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Lecture Presentation Software
to accompany
Investment Analysis and
Portfolio Management
Eighth Edition
by
Frank K. Reilly & Keith C. Brown
Chapter 6
Chapter 6
Efficient Capital Markets
Questions to be answered:
•
•
•
•
What is does it mean to say that capital markets are efficient?
Why should capital markets be efficient?
What factors contribute to an efficient market?
Given the overall efficient market hypothesis, what are the three
sub-hypotheses and what are the implications of each of them?
• How do you test the three efficient market hypothesis (EMH) and
what are the results of the tests?
• For each set of tests, which results support the hypothesis and
which results indicate an anomaly related to the hypothesis?
• What is behavioral finance and how does it relate to the EMH?
Chapter 6
Efficient Capital Markets
• What are the major findings of behavioral finance and what are the
implications of these findings for EMH?
• What are the implications of the efficient market hypothesis test
results for
–
–
–
–
Technical analysis?
Fundamental analysis?
Portfolio managers with superior analysts?
Portfolio managers with inferior analysts?
What Constitutes An
Efficient Capital Market?
• Two forms of market efficiency
– Informational efficiency – the subject of this chapter
– Transactional efficiency – minimize cost
• Economies of scale
• Economies of scope
• In an efficient capital market, security prices
– Reflect all available information
– Adjust rapidly to the arrival of new information.
• Whether markets are efficient has been extensively
researched and remains controversial
Why Should Capital Markets
Be Efficient?
The premise of an efficient market:
– A large number of competing profit-maximizing participants
analyze and value securities, each independently of the others
– New information regarding securities comes to the market in
a random fashion
– Profit-maximizing investors rapidly adjust (in an unbiased
fashion) security prices to reflect the impact of new
information
Conclusion: In an efficient market, the expected returns
implicit in the current price of a security should reflect
its risk
Alternative
Efficient Market Hypotheses (EMH)
• Random Walk Hypothesis – first hypothesized by Louis
Bachlier, a French doctoral student in mathematics, in
1900. Said that changes in security prices occur randomly
& unpredictably.
• Eugene Fama (1970) Fair Game Model – current market
price reflect all available information about a security and
the expected return based upon this price is consistent with
its risk
• Efficient Market Hypothesis (EMH) – Fama divided EMH
into three sub-hypotheses depending on the information set
involved
– Weak-form efficient
– Semi-strong form efficient
– Strong-form efficient
Efficient Market Hypotheses (EMH)
• Weak-Form EMH - prices reflect all information contained
in the past record of prices & volumes
• Semi-strong-form EMH - prices reflect all public
information
• Strong-form EMH - prices reflect all public and private
information
Weak-Form EMH
• Current prices reflect all security-market
information, including:
–
–
–
–
–
Historical sequence of prices,
Trading volume data
Rates of return
Odd lot transactions
Block trades
• This implies that past rates of return and other
market data is already captured by the current
market price and thus should have no relationship
with future rates of return
– Past and future prices are independent
Semi-strong-Form EMH
• Current security prices reflect all public information,
including market and non-market information
• This implies that decisions made based on information
already in the public domain should not lead to aboveaverage risk-adjusted profits from those transactions
Strong-Form EMH
• Stock prices fully reflect all information from both public
and private sources
• This implies that no group of investors should be able to
consistently derive above-average risk-adjusted rates of
return
• This assumes perfect markets in which all information is
cost-free and available to everyone at the same time
Random Walk Theory: Microsoft Stock Price
Changes from March 1990 to May 2004
For Microsoft stock
over the period March
1990 to May 2004, the
correlation between a
price change on day t
and a price change on
day t+1 was +0.025.
Random Walk Theory: Weekly Returns,
May 1984 – May, 2004
FTSE 100
(correlation = -.08)
Return in week t + 1, (%)
FTSE is an
independent
company owned by
The Financial Times
and the London
Stock Exchange.
Their sole business
is the creation and
management of
indices and
associated data
services, on an
international scale.
Return in week t, (%)
Random Walk Theory: Weekly Returns,
May 1984 – May, 2004
Nikkei 500
Return in week t + 1, (%)
(correlation = -.06)
Return in week t, (%)
Random Walk Theory: Weekly Returns,
May 1984 – May, 2004
DAX 30
Return in week t + 1, (%)
(correlation = -.03)
Return in week t, (%)
Random Walk Theory: Weekly Returns,
May 1984 – May, 2004
S&P Composite
Return in week t + 1, (%)
(correlation = -.07)
Return in week t, (%)
Tests and Results of
Weak-Form EMH
• Statistical Tests of Independence
– Autocorrelation tests
• Test for correlation between prices today and prices tomorrow
• If EMH is true, would expect zero correlation
– Runs tests
• DeFusca et al, 2004
• Price increases assigned a positive sign; price decreases assigned a
negative sign. Test for randomness in the pattern of signs.
• Tests of Trading Rules
– Filter Rules
• A filter tells us to buy or sell depending on changes in market
variables
• The finer the filter, the higher the transactions costs
Tests and Results of
Weak-Form EMH
• Testing constraints
– Use only publicly available data
– Include all transactions costs
– Adjust the results for risk
• Only better-known technical trading rules have been
examined
– Too much subjective interpretation of data
– Almost infinite number of trading rules
• Results generally support the weak-form EMH, but results
are not unanimous
– Tests using actual transactions data have shown positive
correlation but not shown if profitable after transactions costs
Tests of the Semistrong Form of
Market Efficiency
Two types of studies
• Return prediction studies – Can we predict either:
– Time series analysis of returns (predict future returns for one stock)
– Cross sectional distribution of returns (predict which stocks will be
in the top decile, etc.)
• Event studies
– Examine how fast stock prices adjust to specific economic events
Tests and Results of
Semistrong-Form EMH
• Adjustment for Market Effects
– Test results should adjust a security’s rate of return for
the rate of return of the overall market during the period
considered
Abnormal rate of return
ARit = Rit - Rmt
where:
ARit = abnormal rate of return on security i during period t
Rit = rate of return on security i during period t
Rmt =rate of return on a market index during period t
Tests and Results of
Semistrong-Form EMH
• Time series tests for abnormal rates of return
– short-horizon return studies have had limited success
– long-horizon return studies have been quite successful
based on
• dividend yield (D/P)
• default spread – difference in yield between B bonds & AAA
bonds (acts as proxy for the market risk premium)
• term structure spread – difference in yield between short & long
Government bonds & T bills
– When D/P and the default spread are high, implies that
investors expect a high return on stocks & bonds. Tends
to occur during poor economic environments (low growth
rates and higher perceived risk by investors). Invest now
for high future returns!!
Tests and Results of
Semistrong-Form EMH
• More time series tests:
– Quarterly earnings reports may yield abnormal returns
due to
• Due to unanticipated earnings change
• Results suggest abnormal returns are earned in the 13 – 26
weeks after the announcement of large unanticipated earnings
changes (referred to as an earnings surprise)
• Studies by Rendleman et al found
– 31% of the change in stock price before the announcement
– 18% on the day of the announcement
– 51% following the announcement date
– These results do not support the EMH.
Tests and Results of
Semistrong-Form EMH
• The January Anomaly
– Stocks with negative returns during the year had higher
returns immediately after the first of the new year
• December trading volume abnormally high for these stocks
• Most of the January effect occurs on the first trading day in the
new year
– Tax selling toward the end of the year has been
mentioned as the reason for this phenomenon (although
a similar pattern has been found in countries with
different tax laws)
– Such a seasonal pattern is inconsistent with the EMH
Tests and Results of
Semistrong-Form EMH
• Other calendar effects
– All the market’s cumulative advance occurs during the
first half of trading months
– Monday/weekend returns were significantly negative
– For large firms, the negative Monday effect occurred
before the market opened (it was a weekend effect)
– For smaller firms, most of the negative Monday effect
occurred during the day on Monday (it was a Monday
trading effect)
Tests and Results of
Semistrong-Form EMH
• Predicting cross-sectional returns
– Basic premise: All securities should have equal, riskadjusted returns
• Studies examine alternative measures of size or
quality as a tool to rank stocks in terms of riskadjusted returns
– These tests involve a joint hypothesis and are
dependent both on market efficiency and the asset
pricing model used
Tests and Results of
Semistrong-Form EMH
• Price-earnings ratios and returns
– Low P/E stocks experienced superior risk-adjusted
results relative to the market, whereas high P/E stocks
had significantly inferior risk-adjusted results
– Publicly available P/E ratios possess valuable
information regarding future returns
• This is inconsistent with semistrong form
efficiency
Tests and Results of
Semistrong-Form EMH
• Price-Earnings/Growth Rate (PEG) ratios
– Studies have hypothesized an inverse relationship
between the PEG ratio and subsequent rates of return.
– This is inconsistent with the EMH
• However, the results related to using the PEG ratio to select
stocks are mixed
Tests and Results of
Semistrong-Form EMH
• The size effect (total market value)
– Several studies have examined the impact of size on
risk-adjusted rates of return
– The studies show that small firms consistently
experience significantly larger risk-adjusted returns
than large firms
• But some of the size effect seems to have disappeared
– Firm size is a major efficient market anomaly
Tests and Results of
Semistrong-Form EMH
• The P/E studies and size studies are dual tests of the EMH
and the CAPM
• Abnormal returns could occur because either
– Markets are inefficient or
– Market model is not properly specified and provides incorrect
estimates of risk and expected returns
Tests and Results of
Semistrong-Form EMH
• Neglected Firms
– Neglected firms are those firms not followed by many
analysts
– Neglected firm effect caused by lack of information and
limited institutional interest
– Small-firm effect was confirmed
– Another study contradicted the above results
– Neglected firm concept applied across size classes
Tests and Results of
Semistrong-Form EMH
• Ratio of Book Value of a firm’s Equity to Market
Value of its equity
– Significant positive relationship found between current
values for this ratio and future stock returns
– Results inconsistent with the EMH
• Size and BV/MV appear to dominate other ratios such as
P/E ratio or leverage
• This combination only works during periods of loose
monetary policy
Tests and Results of
Semistrong-Form EMH
• Event studies
– Stock split studies show that splits do not result in
abnormal gains after the split announcement, but before
– Initial public offerings seems to be underpriced by
almost 18%, but that varies over time, and the price is
adjusted within one day after the offering
• Suppose you had bought stock immediately following each
IPO & then held that stock for five years.
• Over the period 1970 – 2002, your average annual return
would have been 4.2% less than the return on a portfolio of
similar-sized stock
– Listing of a stock on an national exchange such as the
NYSE may offer some short term profit opportunities
for investors
Tests and Results of
Semistrong-Form EMH
• Event studies (continued)
– Stock prices quickly adjust to unexpected world events
and economic news and hence do not provide
opportunities for abnormal profits
• Patell & Wolfson found that when new information is released,
the major part of the adjustment in price occurs within 10
minutes of the announcement
– Announcements of accounting changes are quickly
adjusted for and do not seem to provide opportunities
– Stock prices rapidly adjust to corporate events such as
mergers and offerings
– The above studies provide support for the semistrongform EMH
Summary on the
Semistrong-Form EMH
• Evidence is mixed
– Strong support from numerous event studies with the
exception of exchange listing studies
– Studies on predicting rates of return for a cross-section
of stocks indicates markets are not semistrong efficient
• Dividend yields, risk premiums, calendar patterns, and
earnings surprises all appear to yield valuable information
• Predictors such as size, the BV/MV ratio (when there is
expansive monetary policy), P/E ratios, and neglected firms
also appear to yield valuable information
Tests and Results of
Strong-Form EMH
• Strong-form EMH contends that stock prices fully reflect
all information, both public and private
• This implies that no group of investors has access to
private information that will allow them to consistently
earn above-average profits
Testing Groups of Investors
•
•
•
•
Corporate insiders
Stock exchange specialists
Security analysts
Professional money managers
Corporate Insider Trading
• Insiders include major corporate officers, directors, and
owners of 10% or more of any equity class of securities
• Insiders must report to the Securities Commission within
10 calendar days of a transaction in the stock of the firm
for which they are an insider
• These insider trades are made public within minutes of
filing (note that the textbook refers to 6 weeks – in Canada,
it is within five minutes of filing)
• Corporate insiders generally experience above-average
profits especially on purchase transaction
Corporate Insider Trading
• This implies that many insiders had private information
from which they derived above-average returns on their
company stock
• Studies showed that public investors who traded with the
insiders based on announced transactions would have
enjoyed excess risk-adjusted returns (after commissions),
but the markets now seems to have eliminated this
inefficiency (soon after it was discovered)
• Other studies indicate that you can increase returns from
using insider trading information by combining it with key
financial ratios and considering what group of insiders is
doing the buying and selling
Stock Exchange Specialists
• Specialists have monopolistic access to information about
unfilled limit orders
• You would expect specialists to derive above-average
returns from this information
• The data generally supports this expectation
Security Analysts
• Tests have considered whether it is possible to identify a
set of analysts who have the ability to select undervalued
stocks
• The analysis involves determining whether, after a stock
selection by an analyst is made known, a significant
abnormal return is available to those who follow their
recommendations
• There is evidence in favor of the existence of superior
analysts
– Warren Buffet, Peter Lynch (Fidelity Magellan Fund)
Warren Buffet
• Buffet Partnership Ltd (1957 – 1969) beat the
Dow Jones Industrial Average every year of its
existence, with a cumulative return of 2,749%
versus the Dow’s cumulative return of 152.6%
• Buffet acquired Berkshire Hathaway in 1965.
• Since then he beat the return on the Dow in 36 out
of 41 years
• After tax cumulative return of 305,134% versus
5,583% (pre-tax) for the Dow.
Ivan Boesky
• By 1986 Ivan Boesky had become an arbitrageur who had
amassed a fortune of about US$200 million by betting on
corporate takeovers.
• He was investigated by the US SEC for making
investments based on tips received from corporate insiders.
• These stock acquisitions were sometimes brazen, with
massive purchases occurring only a few days before a
corporation announced a takeover.
• Although insider trading of this kind was illegal, laws
prohibiting it were rarely enforced until Boesky was
prosecuted.
• Boesky cooperated with the SEC and informed on several
of his insiders, including junk bond trader Michael Milken.
• As a result of a plea bargain, Boesky received a prison
sentence of 3.5 years and was fined US$100 million.
• Although he was released after two years, he was barred
from working in the securities business for the remainder
of his life.
The Value Line Enigma
• Value Line (VL) publishes financial information on about
1,700 stocks
• The report includes a timing rank from 1 down to 5
• Firms ranked 1 substantially outperform the market
• Firms ranked 5 substantially underperform the market
• Changes in rankings result in a fast price adjustment
• Some contend that the Value Line effect is merely the
unexpected earnings anomaly due to changes in rankings
from unexpected earnings
Professional Money Managers
• Trained professionals, working full time at investment
management
• If any investor can achieve above-average returns, it
should be this group
• If any non-insider can obtain inside information, it would
be this group due to the extensive management interviews
that they conduct
Performance of
Professional Money Managers
• Most tests examine mutual funds
• New tests also examine trust departments, insurance
companies, and investment advisors
• Risk-adjusted, after expenses, returns of mutual funds
generally show that most funds did not match aggregate
market performance
– Mark Carhart analyzed 1,493 mutual funds to see if professional
money managers could out-perform the market
– He found that, on average, mutual funds earn a lower return than
the benchmark after expenses and roughly match the benchmark
return before expenses
Conclusions Regarding the
Strong-Form EMH
• Mixed results, but much support
• Tests for corporate insiders and stock exchange specialists
do not support the hypothesis
– Both groups seem to have monopolistic access to important
information and use it to derive above-average returns
• Tests results for analysts are concentrated on Value Line
rankings
– Results have changed over time
– Currently tend to support EMH
• Individual analyst recommendations seem to contain
significant information
• Performance of professional money managers seem to
provide support for strong-form EMH
Behavioral Finance
It is concerned with the analysis of various psychological
traits of individuals and how these traits affect the manner
in which they act as investors, analysts, and portfolio
managers
Explaining Biases
• Prospect theory
– Investors fear losses more than they value gains
– Hold losers too long and sell winners too quickly
• Overconfidence (confirmation bias)
– Look for information that supports prior opinions and
decisions
• Noise traders
– Tend to follow newsletter writers, who are almost
always wrong
– Tend to move as a herd, increasing volatility
• Escalation bias
– Add money to failures rather than successes
– Concept of averaging down
Fusion Investing
• The integration of two elements of investment
valuation
– Fundamental value
– Investor sentiment
• Fundamental value is equal to the PV of expected
future cash flows
• Investor sentiment driven by noise traders
– When noise traders are bullish, stock prices above
fundamental value
– When noise traders are bearish, stock prices are below
fundamental value
• Therefore, consider both fundamental value &
investor sentiment prior to buying or selling
Implications of
Efficient Capital Markets
• Overall results indicate the capital markets are efficient as
related to numerous sets of information
• However, there are substantial instances where the market
fails to rapidly adjust to public information
Efficient Markets
and Technical Analysis
• Assumptions of technical analysis directly oppose the
notion of efficient markets
• Technicians believe that new information is not
immediately available to everyone, but disseminated from
the informed professional first to the aggressive investing
public and then to the masses
• Technicians also believe that investors do not analyze
information and act immediately - it takes time
• Therefore, stock prices move to a new equilibrium after the
release of new information in a gradual manner, causing
trends in stock price movements that persist for periods of
time
Efficient Markets
and Technical Analysis
• Technical analysts develop systems to detect movement to
a new equilibrium (breakout) and trade based on that
• Contradicts rapid price adjustments indicated by the EMH
• If the capital market is weak-form efficient, a trading
system that depends on past trading data can have no value
Efficient Markets
and Fundamental Analysis
• Fundamental analysts believe that there is a basic intrinsic
value for the aggregate stock market, various industries, or
individual securities and these values depend on
underlying economic factors
• Investors should determine the intrinsic value of an
investment at a point in time and compare it to the market
price
Efficient Markets
and Fundamental Analysis
• If you can do a superior job of estimating intrinsic value
you can make superior market timing decisions and
generate above-average returns
• This involves aggregate market analysis, industry analysis,
company analysis, and portfolio management
• Intrinsic value analysis should start with aggregate market
analysis
Aggregate Market Analysis
with Efficient Capital Markets
• EMH implies that examining only past economic events is
not likely to lead to outperforming a buy-and-hold policy
because the market adjusts rapidly to known economic
events
• Merely using historical data to estimate future values is not
sufficient
• You must estimate the relevant variables that cause longrun movements
Industry and Company Analysis
with Efficient Capital Markets
• Wide distribution of returns from different industries and
companies justifies industry and company analysis
• Must
– Understand the variables that effect rates of return
– Do a superior job of estimating future values of these relevant
valuation variables, not just look at past data
• Important relationship between expected earnings and
actual earnings
– Must accurately predict earnings surprises
• Strong-form EMH indicates likely existence of superior
analysts
• Studies indicate that fundamental analysis based on P/E
ratios, size, and the BV/MV ratios can lead to abnormal
returns
How to Evaluate Analysts or
Investors
• Examine the performance of numerous securities that this
analyst recommends over time in relation to a set of
randomly selected stocks in the same risk class
• Selected stocks should consistently outperform the
randomly selected stocks
Conclusion about Fundamental
Analysis
• Estimating the relevant variables is as much an art and a
product of hard work as it is a science
• The successful investor must understand what variables are
relevant to the valuation processes and have the ability and
work ethic to do a superior job of estimating these
important valuation variables
Efficient Markets
and Portfolio Management
• Portfolio Managers with Superior Analysts
– Concentrate efforts in mid-cap stocks that do not
receive the attention given by institutional portfolio
managers to the top-tier stocks
– The market for these neglected stocks may be less
efficient than the market for large well-known stocks
Efficient Markets
and Portfolio Management
• Portfolio Managers without Superior Analysts
– Determine and quantify your client's risk preferences
– Construct the appropriate portfolio
– Diversify completely on a global basis to eliminate all
unsystematic risk
– Maintain the desired risk level by rebalancing the
portfolio whenever necessary
– Minimize total transaction costs
The Rationale and
Use of Index Funds and ExchangeTraded Funds
• Efficient capital markets and a lack of superior analysts
imply that many portfolios should be managed passively
(so their performance matches the aggregate market &
minimizes the costs of research and trading)
• ETFs duplicate the composition and performance of many
indices
Insights from Behavioral Finance
• Growth companies will usually not be growth stocks due
to the overconfidence of analysts regarding future growth
rates and valuations
• Notion of “herd mentality” of analysts in stock
recommendations or quarterly earnings estimates is
confirmed
The Internet
Investments Online
http://www.bloomberg.com
http://news.ft.com
http://www.online.wsj.com
http://finance.yahoo.com
http://money.cnn.com
http://www.cnbc.com
http://www.abcnews.com
http://www.nbcnews.com
http://www.msnbc.msn.com