Transcript No Slide Title

CHAPTER 8
The Efficient Market
Hypothesis
McGraw-Hill/Irwin
© 2008 The McGraw-Hill Companies, Inc., All Rights Reserved.
8.1 RANDOM WALKS AND THE EFFICIEN
MARKET HYPOTHESIS
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Efficient Market Hypothesis (EMH)
Do security prices reflect information
Why look at market efficiency
– Implications for business and corporate
finance
– Implications for investment
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Random Walk and the EMH
Random Walk - stock prices are random
– Randomly evolving stock prices are the
consequence of intelligent investors
competing to discover relevant information
Expected price is positive over time
Positive trend and random about the trend
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Random Walk – Model
– Model can be of prices P,
– More commonly model in logs, LN(P)
Pt  a  Pt 1   t
ln(Pt )  a  ln(Pt 1 )   t
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Random Walk with Positive Trend
Security
Prices
Time
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Random Walk – Why Logarithms?
Transform data to natural logarithms so
model is about percentage changes. The
change in the natural log, LN(Pt)-LN(Pt-1)
is a good approximation to the percentage
change
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More on Logarithms
ln(Pt )  a  ln(Pt 1 )   t
ln(Pt )  ln(Pt 1 )  a   t  ' percent change in P'
exp(ln(Pt ))  exp(a  ln(Pt 1 )   t )
 exp(a )  exp(ln(Pt 1 ))  exp( t )
so Pt  A  Pt 1  t where A  exp(a ) and   exp( )
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Random Price Changes
Why are price changes random
– Prices react to information
– Flow of information is random
– Therefore, price changes are random
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Figure 8.1 Cumulative Abnormal Returns
Before Takeover Attempts
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Figure 8.2 Stock Price Reaction to CNBC
Reports
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EMH and Competition
Stock prices fully and accurately reflect
publicly available information
Once information becomes available,
market participants analyze it
Competition assures prices reflect
information
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Versions of the EMH
Weak: can’t predict future stock price
movements based on lagged stock price
Semi-strong: can’t predict future stock
price movements based on any publicly
known lagged data
Strong: can’t predict future stock price
movements based on any lagged data
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8.2 IMPLICATIONS OF THE EMH
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Types of Stock Analysis
Technical Analysis - using prices and volume
information to predict future prices; search for
patterns in the data
– Weak form efficiency & technical analysis; EMH
(weak form) suggests technical analysis is futile.
Fundamental Analysis - using economic and
accounting information to predict stock prices
– Semi strong form efficiency & fundamental analysis;
EMH (semi-strong) suggests fundamental analysis is
futile.
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Implications of Efficiency for Active or
Passive Management
Active Management
– Security analysis
– Timing
Passive Management
– Buy and Hold
– Index Funds
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The Role of Portfolio Management in
an Efficient Market
Even if the market is efficient a role
exists for portfolio management:
– Appropriate risk level
– Tax considerations
– Other considerations
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Information Processing is not Costless
EMH requires all to have the relevant
information and process it costlessly and
flawlessly.
Economic theory suggests an issue if there is a
cost to data acquisition and/or processing. “The
Impossibility of Informationally Efficient Markets”
But…EMH in the extreme makes clear how
difficult it can be for various active management
policies to work as intended or as claimed.
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8.3 ARE MARKETS EFFICIENT
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Empirical Tests of Market Efficiency
Magnitude Issue
–
–
–
If managers are successful and raise returns by a small amount, can we detect it?
If managers identify stock prices that are mispriced by a small amount, can we detect this?
Instead of asking ‘Are markets efficient?’ maybe we should ask ‘How efficient are
markets?’
Selection Bias Issue
–
–
The outcomes we observe have been preselected in favor of failed attempts (because true
market-beating schemes are not reported)
Cannot evaluate the true ability of portfolio managers
Lucky Event Issue
– Just because an investor or investment scheme has been successful in the
past, even for a number of years, is no proof that it was not merely good luck
instead of good management or superior ability to forecast.
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Weak-Form EMH Tests: Patterns in Stock Returns
Returns over short horizons
– Weak-Form EMH claims no serial correlation in stock returns.
– Very short time horizons small magnitude of positive trends
– 3-12 month some evidence of positive momentum
Returns over long horizons – pronounced negative
correlation
– Dramatic evidence; could be fads
– But, could just indicate changes in risk premium over time.
Evidence on Reversals
– Loser Portfolio (35 stocks with worst 5-yr performance)
outperforms the ‘Winner portfolio’ over the next 3-yr period by
25%. Evidence for a contrarian approach.
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Predictors of Broad Market Returns
Fama and French
– Aggregate returns are higher with higher dividend
ratios (dividend/price)
Campbell and Shiller
– Earnings yield can predict market returns
(earnings/price)
Keim and Stambaugh
– Bond spreads can predict market returns (interest on
high grade minus interest on low grade corporate
bonds)
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Semi-Strong Tests: Market Anomalies
P/E Effect: Portfolios with low P/E stocks
have higher returns than portfolios with
high P/E stocks (even if adjusted for beta!)
– But could be that P reflects risk differences
Small Firm Effect (January Effect)
– Invest in low-capitalization stocks
– Earn excess returns
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Figure 8.3 Returns in Excess of RiskFree Rate and in Excess of the SML
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Semi-Strong Tests: Market Anomalies
(Con’t)
Neglected Firm
– Small firms tend to be neglected by large
institutional traders
Book-to-Market Ratios
– Beta seems to have no power to explain
average security returns after controlling for
size and B-to-M ratios
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Figure 8.4 Average Annual Return
as a Function of Book-to-Market
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Semi-Strong Tests: Market Anomalies
(Con’t)
Post-Earnings Announcement Drift
– There is a large abnormal return on the
earnings announcement day
– Drift in returns even after announcement
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Figure 8.5 Cumulative Abnormal Returns in
Response to Earnings Announcements
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Strong-Form Tests: Inside Information
The ability of insiders to trade profitability
in their own stock has been documented in
studies by Jaffe, Seyhun, Givoly, and
Palmon
SEC requires all insiders to register their
trading activity
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Interpreting the Evidence
Risk Premiums or market inefficiencies—
disagreement here
– Fama and French argue that these effects can
be explained as manifestations of risk stocks
with higher betas
– Lakonishok, Shleifer, and Vishney argue that
these effects are evidence of inefficient
markets
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Figure 8.6 Return to Style Portfolio as a
Predictor of GDP Growth
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Interpreting the Evidence (Con’t)
Anomalies or Data Mining
– Rerun the computer database of past returns
over and over and examine stock returns
along enough dimensions:
Simple chance may cause some criteria to appear
to predict returns
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8.4 MUTUAL FUND AND ANALYST
PERFORMANCE
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Stock Market Analysts
Do analysts add value—mixed evidence
– Womack study found that positive changes
are associated with increased stock prices of
about 5%
– Negative changes result in average price
decreases of 11%
– Are prices change due to analysts’ information
or through pressure brought on by the
recommendations themselves
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Mutual Fund Managers
Some evidence of persistent positive and
negative performance
Potential measurement error for benchmark
returns
– Style changes
– May be risk premiums
Superstar phenomenon
– Peter Lynch (Fidelity Magellan), Warren Buffet
(Berkshire Hathaway), John Templeton, John Neff
(Vanguard Windsor)
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Figure 8.7 Estimates of Individual
Mutual Fund Alphas
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Table 8.1 Performance of Mutual Funds
Based on Three-Index Model
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Figure 8.8 Persistence of
Mutual Fund Performance
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Table 8.2 Two-Way Table of Managers Classified
by Risk-Adjusted Returns over Successive
Intervals
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