“A blindfolded monkey
throwing darts at a newspaper’s financial pages could select a portfolio that
would do just as well as one carefully selected by the experts” –
quotes Burton Malkeil[i]
on market efficiency theory. Efficient Market Hypothesis, term coined
by Eugene Fama[ii]
way back in 1970, and further studies in the area went onto earn him
the Nobel. The theory stated that markets are efficient or intelligent enough
to subsume all the information relating to firms in general and the price
discovered by market is the right price. When, market has used every bit of
information in arriving at the price, no one individual market participant can
make an excess or abnormal return by beating the market’s intelligence. Only
arrival of new information can lead to a change in the price, and the invisible
angel in the market will very soon bring the price to incorporate the new
information also and thus leaving no further speculative opportunity.
The theory is further enhanced by
dividing the level of efficiency on the basis of the kind of information that
could have been subsumed by the market. If we presume that a given market is
using all the historical information relating to a scrip, we call the market to
be efficient in its weak-form; if it is presumed that along with
historical data, the market is also using publicly available information,
including market sentiments, rumors and expert opinions, we call the market to
be semi-strong efficient; and finally if we presume market has access to
information that is privately known to only the insiders, and the price
discovery mechanism uses such data also, we call the market to be efficient in
its strong form.
EMH being a theory, even though
seems logical enough, it needs extensive research across markets, across time
lines, and through different statistical tests. Hence, EMH studies are a
regular research problems, being attempted by capital market researchers since
decades and it continues till date.
Semi-Efficient Market Hypothesis
One of the trigger during such
research series was to test whether the entire market is efficient, or it is
the individual stocks that are efficiently priced. It was then observed that
most significant contributions to these theories have concluded based on their
tests conducted on a market as a whole, and not individual scripts. Prasanna
Chandra[iii] puts it as below:
‘The
efficient market hypothesis (EMH) has a cousin, the semi-efficient market
hypothesis (SEMH). SEMH holds that some stocks are priced more efficiently than
others. Consider two companies, Infosys and a hypothetical start-up firm called
Nuvo Software. Infosys is followed by many investors and actively traded.
Thousands of portfolios would contain Infosys shares and innumerable security
analysts follow it. Hence it likely to be fairly priced. What about Nuvo
Software? Very few people follow it; so according to SEMH there is a greater
likelihood that it will be mispriced. Extending this idea, one may argue that
the market perhaps has several tiers. Put differently, there is a pecking order
of efficiency. Most observers of the market are generally sympathetic of the
logic of SEMH”
Two observations from the above
explanation by the author. One, it may make more sense to study individual
stocks to determine the efficiency of a market. Two, efficiency of a market
follows a pecking order and hence, it would be impossible for one to put a
dichotomizing line between an efficiently priced and a not-so-efficiently priced
scrip, as the pecking order is more discrete than continuous.
Sample study for SEMH
We have conducted a sample study
on 12 stocks from Indian markets, 4 each from large cap, midcap and small cap
to analyse if the prices follow a pattern among these stocks. In essence, we
are checking for the weak-form of efficiency (i.e., whether the market
determined prices of these stocks are randomly priced, and if so, we conclude
that market has used all the historical information, in the form of historical
prices, and efficient in its weak-form) of each scrip. Based on the results we
can derive inputs for SEMH theory.
Stocks Selected
Stocks
selected using convenience sampling as below:
Large-Cap
(forming first 75% of market cap): Infosys,
BPCL, SBIN & Tata Steel (random 4 from CNX
NIFTY)
Mid-Cap
(forming market cap between 75th percentile
to 90th percentile) : Petronet LNG, Reliance Communications,
Marico Ltd, Pidilite Industries Limited (random 4 from CNX Midcap)
Small-cap
(forming market cap between 90th percentile
to 95th percentile): Cox & Kings Ltd., Gati Ltd., Raymond
Ltd., Zydus Wellness Ltd., (random 4 from CNX Smallcap)
Methodology used
As the objective is to test the
random movement of the stock prices, a non-parametric runs test is conducted.
Runs test follows the mechanism of designating a plus (+) sign when there is
increase in price and a minus (-) sign when a decrease in price occurs, when
the stock prices are arranged chronologically. A run occurs when there is no
difference between the sign of two changes. When the sign of change differs,
the run ends and a new run begins. The total number of runs of a series of
stock prices are then tested for statistical significance (i.e., whether the
runs of the given sample series statistically differs from the number of runs
of a purely random series of the same size). Thus for our study we tested for
randomness using runs test of the 12 selected stocks based on their weekly
closing prices. The hypothesis tested hence for each script was in the below
form:
H0: The weekly closing price series of
Infosys is randomly distributed
H1: The weekly closing price series of
Infosys is not randomly distributed
Test Conducted: One-Sample
Runs Test, around the mean
Decision
Criterion: Reject the Null Hypothesis if the sig. value is less than 0.05
(95% con. level)
Results
Test for randomness as above is conducted using SPSS 23.0 v. and the
results are provided in the table below:
Interpretation
Null
Hypothesis is rejected in ALL CASES, submitting proof to infer that “all
the selected scrips, across market capitalizations, do not follow random walk,
hence, none are efficiently priced in their weak-form”.
Based
on the above, we can also interpret that, SEMH also does not hold gold. This is
evident in the sample case that we have tested above, where all the stocks have
emerged to be inefficiently priced.
Conclusion
Contrary to the arguments of few
researchers, on the pecking order of efficiency, above results deduce the
absence of such order and also leaves ample scope for further stimulations to
question the existence of SEMH.
It may be noted that the above
conclusions are based on sample study. As has already been mentioned, either
EMH or SEMH is still a ‘Hypothesis’ and demands further research using
different sample, sample size, timeframe, testing tools and markets.
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