form newbeliefs as new information becomes

available.

All investor predictions are accurate.Expected Utility + Rational Expectations

=> Market Efficiency

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Are Financial Markets Efficient?

Weak form of market efficiency supported to a

certain extent.

Challenges:

Excess market volatility

Stock price over-reaction: long time trends (1-3

years) reverse themselves.

Momentum in stock prices: short-term trends(6-12 months) continue.

Size and B/M ratio (stale information) may help

predict returns.

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Stock Price Reaction to

Non-Information Crash of 1987: 22.6% decline without any

apparent news.

50 largest one-day stock price movements:occurred on days of no major

announcements.

Inclusion of a stock in the S&P500 indexresults in significant share price reactions.Example: AOL rose 18% on the news of its inclusion in

the index.

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Role of Investor Behavior

Bounded Rationality: satisficing

behavior. Information processing

limitations. Example:memory limitations. Investor Sentiment: beliefs based on

heuristics rather than Bayesian rationality.

Investors may react to irrelevantinformation and hence may trade on

noise rather than information.

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Irrational Behavior of

Professional Money Managers May choose a portfolio very close to the

benchmark against which they are evaluated

(for example: S&P500 index). Herding:may select stocks that other

managers select to avoid falling behind

and looking bad. Window-dressing:add to the portfolio stocks that

have done well in the recent past and sell stocks that have

recently done poorly.

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An Example

Initial endowment: $300. Consider a choice

between:

a sure gain of $100 a 50% chance to gain $200, a 50% chance to gain $0.

Initial endowment: $500. Consider a choice

between:

a sure lossof $100

a 50% chance to lose$200, a 50% chance to lose$0.

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Reversal in Choice

Case 1: 72% chose option 1, 28% chose option 2.

Case 2: 36% chose option 1, 64% chose option 2.

=> A reversal in Choice

Problem framed as a gain: decision maker is

risk averse.

Problem framed as a loss: decision maker isrisk seeking.

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Allais Paradox

Case 1:consider a choice between:

$1 million with certainty.

$5 million with prob 0.1, $1m with prob 0.89and $0 with prob 0.01

Case 2:consider a choice between:

$1m with prob 0.11, $0 with prob 0.89.$5m with prob 0.10 and $0 with prob 0.90.

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Allais Paradox: Explanation

u(1m) > 0.10*u(5m) + 0.89*u(1m) +

0.01*u(0m)

Add 0.89*u(0m) - 0.89*u(1m) to both sides.

0.11*u(1m) + 0.89*u(0m) > 0.10*u(5m) +

0.90*u(0m)

Violates Expected Utility Theorem!

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Prospect Theory

Proposed by two psychologists: DanielKahneman and Amos Tversky.

Gambles are evaluated relative to a

reference point.

Decision maker analyzes gains and

losses differently.

Incremental value of a loss is larger thanthat of a loss.the hurt of a $1000 loss is more painful than the benefit

of a $1000 gain.

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Behavioral Heuristics and

Decision-Making Biases What strategies do decision makers use

when faced with difficult decisions,

especially ones that involve uncertainty? Commonly Used Heuristics

Availability:familiarity breeds investment.

Representativeness:judgement based on similarity.Patterns in random sequences.

Reliance on the judgement of other people (Keynes

beauty contest analogy).

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Gamblers Fallacy

Investors may apply law of large numbers

to small sequences.

Example: fair coin tossing.THTHTHHHHHH -> P(T) = ?, P(H) = ?.

Which of the 2 sequences is more likely to

occur in a fair coin tossing experiment? HHHHHHTTTTTTHHHHHH

HHTHTHHTHTTHTHHTTH

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Some more Heuristics

Overconfidence:people overestimate the reliability oftheir knowledge.

Excessive trading

Framing Effect Regret Aversion: anticipation of a future regret can

influence current decision.

Disposition Effect: sell winners, hold on to the losers.

Anchoring and adjustment: can create under-reaction.

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Fashions and Fads

People are influenced by each other. There

is a social pressure to conform.

Herding behavior: safety-in-numbers.

Informational Cascades

Positive Feedback

Example: excessive demand for internet IPOs.Extremely high opening day returns.

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Can arbitrage opportunities exist?

Yes!

Real-world arbitrage is always risky. No

riskless hedge for the arbitrageur. Arbitrageur facesnoise trader risk: mispricing

can become worse before it disappears.

Close substitutes (needed for arbitragepositions) may not be available.

Fundamentally identical assets may NOT sell at

identical prices.

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Behavioral Finance:

Two Major Foundations Investor Sentiment:creates disturbances to

efficient prices.

Limited arbitrage:arbitrage is neverriskfree, hence it does not counter irrational

disturbances.

Prices may not react to information by the rightamount.

Prices may react to non-information.

Markets may remain efficient.

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Summary

Investor behavior does have an impact onthe behavior of financial markets. How

much? Not clear!

Both social and psychological must betaken into account in explaining the

behavior of financial markets.

Market anomalies may be widespread. Behavioral Finance: does not replace but

complementstraditional models in Finance.