Download The Efficient Market Hypothesis

The Efficient Market Hypothesis
Dr. Himanshu Joshi
FORE School of Management
New Delhi
The Efficient Market Hypothesis
• One of the earliest application of computers in
economics was to analyze economic time
series. Business theorist felt that tracing the
evolution of several economic variables over
time would clarify and predict the progress of
the economy through boom and bust periods.
Assumption for stock prices..
• A natural candidate for analysis was the
behavior of stock market prices over time.
• Assuming that stock market prices reflect
prospects of the firm, recurrent patterns of
peaks and trough in economic performance
ought to show up in these prices.
The Experiment and the Result..
• Maurice Kendall examined this proposition in
1953. he found to his great surprise that he could
identify no predictable patterns in stock prices.
• Prices seems to evolve randomly.
• They were likely to go up as they were to go
down on any particular day, regardless of past
performance.
• The data provided no way to predict price
movements.
Interpretation..
• Kendall’s results were disturbing to some
financial economists. They seemed to imply
that stock market is dominated by erratic
market psychology. It follows no logical rules.
• So result seems to confirmed irrationality of
the market.
Random Walks and the Efficient
Market Hypothesis
• Suppose Kendall had discovered that stock
prices are predictable.
• What a gold mine this would have been.
• If they could use the Kendall’s equations to
predict stock prices, investors would reap
unending profits simply by purchasing stocks
that the computer model implied were about
to increase in price and by selling those stocks
about to fall in price.
Model predicts???
• Suppose model predict with great confidence
that Infosys share, currently at $100 would
increase dramatically in 3 days to $110.
• What would all investors with access to the
model’s prediction do today?
• When price of Infosys will reach $110.
Model?
• This simple example illustrate why Kendall's
attempt to find recurrent patterns in stock
price movements was likely to fail.
• A forecast about favorable future price
performance leads to favorable current
performance, as market participants all try to
get into the action before price jump.
Revised Interpretation of Random
Walk.
• Any information that could be used to predict
stock performance should already be reflected in
stock prices.
• As soon as there is any information indicating
that stock is underpriced and therefore offer a
profit opportunity, investors flock to buy the
stock and immediately bid up its price to a fair
level, where only ordinary rates of return can be
expected.
• These “ordinary rates” are simply rate of return
commensurate with the risk of the stock.
Random Walk and EMH..
• This is the essence of the argument that stock
prices should follow a random walk, that is
that price should be random and
unpredictable.
• Therefore, the notion that stocks already
reflect all available information is referred to
as the efficient market hypothesis. (EMH.)
Application.
• On January 9, 2009, Sensex fell from 9586.88 points to
9406.47 points, a decline of 1.88%. If the sale of
Siemens Information Systems Limited is a value-neutral
decision, then Siemen’s stock price should have fallen
by 1.88% × 0.86, that is 1.62%.
• However, on Jan 9, 2009, the price of Siemens fell from
298 to 260.7, a decline of 12.52%. If we assume that on
January 9, 2009 the stock market did not get any other
value relevant information about Siemens (other than
the sale of its 100% subsidiary), then the entire
difference of 10.9% decline (12.52% - 1.62%) can be
attributed to this sale transaction.
Examples of Random Walk
Cumulative Abnormal Returns Before Takeover
Attempts: Target Companies
Examples of Random Walk
Stock Price Reaction to CNBC Reports
Competition as the source of
efficiency.
• Stock prices fully and accurately reflect
publicly available information.
• Once information becomes available, market
participants analyze it.
• Competition assures prices reflect
information.
IS Equity Research is a Wasteful
Exercise?
Competition as the source of
efficiency..
• Why should we expect stock prices to reflect all available
information?
• After all if you are willing to spend time and money on gathering
information, it might seem reasonable that you could turn up
something that has been overlooked by the rest of the investment
community.
• When information is costly to uncover and analyze, one would
expect investment analysis calling for such expenditures to result in
an increased expected return.
• Investors will have an incentive to spend time and resources to
analyze and uncover new information only if such activity is likely to
generate higher investment returns.
• Thus, in market equilibrium, efficient information gathering should
be fruitful.
Versions of the EMH
• Weak
(Stock Prices reflect all past trends)
• Semi-strong
(Stock Prices reflect all public information)
• Strong
(Stock Prices reflect all information public or
private)
Quiz?
Q1.Suppose you observe that high level managers
make superior returns on investments in their
company’s stock. Would this be violation of weakform market efficiency? Would it be violation of
semi strong form market efficiency?
Q2.If the weak form of the efficient market
hypothesis is valid, must the strong form also
hold?
• Conversely, does strong-form efficiency imply
weak form efficiency?
Types of Stock Analysis
• Technical Analysis - using prices and volume
information to predict future prices
– Weak form efficiency & technical analysis
• Fundamental Analysis - using economic and
accounting information to predict stock prices
– Semi strong form efficiency & fundamental
analysis
Technical Analysis
• Technical analysis is essentially the search for
recurrent and predictable patterns in stock prices.
• Although Technicians recognize the value of
information regarding future economic prospects
of the firm, they believe that such information is
not necessary for successful trading strategy.
• This is because whatever the fundamental reason
for change in stock price, if the stock price
responds slowly enough, the analyst will be able
to identify a trend that can be exploited during
the adjustment period.
Technical Analysis
• Thus the key to successful technical analysis is
a sluggish response of stock prices to
fundamental supply and demand factors.
• This prerequisite is of course, diametrically
opposed to the notion of an efficient market
hypothesis.
Technical Analysis
• Relative Strength Approach (Ratio of Stock
Price to Market Indicator)
• Resistance and Support level.
If everyone in the market believe in
resistance levels, why do these beliefs
not become self-fulfilling prophecies?
• The market dynamic is one of a continual
search for profitable trading rules, followed by
destruction by overuse of those rule found to
be successful, followed by more search for yet
to be discovered rules.
Fundamental Analysis
• Fundamental Analysis uses earnings and
dividend prospects of the firm, expected
future interest rates, and risk evaluation of the
firm to determine proper stock prices.
• Here we try to determine present discounted
value of all the payments a stockholder will
receive from each share of stock.
• If the value exceeds the stock price, buy it.
Fundamental Analysis
• FCFF
• FCFE
Active or Passive Management
• Active Management
– Security analysis
– Timing
• Passive Management
– Buy and Hold
– Index Funds
EXAMPLE
Money Magazine – Oct. 03
Top Picks from 24 Top Pros – Invest in the Best
• Asked some “first-rate investing minds to share their best
ideas.”
• “We call this gathering of wise minds the Ultimate
Investment Club.”
• The 24 top pros identified 34 domestically traded stocks as
their top picks.
• Each pick was backed by brilliant and compelling logic.
27
THE STORY MONEY MAGAZINE NEVER PUBLISHED
BUT THE COLORADO SPRINGS BUSINESS JOURNAL DID
The Ultimate Investment Club destroyed 14% vs. the Market!
First Rate Investing
Minds
US Stock Market
-2.4%
+11.5%
Twelve months ended August 31, 2004. Source: Calculated from Yahoo Finance - included dividend reinvestment. This
included six stock picks listed on US exchanges but not included in the Wilshire 5000 Total Stock Index. The 28 US domiciled
stocks had a -7.6% return which lagged the index by 19%.
Market Efficiency & Portfolio Management
Even if the market is efficient a role exists for
portfolio management:
• Appropriate risk level
• Tax considerations
• Other considerations
Event Studies
• Empirical financial research that enables an
observer to assess the impact of a particular
event on a firm’s stock price
• Abnormal return due to the event is estimated as
the difference between the stock’s actual return
and a proxy for the stock’s return in the absence
of the event
How Tests Are Structured
•
Returns are adjusted to determine if they are
abnormal
Market Model approach
a. rt = at + brmt + et
(Expected Return)
b. Excess Return =
(Actual - Expected)
et = rt - (a + brMt)
Are Markets Efficient?
• Magnitude Issue
• Selection Bias Issue
• Lucky Event Issue
Are Markets Efficient?
• Magnitude Issue: Bodie and Kane noted that an
investment manager overseeing a $5 billion portfolio
who can improve performance by only 0.1% per year will
increase investment earning by $5 billion*0.1% = $5
million.
• The manager clearly would worth her salary.
• Can we statistically measure her contribution?
• Given the annual SD of S&P 500 portfolio is 20%.
• All might agree that stock prices are very close to fair
values and that only managers of very large portfolios
can earn enough trading profits to make the exploitation
of minor mis-pricing worth the effort.
• Are market efficient? Should now be how efficient are
markets?
Are Market efficient?
• The Selection Bias:
• Suppose that you discover an investment
scheme that could really make money.
• You have two choice:
• Either publish your technique in ‘wall street
journal’ to win fleeting fame, or
• Keep your technique secret and use it to earn
millions of dollars.
Selection bias..
• Only investors who find that an investment
scheme can not generate abnormal return will
be willing to report their finding to the whole
world.
• This is called selection bias: the outcome we
are able to observe are preselected in favor of
failed attempts.
Are market efficient?
• The Lucky Event Issue: in virtually any month it
seems we read an article about some investor
or investment company with fantastic
investment performance over the recent past.
• Surely the superior records of such investors
disprove the efficient market hypothesis.
The Lucky Event Issue..
• Consider a contest to flip the most number of
heads out of 50 trials using a fair coin.
• The expected outcome for any person, is of
course, 50% heads and 50% tails.
• If 10,000 people, however compete in this
contest, it would not be surprising if atleast one
or two contestant flipped more than 75% heads.
• In fact statistically there will be 2 contestants
flipping more than 75% heads.
• It would be silly to crown these people the “the
head flipping champions of the world”.
The Lucky Event Issue
• The analogy to efficient market is clear.
• Under the hypothesis that any stock is fairly
priced given all available information, any bet
on a stock is a simply a coin toss.
• The winners, though, turn up in Wall Street
Journal as the latest STOCK MARKET GURUS.
Then they can make fortune publishing market
newsletters and providing market buy, sell or
hold advice.
Weak-Form Tests: Pattern in Stock Return
• Returns over the Short Horizons: could speculators find
trends in past prices that would enable them to earn
abnormal profits?
– Momentum & Serial Correlation
– Serial correlation refers to the tendency for stock
returns to be related to past returns.
– Positive serial correlation means that positive returns
tend to follow positive returns (Momentum property)
– Negative serial correlation means that negative
returns tend to be followed by positive returns. (A
reversal or correction property).
Returns over short Horizons
Empirical Evidences
• Conrad and Kaul and Lo and MacKinlay examine weekly
returns of NYSE stocks and find positive serial correlation
over short horizons.
• However correlation coefficient of weekly returns tends to
be fairly small, at least for large stocks for which price data
are the most reliably up-to-date.
• There appears to be stronger momentum in performance
across market sectors exhibiting best and worst recent
returns.
• In an investigation of intermediate –horizon stock price
behaviour (3-12 months) Jagdeesh and Titman found a
momentum effect in which good or bad recent
performance of particular stock continues over time.
Returns over Long Horizons
• Long term horizon returns (i.e., return over multiyear
periods) have found suggestions of pronounced
negative long term serial correlation in the
performance of aggregate market.
• fad hypothesis: it asserts that stock market may over
react to relevant news. Such overreaction leads to
positive serial correlation (momentum) over short time
horizons. Subsequent correction of the overreaction
leads to poor performance following good
performance and vice versa.
• These episodes of apparent overshooting followed by
correction give stock market the appearance of
fluctuating around its fair value.
Predictors of Broad Market Returns
• Fama and French
– Aggregate returns are higher with higher
dividend ratios
• Campbell and Shiller
– Earnings yield can predict market returns
• Keim and Stambaugh
– Bond spreads can predict market returns
Semistrong Tests: Anomalies
• P/E Effect (Sanjoy Basu)
• Small Firm Effect (Banz)
• Neglected Firm Effect and Liquidity Effects (Arbel
and Strebel)
• Book-to-Market Ratios
• Post-Earnings Announcement Price Drift
The Neglected Firm Effect and
Liquidity Effect
• Arbel and Strebel gave another interpretation of smallfirm-in-January effect. Because small firms tend to be
neglected by large institutional investors, information
about smaller firms is less available.
• This information deficiency makes smaller firms riskier
investments that command higher returns.
• “Brand name” firms are after all subject to
considerable monitoring from institutional investors,
which promises high quality information, and investors
presumably do not purchase “generic stocks” without
prospects of greater returns.
Figure 11.3 Average Annual Return for 10 SizeBased Portfolios, 1926 – 2006
Average Return as a Function of BookTo-Market Ratio (FAMA and FRENCH
Model)
• Fama and French showed that a powerful
predictor of returns across securities is the
ratio of the book value of the firm’s equity to
the market value of equity.
Figure 11.4 Average Return as a Function of BookTo-Market Ratio,
1926–2006
Result..
• The deciles with highest book-to-market ratio had
an annual return of 16.84%, while the lowest
decile averaged only 11.12%.
• The dramatic dependence of return on book to
market ratio of the firm is independent of beta,
suggesting either that:
• High book-to-market ratio firms are relatively
underpriced (inefficient market)
• Or that the book-to-market ratio is serving as a
proxy for a risk factor that affects equilibrium
expected return.
Cumulative Abnormal Returns in
Response to Earnings Announcements
• A fundamental principle of efficient market is
that any new information ought to be
reflected in stock price very rapidly. When
good news is made public, the stock price
should jump immediately.
• A puzzling anomaly, is therefore, sluggish
response of stock prices to firm’s earning
announcements, as discovered by Ball and
Brown.
Cumulative Abnormal Returns in
Response to Earnings Announcements
• Randleman, Jones and Latane provide
influential study of sluggish price response to
earning surprises for a large sample of firms,
rank the magnitude of the surprise, divide
firms into 10 deciles based on size of surprise,
and calculate abnormal returns for each
decile.
Figure 11.5 Cumulative Abnormal Returns in
Response to Earnings Announcements
Results
• There is a large abnormal return (a jump in
cumulative abnormal return) on the earning
announcement day (day 0).
• The abnormal return is positive for positivesurprise firm and negative for negative-surprise
firms.
• The more remarkable result of the study is that
even after the announcement date stock price of
positive-surprise firms continue to rise.
• In other words, exhibits momentum-even after
the earning information become public.
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
• SEBI requires all insiders to register their trading
activity
Interpreting the Evidence
• Risk Premiums or market inefficiencies—
disagreement here
– Fama and French argue that these effects can
be explained as manifestations of risky stocks
with higher betas
– Lakonishok, Shleifer, and Vishney argue that
these effects are evidence of inefficient
markets
Interpreting the Evidence Continued
• Anomalies or Data Mining
• The noisy market hypothesis
• Fundamental indexing
Noisy Market Hypothesis and
Fundamental Indexing
• The EMH argues in favor of Capitalization-weighted
indexed portfolios that provides broad diversification
with minimal trading costs.
• but several researchers and practitioners have
forcefully argued that such “cap-Weighted” indexing is
necessarily inferior to a strategy they call fundamental
indexing.
• It is called noisy market hypothesis. The hypothesis
begin with the observation that market prices may well
contain pricing errors or “noise” relative to intrinsic
value or true value of a firm.
Noisy Market Hypothesis and
Fundamental Indexing
• Even if prices are correct on average, at any time some
stocks will be overvalued and others undervalued.
• Because indexed portfolios invest in proportion to
market capitalization, portfolio weights will track these
pricing error, with greater amounts invested in
overpriced stocks (which have poor expected returns)
and lesser amounts in underpriced stocks (which have
higher expected return)
• The conclusion is that a capitalization weighted
strategy is destined to overweight the firms with the
worst returns propects.
Stock Market Analysts
• Do Analysts Add Value
– Mixed evidence
– Ambiguity in results
•Thank You