Efficient Market Hypothesis
by
Indrani Pramanick (44)
A Description of Efficient Capital
Markets
 An efficient capital market is one in which stock prices
fully reflect available information.
 The EMH has implications for investors and firms.
 Since information is reflected in security prices quickly,
knowing information when it is released does an investor no good.
 Firms should expect to receive the fair value for securities that
they sell. Firms cannot profit from fooling investors in an
efficient market.
History
 Prior to the 1950’s it was generally believed that the use of
fundamental or technical approaches could “beat the market”
(though technical analysis has always been seen as something akin
to voodoo).
 In the 1950’s and 1960’s studies began to provide evidence against
this view.
 In particular, researchers found that stock price changes (not
prices themselves) followed a “random walk.”
 They also found that stock prices reacted to new information
almost instantly, not gradually as had been believed.
The Efficient Markets Hypothesis
 The Efficient Markets Hypothesis (EMH) is made up of three
progressively stronger forms:
 Weak Form
 Semi-strong Form
 Strong Form
The EMH Graphically
 In this diagram, the circles
All historical prices and returns
represent the amount of
information that each form of the
EMH includes.
 Note that the weak form covers the
least amount of information, and
the strong form covers all
information.
 Also note that each successive form
includes the previous ones.
All information, public and private
Strong Form
Semi-Strong
Weak Form
All public information
The Weak Form
 The weak form of the EMH says that past prices, volume, and other market
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statistics provide no information that can be used to predict future prices.
If stock price changes are random, then past prices cannot be used to forecast
future prices.
Price changes should be random because it is information that drives these
changes, and information arrives randomly.
Prices should change very quickly and to the correct level when new
information arrives (see next slide).
This form of the EMH, if correct, repudiates technical analysis.
Most research supports the notion that the markets are weak form efficient.
Tests of the Weak Form
 Serial correlations.
 Runs tests.
 Filter rules.
 Relative strength tests.
 Many studies have been done, and nearly all support weak
form efficiency, though there have been a few anomalous
results.
Serial Correlations
 The following chart shows the relationship (there is none)
between S&P 500 returns each month and the returns from the
previous month. Data are from Feb. 1950 to Sept. 2001.
 Note that the R2 is virtually 0 which means that knowing last
month’s return does no good in predicting this month’s return.
 Also, notice that the trend line is virtually flat (slope = 0.008207,
t-statistic = 0.2029, not even close to significant)
 The correlation coefficient for this data set is 0.82%
Serial Correlations (cont.)
Unlagged vs One-month Lagged S&P 500
Returns
y = 0.008207x + 0.007451
2
R = 0.000067
Unlagged Returns
20.00%
10.00%
0.00%
-10.00%
-20.00%
-30.00%
-30.00%
-20.00%
-10.00%
0.00%
10.00%
One-month Lagged Returns
20.00%
The Semi-strong Form
 The semi-strong form says that prices fully reflect all publicly
available information and expectations about the future.
 This suggests that prices adjust very rapidly to new information,
and that old information cannot be used to earn superior returns.
 The semi-strong form, if correct, repudiates fundamental analysis.
 Most studies find that the markets are reasonably efficient in this
sense, but the evidence is somewhat mixed.
Tests of the Semi-strong Form
 Event Studies
 Stock splits
 Earnings announcements
 Analysts recommendations
 Cross-Sectional Return Prediction
 Firm size
 BV/MV
 P/E
Analysts’ Performance
This chart from the Wall Street Journal, shows that when analysts issue sell
recommendations, those stocks frequently outperform those with buy or hold ratings. If
the professionals can’t get it right, who can?
Mutual Fund Performance
 Generally, most academic studies have found that mutual funds do
not consistently outperform their benchmarks, especially after
adjusting for risk and fees.
 Even choosing only past best performing funds (say, 5-star funds
by Morningstar) is of little help. A study by Blake and Morey finds
that 5-star funds don’t significantly outperform 3- and 4-star funds
over time.
 However, it does seem that you can “weed out” the bad funds (1and 2-stars). Funds that have performed badly in the past seem to
continually perform badly in the future.
The Strong Form
 The strong form says that prices fully reflect all information,
whether publicly available or not.
 Even the knowledge of material, non-public information
cannot be used to earn superior results.
 Most studies have found that the markets are not efficient in
this sense.
Tests of the Strong Form
 Corporate Insiders.
 Specialists.
 Mutual Funds.
 Studies have shown that insiders and specialists often earn
excessive profits, but mutual funds (and other professionally
managed funds) do not.
 In fact, in most years, around 85% of all mutual funds
underperform the market.
Anomalies
 Anomalies are unexplained empirical results that contradict
the EMH:
 The Size effect.
 The “Incredible” January Effect.
 P/E Effect.
 Day of the Week (Monday Effect).
The Size Effect
 Beginning in the early 1980’s a number of studies found that
the stocks of small firms typically outperform (on a riskadjusted basis) the stocks of large firms.
 This is even true among the large-capitalization stocks within
the S&P 500. The smaller (but still large) stocks tend to
outperform the really large ones.
The “Incredible” January Effect
 Stock returns appear to be higher in January than in other
months of the year.
 This may be related to the size effect since it is mostly small
firms that outperform in January.
 It may also be related to end of year tax selling.
The P/E Effect
 It has been found that portfolios of “low P/E” stocks
generally outperform portfolios of “high P/E” stocks.
 This may be related to the size effect since there is a high
correlation between the stock price and the P/E.
 It may be that buying low P/E stocks is essentially the same
as buying small company stocks.
The Day of the Week Effect
 Based on daily stock prices from 1963 to 1985 Keim found that
returns are higher on Fridays and lower on Mondays than should
be expected.
 This is partly due to the fact that Monday returns actually reflect
the entire Friday close to Monday close time period (weekend
plus Monday), rather than just one day.
 Moreover, after the stock market crash in 1987, this effect
disappeared completely and Monday became the best performing
day of the week between 1989 and 1998.
Summary of Tests of the EMH
 Weak form is supported, so technical analysis cannot consistently
outperform the market.
 Semi-strong form is mostly supported , so fundamental analysis
cannot consistently outperform the market.
 Strong form is generally not supported. If you have secret
(“insider”) information, you CAN use it to earn excess returns on
a consistent basis.
 Ultimately, most believe that the market is very efficient, though
not perfectly efficient. It is unlikely that any system of analysis
could consistently and significantly beat the market (adjusted for
costs and risk) over the long run.