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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.