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Beh Finance 1
BEHAVIORAL FINANCE
Introduction
behavioral finance is an alternative to the EMH
this material taken mostly from the 2000 book by
Andrei Shleifer of Harvard:
Inefficient Markets: An Introduction To Behavioral
Finance
EMH has been the central tenet of finance for almost30 years
power of the EMH assumption is remarkable
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Beh Finance 2
EMH started in the 1960s
immediate success in theory and empirically
early empircal work gave overwhelming support to
EMH
EMH invented at Chicago and Chicago became a
world center of research in finance
Jensen (1978) no other proposition in economics
. . . has more solid empirical support
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Beh Finance 3
verdict is changing efficiency of arbitrage is much weaker than
expected
true arbitrage possibilities are rare
near arbitrage is riskier than expected
Markets can remain irrational longer than you
can remain solvent John Maynard Keyes
quoted by Roger Lowenstein in When Genius
Failed: The Rise and Fall of Long-Term Capital
Management
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Beh Finance 4
Defense of EMH
three lines of defense of the EMH:
investors are rational
trading of irrational investors is random and theirtrades cancel each other
even if a herd of irrational investors trade in
similar ways, rational arbitrageurs will eliminate
their influence on market price
each of these defenses is weaker that had been thought
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Beh Finance 5
rational investing = value a security by its
fundamental value
fundamental value = net present worth of all
future cash flows
rational investing prices are (geometric) random
walks
but prices being random walks (or nearly so) does
not imply rational investing
there is good evidence that irrational trading is
correlated
look at the Internet stock bubble
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Beh Finance 6
initial tests of the semi-strong form of efficiency
supported that theory
event studies showed that the market did react
immediately to news and then stopping reactin so reaction to news, as EMH predictos
also no reaction to stale news, again as EMH
predicts
Scholes (1972) found little reaction to non news block sales had little effect on prices
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Beh Finance 7
Challenges to the EMH
it is difficult to maintain that all investors arerational.
many investors react to irrelevant information
Black calls them noise traders
investors act irrationally when they
fail to diversify
purchase actively and expensively managed mutual
funds
churn their portfolios
investors do not look at final levels of wealth when
assessing risky situations (prospect theory)
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Beh Finance 8
there is a serious loss aversion
people do not follow Bayes rule for evaluating new
information
too much attention is paid to recent history
overreaction is commonplace
these deviations from fully rational behavior are not
random
moreover, noise traders will follow each othersmistakes
thus, noise trading will be correlated across investors
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Beh Finance 9
managers of funds are themselves human and will
make these errors too
managers also have their own types of errors
buying portfolios excessively close to a benchmark
buying the same stocks as other fund managers (soas not to look bad)
window dressing adding stocks to the portfolio
that have been performing well recently
on average, pension and mutual fund managersunderperform passive investment strategies
these managers might be noise traders too
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Beh Finance 10
Can arbitrageurs save the day?
the last defense of the EMH depends on arbitrage
even if investor sentiment is correlated and noise
traders create incorrectly priced assets arbitrageurs are expected to take the other side of
these traders and drive prices back to fundamental
values
a fundamental assumption of behavioral finance is
that real-world arbitrage is risky and limited
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Beh Finance 11
arbitrage depends on the existence of close
substitutes for assets whose prices have been driven
to incorrect levels by noise traders
many securities do not have true substitutes
often there are no risk-less hedges for arbitrageurs
mispricing can get even worse, as the managers of
LTCM learned this is called noise trader risk
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Beh Finance 12
What do the data say?
Shiller (1981), Do stock prices move too much to be
justified by subsequent changes in dividends:
market prices are too volatile more volatile than explained by a model where
prices are expected net present values
this work has been criticized by Merton who said
that Shiller did not correctly specify fundamentalvalue
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Beh Finance 13
De Bondt and Thaler (1985), Does the stock market
overreact?:
frequently cited and reprinted paper
work done at Cornell
compare extreme winners and losers
find strong evidence of overreaction for every year starting at 1933 they formed
portfolios of the best performing stocks over the
previous three years
winner portfolios they also formed portfolios of the worse performing
stocks
loser portfolios
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Beh Finance 14
then examined returns on these portfolios over the
next five years
losers consistently outperformed winners
difference is difficult to explain as due to differences
in risk, at least according to standard models such asCAPM
De Bondt and Thaler claim that investors overreact
extreme losers are too cheap
so they bounce back
the opposite is true of extreme winners
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Beh Finance 15
historically, small stocks have earned higher returns
than large stocks no evidence that the difference is due to higher risk
superior returns of small stocks have been
concentrated in January
small firm effect and January effect seem to havedisappeared over the last 15 years
market to book value is a measure of cheapness
high market to book value firms are growth stock they tend to underperform
also they tend to be riskier, especially in severe
down markets
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Beh Finance 16
October 19, 1987 Dow Jones index dropped 22.6%
there was no apparent news that day
Cutler et al (1991): looked at 50 largest one-day
market changes
many came on days with no major news
announcements
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Beh Finance 17
Roll (1988) tried to predict the share of return
variation that could be explained by
economic influences
returns on other stocks in the same industry public firm-specific news
Rolls findings:
R2 = .35 for monthly data
R2 = .2 for daily data
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Beh Finance 18
Rolls study also shows that there are no close
substitutes for stocks
this lack of close substitutes limits arbitrage
stocks rise if the company is put on the S&P 500
index
this is reaction to non news America Online rose 18% when included on the
S&P
In summary, there is now considerable evidence
against the EMH This evidence was not found during early testing of
the EMH
Researchers needed to know what to look for
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Beh Finance 19
Market Volatility and Irrational Exuberance
Two books by Robert J. Shiller:
1989 Market Volatility
2000 Irrational Exuberance
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Beh Finance 20
What is a stock worth?
Let Vt be intrinsic value at time t. By definition
Vt =Ct+1
1 + k+
Ct+2
(1 + k)2+ =
i=1
Ct+i
(1 + k)i.
Ck is the cash flow at time k
k is the discount rate
A little bit of algebra shows that
Vt =T
i=1
Ct+i
(1 + k)i+
VT
(1 + k)T.
(exercise: check)
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Beh Finance 21
From previous page:
Vt =T
i=1
Ct+i(1 + k)i
+ VT(1 + k)T
. (1)
Shillers idea:
T = now
t < T is the past
Use past data to compute Vt as an approximation use PT in place of VT then all quantities in (1) are known at time T
compare Vt with Pt = actual stock price
EMH says that Pt is the optimal forecast at
time t of Vt.
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Beh Finance 22
How do Vt
and Pt
compare?
Rough freehand sketch of Shillers plot.
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Beh Finance 23
We see that Pt is more volatile than Vt.
Does this agree with the hypothesis that Pt is the
optimal forecast of Vt?
NO!
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Beh Finance 24
Best prediction
If X is the best predictor of X, then X and X X are uncorrelated
Var(X
) = Var(X) + E(X X)2
. Var(X) Var(X).(Exercise: prove these results if X is the best linearpredictor of X.)
An optimal predictor is less variable than the
quantity being predicted.
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Beh Finance 25
Example: random walk
Suppose that Wt = 1 + + t, where 1, . . . are IID
N(, 2).
at time t, 0 t < T, the best predictor of WT is
WT = Wt + (T t) In other words, at time t
WT = {1 + 2 + + t} + {t+1 + + T}
is predicted by
WT = {1 + 2 + + t} + { + + }
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Beh Finance 26
From last page:
WT = {1 + 2 + + t} + {t+1 + + T}is predicted by
WT = {1 + 2 + + t} + { + + } Var(WT) = T
2
Var(WT) = Var(Wt) = t2. WT WT = (t+1 ) + + (T ) Var(WT WT) = (T t)
2
.Therefore, in this example,
Var(WT) = Var(WT) + Var(WT WT)
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Beh Finance 27
As t T we cumulate more information about WT and
Var(WT) = Var(Wt) = t2
increases Var(WT WT) = (T t)2 decreases Var(WT) = T
2 stays the same (of course)
The main point, however, is simply that
an optimal forecast is less variable that what is being
forecasted.
stock prices are more variable that the present values
of future discounted dividends.Therefore, price cannot be optimal forecasts of the
present value of discounted future dividends.
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Beh Finance 28
At least, this is Shillers argument.
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Irrational Exuberance is a very interesting
discussion of market psychology, bubbles, naturally
occurring Ponzi schemes, and other possible
explanations of why the market seemed overpriced in
2000.
Shillers analysis suggests that the market may be
still overpriced in 2002, despite two years of declining
prices.
Shiller presents fascinating evidence that periodswhere the market is either over or under priced have
occurred, often several times, in many countries.