Chapter 12
Market Efficiency and Behavioral Finance
Chapter 12
Efficient Market Hypothesis (EMH)
• Are security markets efficient relative to the
information available for valuing securities?
• Do security prices reflect relevant information
quickly and accurately?
• Why look at market efficiency?
– Implications for business and corporate finance
– Implications for investment
8-2
Random Walk and the EMH
• Random Walk - stock price changes are
random
– Actually submartingale
• Expected price is positive over time
• Positive trend and random about the trend
8-3
Random Walk with Positive Trend
Security
Prices
Time
8-4
Market Efficiency
• The Efficient Market Hypothesis (EMH) is a
hypothesis that asserts: As a practical matter, the major
financial markets reflect all relevant information at a
given time.
• Market efficiency research examines the relationship
between stock prices and available information.
– The important research question: Is it possible for investors to
“beat the market?”
– Prediction of the EMH theory: If a market is efficient, it is not
possible to “beat the market” (except by luck).
8-5
What Does “Beat the Market” Mean?
• The excess return on an investment is the return
in excess of that earned by other investments that
have the same risk.
• “Beating the market” means consistently earning
a positive excess return.
8-6
Forms of Market Efficiency,
(i.e., What Information is Used?)
• A Weak-form Efficient Market is one in which past prices and
volume figures are of no use in beating the market.
– If so, then technical analysis is of little use.
• A Semistrong-form Efficient Market is one in which publicly
available information is of no use in beating the market.
– If so, then fundamental analysis is of little use.
• A Strong-form Efficient Market is one in which information of any
kind, public or private, is of no use in beating the market.
– If so, then “inside information” is of little use.
– Securities law regulates insider trading, so the law believe
markets are not strong form efficient.
8-7
Why Would a Market be Efficient?
• The driving force toward market efficiency is simply
competition and the profit motive.
• Even a relatively small performance enhancement can
be worth a tremendous amount of money (when
multiplied by the dollar amount involved).
• This creates incentives to unearth relevant information
and use it.
8-8
Random Price Changes
Why are price changes random?
• Prices react to information
• Flow of information is random
• Therefore, price changes are random
8-9
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.
8-10
Types of Stock Analysis
• Technical Analysis - using prices and
volume information to predict future
prices.
– If securities markets are weak form efficient,
then technical analysis is useless
• Fundamental Analysis - using economic
and accounting information to predict
stock prices.
– If securities markets are semi strong form
efficient, then fundamental analysis is
useless
8-11
Technical Analysis
• Technical analysis differs significantly from
fundamental analysis.
• Technical analysis is a controversial set of techniques
for predicting market direction based on
– Historical price and volume behavior
– Investor sentiment
• Technical analysts essentially search for bullish
(positive) and bearish (negative) signals about stock
prices or market direction.
8-12
Dow Theory, I.
• The Dow theory is a method that attempts to interpret
and signal changes in the stock market direction.
• Historically, quite popular.
• The Dow theory identifies three forces:
– a primary direction or trend,
– a secondary reaction or trend, and
– daily fluctuations
• Daily fluctuations are essentially noise and are of no
real importance.
8-13
Dow Theory, II.
Dow Jones Industrial Average,
January 2, 2001 to October 3, 2003
12,000
The primary direction is either bullish or bearish,
and reflects the long-run direction of the market.
11,000
Level
10,000
9,000
8,000
Secondary
trends,
temporary
departures
Corrections,
reversions to the
primary direction
7,000
01/01
04/01
07/01
10/01
01/02
04/02
07/02
10/02
01/03
04/03
07/03
10/03
Date
8-14
Dow Theory, III.
• Purpose: to signal changes in the primary direction.
• Must monitor two indexes:
– Dow Jones Industrial Average
– Dow Jones Transportation Average
• If ONE index departs from the primary direction, this is
not a signal.
• However, if a departure in one is followed by a
departure in the other, this is viewed is confirmation
that the trend has changed.
The trend is your friend…
8-15
Support and Resistance Levels
• A support level is a price or level below which a stock
or the market as a whole is unlikely to go, while a
• Resistance level is a price or level above which a stock
or the market as a whole is unlikely to rise.
• Resistance and support areas are usually viewed as
psychological barriers
– Bargain hunters help “support” the lower level.
– Profit takers “resist” the upper level.
• A “breakout” occurs when a stock (or the market)
passes through either a support or a resistance level.
8-16
Market Diaries,
A Collection of Technical Indicators
8-17
Technical Indicators, Notes
• The “advance/decline line” shows, for some period, the cumulative
difference between advancing and declining issues.
• “Closing tick” is the difference between the number of shares that
closed on an uptick and those that closed on a downtick.
• “Closing arms” or “trin” (trading index) is the ratio of average
trading volume in declining issues to average trading volume in
advancing issues. Using data from the "Previous Close:"
Arms 
754,540,570/1,734 435,144

 1.6944
384,700,630/1,498 256,809
• “zBlock trades” are trades in excess of 10,000 shares.
8-18
Charting, Relative Strength
• Relative strength charts measure the performance of
one investment relative to another.
• Comparing stock A to stock B, through relative strength.
Stock A
(4 Shares)
Stock B
(2 Shares)
Relative
Strength
1
$100
$100
1.00
2
96
96
1.00
3
88
90
0.98
4
88
80
1.10
5
80
78
1.03
6
76
76
1.00
Month
8-19
Charting, Moving Averages
• Moving average charts are average daily prices or index
levels, calculated using a fixed number of previous days’
prices or levels, updated each day.
• Because daily price fluctuations are “smoothed out,”
these charts are used to identify trends.
• Example: Suppose the technical trader calculates a 15day and a 50-day moving average of a stock price.
– If the 15-day crosses the 50-day from above, it is a bearish
signal—time to sell.
– If the 15-day crosses the 50-day from below, it is a bullish
signal—time to buy.
8-20
Example: 15-Day and
50-Day Moving Averages
Dow Jones Industrial Average,
15-Day and 50-Day Moving Average
11,000
10,500
10,000
Index Level
15-Day
50-Day
9,500
9,000
8,500
8,000
7,500
1/2/02
3/6/02
5/7/02
7/9/02
9/9/02
11/7/02 1/10/03
3/14/03 5/15/03
7/17/03
9/17/03
Date
Note the "whipsaw" action—i.e., plenty of buying and selling signals.
This happens because 15 and 50 may be too "close" together in time.
8-21
More Chart Types
• A hi-lo-close chart is a bar chart showing, for each day,
the high price, low price, and closing price.
• A candlestick chart is an extended version of the hi-loclose chart. It plots the high, low, open, and closing
prices, and also shows whether the closing price was
above or below the opening price.
8-22
Candlestick Making, Basics
8-23
Candlestick “Formations”
8-24
Point and Figure Charts, I.
• Point-and-figure charts attempt to show only major price
moves and their direction.
– The point and figure chart maker decides what price move is
major.
– That is, it could be $2, $5, or any other level.
• A major up-move is marked with an “X”
• A major down-move is marked with an “O”
• Start a new column when there is a direction change.
– Buy and sell signals are generated when new highs or new lows
are reached.
– Congestion area, the area between buy and sell signals—a time
of market indecision concerning its trend.
8-25
Point and Figure Charts, II.
8-26
Point and Figure Charts, III.
8-27
Chart Formations
• Once a chart is drawn, technical analysts examine it for
various formations or pattern types in an attempt to
predict stock price or market direction.
• One example is the head-and-shoulders formation.
– When the stock price “pierces the neckline” after the right
shoulder is finished, it is time to sell.
8-28
Chart Formations, The Head and Shoulders
8-29
Other Technical Indicators
• The “odd-lot” indicator looks at whether odd-lot
purchases are up or down.
• Followers of the “hemline” indicator claim that hemlines
tend to rise in good times.
• The Super Bowl indicator forecasts the direction of the
market based on who wins the game.
– Two Conference representatives play in the Super Bowl: one
from the National Football Conference and one from the
American Football Conference.
– A win by the National Football Conference (or one of the original
members of the National Football League) is bullish.
8-30
Are Financial Markets Efficient?
• Nevertheless, three generalities about market
efficiency can be made:
– Short-term stock price and market movements
appear to be difficult to predict with any accuracy.
– The market reacts quickly and sharply to new
information, and various studies find little or no
evidence that such reactions can be profitably
exploited.
– If the stock market can be beaten, the way to do so is
not obvious.
8-31
Some Implications if Markets are Efficient
• Security selection becomes less important,
because securities will be fairly priced.
• There will be a small role for professional
money managers.
• It makes little sense to time the market.
8-32
Active or Passive Management
• Active Management
– Security analysis
– Timing
• Passive Management
– Buy and Hold
– Index Funds
8-33
Market Efficiency & Portfolio Management
• Even if the market is efficient a role exists
for portfolio management:
• Diversification still matters
• Tax considerations
• Appropriate risk level
• Other considerations
– Age
– Personal knowledge
– Personal circumstances
8-34
Empirical Tests of Market Efficiency
• Event studies
• Assessing performance of professional
managers
• Testing some trading rule
8-35
Event Studies: How Tests Are Structured
1.
Examine prices and returns over time
8-36
Returns Over Time
-t
0
+t
Announcement Date
8-37
How Tests Are Structured (cont’d)
2. Returns are adjusted to determine if they
are abnormal.
Market Model approach
a. Rt = at + btRMt + et
(Expected Return)
b. Excess Return =
(Actual - Expected)
et = Actual - (at + btRMt)
8-38
How Tests Are Structured (cont’d)
2. Returns are adjusted to determine if they are
abnormal.
Market Model approach
c. Cumulate the excess returns over time:
See Figure 12.1
-t
0
+t
8-39
Issues in Examining the Results
• Magnitude Issue
– Someone researching for a large fund only
needs a small gain to justify the research –
too small too measure, relative to noise
• Selection Bias Issue
– Those who know how to beat the market
keep it a secret (or else everyone would do it;
thus, we don’t know how to study those who
beat the market
8-40
Issues in Examining the Results
• Lucky Event Issue
– Was it luck or skill? Even in a “Candy Land”
tournament, there will be a winner (and a
loser)
• Possible Model Misspecification
– Are we making the correct risk adjustment
when we make our comparisons. What if
beta is not the correct way to measure risk?
What if risk changes over time?
• Data snooping – all random data will have
parts that look non random
8-41
What Does the Evidence Show?
• Technical Analysis
– Short horizon: Very short time horizons (weekly)
shows some reversals, but not enough to trade
profitably on (Negative serial correlations). Longer
horizons (3 month to a year) shows that momentum
exits, not in individual stocks, but in portfolios, with
enough gain to cover trading costs (positive serial
correlations).
– Long horizon: Fama and French find a long term
negative serial correlation in the aggregate market.
DeBont and Thaler find contrarian investing (winner
and loser portfolios) over 5 years leads to excess
return (January to January). Other researchers
found much of the effect disappears if one looks at
July to July.
8-42
What Does the Evidence Show?
• Fundamental Analysis
– Broad market returns seem to be influenced
by dividend yields, earnings yields, bond yield
spreads. These may simply be proxies for
changing betas.
– Many event studies reinforce semi strong
market efficiency such as Figure 12.1
8-43
What Does the Evidence Show?
• Anomalies Exist
– Anomalies are empirical results that are
known, but should not exist in an efficient
market. Is that beta is an incomplete or even
wrong measure of risk, or are markets not
efficient?
– For example, Basu found a P/E effect, after
adjusting for Beta. Is there a P/E effect, or is
P/E just a measure of the firm risk, that adjust
quickly, while a beta measurement is based
on long term data?
8-44
Stock Price Behavior and Market Efficiency
The day-of-the-week effect refers to the tendency for
Monday to have a negative average return.
8-45
The Amazing January Effect, I.
• The January effect refers to the tendency for small
stocks to have large returns in January.
• Does it exist for the S&P 500?
8-46
The Amazing January Effect, II.
• The January effect refers to the tendency for small
stocks to have large returns in January. What do we
see when we look at returns on small stocks?
8-47
The Market Crash in October 1987
• On October 19, 1987 (Black Monday), the Dow
plummeted 500 points to 1,700.
– Investors lost about $500 billion in share value.
– The market lost over 20% of its value.
– The volume was a record at the time: 600 million
shares.
• Today the NYSE has circuit breakers.
– Rules that kick in to slow or stop trading when the
DJIA decreases (or increases) by more than a preset amount in a trading session.
8-48
The Performance of
Professional Money Managers
• From 1963 to 1998, the S&P 500 index outperformed
general equity mutual funds 22 times (out of 36).
• Why can’t the pros beat the averages? (You can hold a
market average very easily—SPDRs)
8-49
Other Anomalies
• Neglected Firm
– Neglected firms are typically small firms for which
there is little analyst coverage. Tend to have higher
returns – may be due to lack of liquidity. Suggests
this a risk premium in addition to beta
• Market to Book Ratios
– market to book ratios seem to explain returns better
than beta
• Post-Earnings Announcement Drift
– ( see Figure 12.7). The reaction to earnings
announcement continues after the announcement
date.
8-50
Strong Form Efficiency Tests
• Tests of insider trading suggests that insiders
can usually beat the market suggest that
markets are relatively efficient, up to semi
strong form. Trying to mimic insiders does not
seem to be of value, after their trades are
reported.
8-51
Explanations of Anomalies
• May be risk premiums (but not beta)
• Behavioral Explanations
– What if people don’t act rationally? Does that
mean prices are irrational? Some irrational
decisions will create profit opportunities for
arbitrageurs, so there will be limits to the
degree of irrationality.
8-52
Information Processing
• Forecasting Errors – people put too much
weight on recent evidence (one good exam
grade does not necessarily mean you will ace
the course or one good quarter does not means
the firms prospects are forever better)
• Overconfidence – people tend to be over
confident in their beliefs. Those who trade a lot
(confident in their beliefs) do worse than others.
• Conservatism – some people under react
• Sample Size Neglect and Representativeness –
anecdotal evidence move people more than
large statistical samples
8-53
Behavioral Biases
• Framing – On the risk tolerance quiz, the
same question mathematically, often
reversed the answer, when asked a
different way
• Mental Accounting – we budget in our
mind for certain things. People are more
likely to make risky gambles with the
“house” money than with their own.
• Regret Avoidance – certain losses cause
more pain than others, even if the dollar
amount is the same.
8-54
Limits to Arbitrage
• Fundamental Risk – if prices wander too long,
those trying to gain, may in the short term lose
(E.g. Priceline short seller)
• Implementation Costs - transactions costs may
limit arbitrage.
• Model Risk – what if your arbitrage model is
wrong?
• Result: Prices could be wrong (do not reflect
fundamentals) but its hard to profit from the
apparent opportunities. In other words,
absence of profit potential does not imply EMH
8-55
Mutual Fund Performance
• Some evidence of persistent positive and
negative performance.
• Potential measurement error for
benchmark returns.
– Style changes: When Elton et. Al. compared
results to 3 potential index funds (large
stocks, small stocks, bonds), mutual funds
showed negative (but mostly not significant)
alphas.
– May be risk premiums
8-56
So, are markets efficient?
• There’s the story of the finance professor
walking with a graduate student who spies a
$20 bill on the sidewalk. The professor says
there is no point picking up the $20 bill as if
there really was a $20 bill on the sidewalk
someone else would have picked it up already
• Superstar phenomenon:
– Who are the best investors of all time? Peter Lynch,
Warren Buffet, John Templeton, Jeff Neff. Why are
there so few in the club?
8-57