Capital Asset Pricing Model: The Indian
Context
R Vaidyanathan
T
he Capital Asset Pricing model is based on two parameter portfolio analysis
model developed by Markowitz (1952). This model was simultaneously and
independently developed by John Lintner (1965), Jan Mossin (1966) and
William Sharpe (1964). In equation form the model can be expressed as
follows:
E (Ri) = Rf + i [E(rm) – Rf] = Rf +im / m (E(Rm) – Rf / m)
Where E(Ri) is expected return on asset i, Rf is the risk-free rate of return, E(Rm) is
expected return on market proxy and i; is a measure of risk specific to asset i. This
relationship between expected return on asset i and expected return on market portfolio is
also called the security market line. If CAPM is valid, all securities will lie in a straight
line called the security market line in the E(R), i frontier. The security market line
implies that return is a linearly increasing function of risk. Moreover, only the market risk
affects the return and the investor receive no extra return for bearing diversifiable
(residual) risk.
The set of assumptions employed in the development of the CAPM can be
summarized as follows [Sears and Trennepohl (1993)]:
1. Investors are risk-averse and they have a preference for expected return and a
dislike for risk.
2. Investors make investment decisions based on expected return and the variances of
security returns, i.e. two-parameter utility function.
3. Investors behave in a normative sense and desire to hold a portfolio that lies along
the efficient frontier.
These three assumptions were also made in the development of the Markowitz and
Sharpe single-index portfolio analysis models. In addition to these three, CAPM also
makes the following assumptions.
4. There exists a riskless asset and investors can lend or invest at the riskless rate and
also borrow at this rate in any moment.
5. All investments are perfectly divisible. This means that every security and
portfolio is equivalent to a mutual fund and that fractional shares for any investment can
be purchased in any amount.
6. All investors have homogenous expectations with regard to investment horizons or
holding periods and to forecasted expected returns and risk levels on securities. This
means that investors form their investment portfolios and revise them at the same
interval of time
Research Papers in Applied Finance
(e.g., every six months). Furthermore, there is complete agreement among investors as to
the return distribution for each security or portfolio.
7. There are no imperfections or frictions in the market to impede investor buying
and selling. Specifically, there are no taxes or commissions involved with security
transactions. Thus there are no costs involved in diversification and there is no
differential tax treatment of capital gains and ordinary income.
8. There is no uncertainty about expected inflation; or, alternatively all security prices
fully reflect all changes in future inflation expectations.
9. Capital markets are in equilibrium. That is, all investment decisions have been
made
and there is no further trading without new information.
Some of the above assumptions are clearly unrealistic. However, the assumptions are
not as restrictive as it appears initially and some of them can be relaxed without altering
the basic nature of the model as we explain below. [Sears and Trennepohl (1993)]
Theoretical Implications of Relaxing the above-mentioned assumptions:
2. Inclusion of skewness (third moment) in the pricing model has led to the three
moment CAPM.
4. a. Different borrowing and lending rates lead to different CAPM lines and no
general equilibrium pricing model.
b. No riskless asset exists, leading to the zero beta CAPM, which provides for a
theoretical explanation of the basic CAPM empirical results.
c. There is riskless lending but no riskless borrowing, leading to the zero beta CAPM
5. CAPM would be series of line segments, each representing portfolio positions with
no fractional shares.
6. Different expectations lead to different CAPM lines and no general equilibrium
pricing model.
7. a. Inclusion of transactions costs in the model would produce bands around the
relationship, leading to fuzzy equilibrium.
b. Consideration of taxes leads to an alternative CAPM model that incorporates
the differential tax effects of dividends and capital gains.
Empirical Implications of Relaxing the above-mentioned
Assumptions
2. The general conclusion of tests of this model indicate that skewness is important in
the pricing of securities. In particular, whenever the market portfolio is positively
(negatively) skewed, investors are willing to accept (require) a lower (higher) average
return in exchange for positive skewness with the market portfolio.
4. a. Assumption cannot be tested empirically, band c. some empirical studies
support the zero beta CAPM, but others do not.
5. Assumption has not been tested but is probably not a major empirical problem for
CAPM.
Capital Asset Pricing Model: The Indian Context
6. This is a major empirical problem for the CAPM.
7. a. Because of relatively low transactions costs, this does not seem to be a major
problem.
b. Most studies have shown that tax effects via the dividend yield is important in
the pricing process. In particular, there is a positive relationship between
dividend yields and average returns.
One of the important outcome of the CAPM assumptions is that all investors hold a
portfolio which is a combination between riskless portfolio and market portfolio. This is
because all investors will have identical efficient frontiers due to the assumption of
homogeneous expectations. They can however have different utility functions, which
will decide what combination of riskless portfolio and market portfolio the investor will
choose. This implies that all investors hold the same combination of risky securities
namely, the market portfolio. This is also known as the separation theorem. The market
portfolio in CAPM is the unanimously desirable risky portfolio which contains all risky
assets. Thus return on market portfolio is weighted average of return of all risky assets in
the market and in theory it should contain, besides ordinary shares, all assets, like art
objects, commodities, real estates and so on.
However in practice it is impossible to construct a market proxy which contains all
assets and thus, all the commonly used market indices roughly replicate the market.
The total risk of a portfolio can be measured by the variance of its return. In a more
general situation of a portfolio p consists of n shares and any individual share i has a
weightage of Xi in the portfolio, then the total risk can be expressed as follows:
2p = n t=1 Xi2 + (n t=i Xi i)2 2m
2
2
i-e  p =  ep
+ p2 2m
Total Risk = Unsystematic Risk + Systematic Risk
If CAPM holds, then investors should hold diversified portfolios and the systematic
risk or non-diversifiable risk will be the only risk which will be of importance to the
investors. The other part of the risk, known as the diversifiable risk or unsystematic risk,
will be reduced to nil by holding a diversified portfolio. Thus beta, which is a measure of
the non-diversifiable risk in a portfolio, is most important for investors, from the point of
view CAPM theory. In case the CAPM holds in the market, an investor will no longer
require any sophisticated portfolio selection technique to select his portfolio. He will
choose a mix between risk-free rate and the market portfolio based on his utility
function.
In other words optimal investment decision will be simply to buy the market
portfolio. This investment decision is independent from the decision about how to
finance the investment i.e. whether to lend or borrow at the risk-free rate. Ideally, if
CAPM holds, there will not be any identifiable inefficiency in the market and all
securities will lie on the
Research Papers in Applied Finance
security market line (no security can be found which is wrongly priced).
However, such a situation is not realistic even in a highly developed and efficient
capital market as in the United States. But on an average, if the inefficiencies in the
market are not extreme, the assumptions of the CAPM can be approximately valid even
in a realistic situation. In such a situation majority of the securities (assets) in the market
will be efficiently priced. Thus even though it is known that no market in the world is
efficient in a perfect sense, empirical tests of CAPM can still give meaningful results.
In testing CAPM, an equation which is similar in nature to the one factor market
model of Sharpe (1964) is used. The one factor market model, which is based on much
simpler assumptions, can be compared with the CAPM. In equation form the market
model can be expressed as follows:
Rit = ttP +it
Where i =COV (Ri, Rm) /  m
The market model assumes that the joint probability distribution between R it and Rmt
is stationary and bivariate normal, where Rmt is a factor which describes security
returns. The CAPM as described earlier is a one period model describing expected
return. The market model can be expressed as (given expected market return):
2
E (Rit) = i + iE(Rmt)
If CAPM holds then i =Rf (1-i)
Putting this value of i in the original market
model one can get the following equation:
Rit = Rft + i(Rmt - Rft) + it
This is the ex-post version of CAPM. If Rft and Rmt are correlated over time then
estimates of i and i will be biased in opposite directions. However, even if Rft and
Rmt are correlated, the standard deviation of Rft is close to zero. Therefore the
covariance between Rmt and Rft is practically nil and market model beta and CAPM
beta are close in magnitude (Alexander & Francis, 1986).
Survey of Literature
Tests of CAPM
In the following some direct tests of CAPM, which were conducted in different
periods have been listed. Among the tests listed the two most important and widely
followed test are that by Black, Jensen, Scholes (1972) and Fama-MacBeth (1973). all
the tests are listed in chronological order.
Fischer Black, Michael C. Jensen and Myron Scholes (1972) studied the following
equation using 60 months data from NYSE:
Capital Asset Pricing Model: The Indian Context
rit - rn = i + i (rmt rn) + it
Between 1926-64 thirty five overlapping five year period was used to estimate the
constant term and beta in the above equation. The estimates of beta were used to rank the
stocks into 10 portfolios. For each 5 year period subsequent 12 months were used to
calculate the rates of return for the portfolios, thus obtaining a set of monthly rates of
return for the period 1931 to 1965 for each of the 10 portfolio. Time series OLS estimate
of and was obtained for 420 months data and 4 sub-periods data. Except for the first subperiod the and are found to be inversely related. Cross sectional test of CAPM was done
using the following equation:
ri - rf = to + ti i + i, for i=1…10.
This was estimated for the entire 35 years period as well 4 sub-periods. The estimate of
intercept term was significantly different from 0 and estimate of slope significantly less
than average excess return on market portfolio for all the sub-periods as well as for the
35 year period. Thus the intercept term is too large and slope too small for CAPM. The
authors argued that this could happen if zero beta CAPM is valid. Then the following
equation should hold:
rit - rzt = i + i (rmt rzt) + it
Where rz is the return on zero beta portfolio and expected value of i is zero. The
results are consistent with this version of the CAPM. However, the authors do not
perform a separate test to examine this.
The most important empirical investigation of CAPM was done by Eugene F. Fama
and James D. MacBeth (1973). In this study they divided the sample stocks in to 20
portfolios on the basis of estimated beta rankings. The data used for this study are
monthly percentage returns including dividend and capital gain for all stocks in the
NYSE for the period between January '26 to June '68. They used three separate periods
for portfolio formation, beta estimation and final testing. Beta estimated from the data in
each period of portfolio formation were used to rank the shares and form 20 equal sized
portfolios. The following 5 years data were used to recompute beta, and these were
averaged across securities within portfolios to obtain 20 portfolio betas for the risk-return
tests. These portfolio betas were computed month by month in order to account for any
delisting of securities. Measure of non-beta risk was obtained as the standard deviation of
the residual risk in the market model for each securities. For each month in the test period
they regressed portfolio return with the portfolio beta, portfolio beta square and portfolio
residual error each estimated from the previous estimation period. The following
equation was used:
Rpt = ot + it pt-1 + 2t 2pt-l +
3t S (ept-l) + pt for p = 1………20
Research Papers in Applied Finance
Fama and Macbeth (1973) had estimated the above full equation as well as forms of
equation where values of the coefficients of both beta square and residual error are both
separately and simultaneously forced to zero. If both theory and empirical evidence
indicate that one or more variable has no influence, better estimates can be made when
those variables are excluded. The results indicate that neither the beta squared term nor
the residual risk has any influence on stock returns. The performance of beta coefficient
over the entire period indicates the relationship between expected return and beta is
linear and positive. Fama and Macbeth finds that the intercept term is generally
substantially greater than riskfree rate of return and beta coefficient is substantially less
than premium on market portfolio. This indicates that zero beta model is more consistent
with equilibrium condition than the simple CAPM.
Criticism
Richard Roll (1977) in his paper asserted that the asset pricing theory is not testable
unless the exact composition of the true market portfolio is known. Using a market proxy
is subject to two problems, firstly the proxy may be mean variance efficient even when
true market portfolio is not mean variance efficient and secondly proxy may be
inefficient when market can be either efficient or truly inefficient. The exact composition
of the market portfolio is practically not possible to determine. Thus according to the
author it is not possible to test CAPM empirically.
Literature on Anomalies in CAPM
Jack Clark Francis and Frank 1. Fabozzi (1979) conducted a study over a
period of 73 months between December 1965 and December 1971 on 694 stocks listed in
NYSE. The study looked into the stability of the single index market model (SIMM).
The result of the study supports the hypothesis that SIMM is affected by macroeconomic
conditions. The intertemporal instability in the betas frequently observed could be due to
this business cycle economics.
Elroy Dimson (1979) proposed that the intervaling effect (tendency of explanatory
power of market model regression equation and mean value of beta estimated from value
weighted index to rise as differencing interval is increased) found to exist in the testing
of market models is indicative of a possible non-trading problem. The author suggests a
method to estimate beta when the data suffers from this problem. The method, called
aggregated coefficient method (AC) were applied on listed stocks of London Stock
Exchange between January 1955 and December 1974. The author argued that under nontrading problem it is not possible to determine the most efficient method of estimating
betas and thereforeAC method is attractive when transaction times are not known. Robert
H. Litzenberger and Krishna Ramaswamy (1979) derived an after tax version of CAPM.
Share price data from January '36 to December '77 was used in the study (504 periods).
The results of the study indicate that there is a strong positive relationship between
before-tax expected returns and dividend yields of common stocks.
Richard Roll (1981) found the trading infrequency to be an important cause of bias in
short interval data. As the small firms are traded less frequently the risk measures for
these
Capital Asset Pricing Model: The Indian Context
firms are downward biased. The bias is very large in daily data and is also present in
returns from monthly data. According to the author this bias can possibly explain effects
like the small firm effect, low P/E ratio effect and high dividend yield firm effects,
present in the market. Jeffrey F. Jaffe, Randolph Westerfield, M. A Christopher (1989)
studied two sets of indices from the US and one set each from Canada, Australia,
England and Japan. The authors find that Monday return for common stocks is negative
only when market has declined in the previous week. The findings are inconsistent with
market efficiency. The inconsistency cannot be explained by serial correlation arising
from infrequent trading or higher risk on those particular Mondays.
Hee-Kyung K. bark (1991) in his study used the Fama-MacBeth methodology to test
the CAPM in the Korean market. The data was collected from the Daewoo- Yonsei
database on monthly stock returns between the period January 1980 to December 1987.
The period was subdivided into five overlapping periods of 4 years. The study tests the
positive risk return trade off of CAPM. For the entire period there was a negative sign in
the market premium. The residual risk was also found to be a significant factor. Thus the
results indicate CAPM cannot be a predictive model in the Korean market. Eugene F.
Fama and Kenneth R. French (1992) tested CAPM using stock return data between 196390 from NYSE, AMEXA and NASDAQ. The results do not support the Sharpe-LintnerBlack CAPM model's positive relation between average stock return and beta. The
results indicate that size and book-to-market equity capture cross sectional variation in
average stock returns associated with size, E/P, book-to-market equity and leverage. The
authors concluded that if asset pricing is rational than size and book-to-market equity
must be a proxy for risk. However, if asset pricing is irrational then these two variables
may not be proxy for risk and the persistence of these results are doubtful.
As indicated in the literature survey, most of the empirical tests of CAPM have been
conducted on NYSE and based on the basic methodology adopted by B lack, Jensen,
Scholes (1972) and Fama-MacBeth (1973). Besides testing for CAPM, many of the
studies have concentrated on anomalies in the CAPM model, namely, size effect,
seasonal effect, tax effect, dividend effect and problems due to misspecification in the
CAPM model. In spite of the criticism of Roll (1977) on the validity of tests of CAPM, it
is clear that the studies on CAPM have provided valuable insights to the stock returns
behavior in various capital markets across the world. If systematic risk and return are
linearly related and residual risk is unrelated to return, it will have important implication
for investors. The tests of CAPM, though not entirely satisfactory and suffers from the
market index identification problem, often produces results that can be expected from
tests of CAPM. While one should continue the search for true tests of CAPM, one can
perhaps proceed on the basis of the results produced by tests of observable, but not
optimum, phenomena.
Tests in the Indian Context
N. Krishna Rao (1971) tested the Random Walk hypothesis on Indian Aluminium
weekly average share price data for a period of 16 years (1955-70) collected from the
Calcutta Stock Exchange. Spectral analysis of the data indicated that Random Walk
hypothesis holds for Indian Aluminium.
Research Papers in Applied Finance
J.L. Sharma and Robert. E. Kennedy (1977) tested the applicability of Random Walk
hypothesis in India, London and US. Data for last Friday in every month was collected
for a period of 132 months. Spectral density estimated fot first difference series for each
index confirmed randomness of the series. No systematic cyclical component was found
in the indexes. S.K. Barua (1981) in his paper examined the efficiency in the Indian
capital market using Runs test and Serial Correlation test with lags up to period 8 on 20
securities and the market index. Daily data over the period of July 1977 to June 1979 was
collected. In summary the preliminary evidence suggests towards market efficiency in the
Indian capital market. L. C. Gupta (1981) studied share price data between the period of
1960-76. Each year's high and low price for the sample shares were considered. A total of
606 equity shares for one or more holding periods were considered in the study. The data
was collected from Bombay, Calcutta and Madras stock exchange. The long-term rates
on equities were less than that on debentures, preference shares, company deposits and
long-term bank deposits most of the time. The belief that equities provided hedge against
inflation was found to be unfounded. The author doubted the applicability of CAPM in
the Indian capital market.
J.L. Sharma (1983) tested the market efficiency in the Indian capital market. The data
consisted of 23 stocks listed in the Bombay Stock Exchange between the period 1973-78.
Thus the results indicate that Random Walk hypothesis holds for the Bombay Stock
Exchange. Y.B. Yalwar (1985) took a sample of 122 actively traded shares between the
period 1963-82. He calculated rates of return for each sample stock using geometric
mean monthly return method for holding periods of 1 year, 5 year, 10 year and 15 year.
The study showed that the equity returns are high and consistent with the market risk
premium. Beta estimates for all securities were positive and significant except for two
samples. Second pass regression was tested on mean return. The results indicated CAPM
is a good descriptor of the Indian capital market. The BSE is efficient at least in the weak
form as far as pricing of actively traded shares are concerned. S:K. Barua and V.
Raghunathan (1986) studied the efficiency in the Indian Capital Market with a special
reference to Reliance issue of convertible debenture. They showed that an investor
operating in the forward market can earn abnormal return compared to an investor
operating in the cash market.
S.K. Barua and V. Raghunathan (1987) tested the market efficiency in India based on
actual returns. The results indicate that the Indian capital market in inefficient in pricing
its securities. N.P. Srinivasan and M.S. Narasimhan (1988) in their note criticise the
papers ofBarua and Raghunathan (1986 & 1987) since it considered only ex-post return.
Ex-post violation of risk-return parity need not suggest market inefficiency. V.K. Vasal
(1988) in his study looked into the effect of corporate financial decisions and share price
behavior in the Indian capital market. The sample data for the study was taken from
Indian Cotton Textile Industry. The test period was three cross sectional periods 1979,80
and 81. The empirical results indicate that the Indian capital market is reasonably
efficient in valuing a firm.
N. Krishna Rao (1988) tested the efficiency level in the Indian capital market. The
sample consists of week-end prices of 10 blue chip companies in the Bombay Stock
Exchange adjusted for bonus and rights issue. The period is July 1982 to June 1987. The
Capital Asset Pricing Model: The Indian Context
result of the above studies supports the hypothesis that Indian capital market is at least
weakly efficient.
Uma Shashikant (1988) conducted the study on a sample of 100 companies, selected
from actively traded shares in 1964. The study period was 1965-87. contrary to the
findings of L.c. Gupta the rate of return was found to be increasing withholding period.
Except for war years of 1965 and 1971 other returns were positive, confirming sub
Martingale model of share price.
A study on asset pricing in Indian markets has been conducted by J.R. Verma (1988).
The study does not reject the CAPM. However, as the author notes, replication on larger
samples of securities is desirable to provide conclusive evidence in favor of the theory.
G. C. Maheshwari and K.R. Vanjara (1989) conducted the study on a sample of 142
securities. The scrips were selected on the basis of their performance and assets during
the year 1986. The study spanned from January 1, 1980 to December 31, 1986. The study
indicates that the Indian capital market is probably not very efficient. LM. Pande and
Ramesh Bhat (1989) mailed questionnaires to 600 prepares and users of accounting
information to study their perception about the Indian capital market. The result of the
study indicates that the Indian capital market is perceived to be inefficient.
S.K. Barna and V. Raghunathan (1990) in their paper studied 23 leading company
stock prices. They calculated PIE ratio based on fundamental analysis and compared
them with actual PIE data. The results indicated on an average shares are over valued in
the Bombay Stock Exchange. Obaidullah (1991) tested for the normality of stock market
returns in India. He used sensex data from April 1979 to August 1991 and Natex data
from April 1984 to November 1991. He found that daily returns differed significantly
from normality whereas monthly sensex returns differed significantly from normality
whereas monthly sensex returns were not significantly different from a normal
distribution. The monthly returns were positively skewed and leptokurtic but not
statisticaIly significant. Further the deviations were lesser where logarithmic price
changes were used as against the percentage price changes. A study by Obaidullah (1991
a) reported that the stock price adjustment to release of value-relevant information is
inaccurate. This implies that at any given point in time there are undervalued and
overvalued stocks in the market. Prices are not equal to their fundamental intrinsic
values. Hence, a risk-return parity cannot be expected to hold good. Another study by
Obaidullah (1991 b) attributes abnormal returns to price-earnings ratios. The abnormal
returns are also observed to persist. The so-called CAPM equilibrium is never reached.
R.N. Agarwal (1991) looked into dividends and stock prices in the commercial
vehicle sector in India. He covered the period between 1966-67 to 1986-87. The
regression result suggests that current dividend behavior is explained by the current level
of net profits and the two past dividends. The adaptive expectation hypothesis (past share
prices are expected to be adapted) are supported by the result. Satinder Palaha (1991)
conducted the study on a sample of 419 stocks divided into 11 industry groupings.
Individual security betas of forty stocks as well as portfolio beta were estimated for the
entire period of 1976-85 as well as its 5-year sub-periods. OLS was used in the
estimation procedure.
236
Research Papers in Applied Finance
Over two sub periods the betas showed a high degree of stability. However, the
individual security betas showed high instability. Out of 40 individual securities only in 5
cases the model had some degree of relevance.
Vaidyanathan & Ray (1992) found that for companies belonging to chemical
industries, market risk is less than 40%, as a percent of total risk. In the case of other
types of industries market risk was less than 50% of total risk. When individual investors
hold small number of stocks and in the context of large proportion of firm specific risks,
efficient portfolios do not get formed. Vaidyanathan & Gali (1993) found a settlement
period effect in the Bombay Stock Exchange scrips during 1989 and 1990. The average
return on the first trading day of the settlement period is usually higher than that on the
last trading day and the intermediate days. In fact it is higher than the overall daily
average returns. Ray (1994) conducted a test of CAPM using 170 actively traded scrips
on the Bombay Stock Exchange. He used monthly data over the period 1980-91. He used
three market indices, the RBI index, ET index and the BSE Sensitive Index. He used the
Fama-MacBeth methodology and found that CAPM does not seem to hold for the Indian
capital market.
A study conducted by Obaidullah (1994) used monthly stock price data for a period
of sixteen years (1976-91) for a sample of thirty stocks. The results from the exercise,
however, do not lend themselves to any supportive or contradictory interpretation. The
coefficients of 2p are, in general, not statistically significant. This is in conformity with
the CAPM. However, in the multiple regression model, the coefficients of p also in
most cases become statistically insignificant which is contrary to what the CAPM
predicts. Hence he suggests that CAPM as a description of asset pricing in Indian
markets does not seem to rest on solid grounds. Vaidyanathan & Gali (1994 a) studied
the variation in various indices (Sensex, ET index and Natex) and found that one scrip
(Reliance) explained more than half of the variation in the indices during 1989 and 1990.
In case Hindustan Lever is also considered then the two scrips explain around 70% of the
variation in Sensex and Natex. Vaidyanathan & Gali (1994 b) studied the efficiency of
the stock market (weak form) using runs, serial correlation and filter tests at four
different points for the period 1980 to 1990 for ten scrips. The evidence from all the three
tests support the weak form of efficiency.
Sehgal (1994) used data of the Natex and 80 individual securities over the period
April 1984 to March 1993 and used logarithmic price changes. Testing for the
significance of skewness and kurtosis we found that for Natex skewness is not significant
but kurtosis is significant. For individual securities a vast majority had significantly
positive kurtosis. Further, each of the randomly formed portfolios of eight securities were
also found to significantly deviate from normality. However, the sample period includes
the security scam period of February, 1992 to May, 1992 during which period there were
extreme variations in the indices and stock prices. The effect of these could affect the
outcome of the test. Gali (1995) has tested for the normality of the returns of Sensex, ET
index and Natex during May, 1987 to June, 1994. He constructed daily, weekly,
settlement periodwise and monthly returns. Monthly and settlement period-wise returns
were normal for all the indices.
~
Capital Asset Pricing Model: The Indian Context
Imperfections in the Indian Capital Market
The results from some of these studies indicate that the Capital Asset Pricing Model
probably cannot explain the risk-return relations in the Indian capital market. There
could be several reasons for the empirical data not supporting the model. As pointed out
in the literature survey, one of the shortcomings of any ex-post test of CAPM is the
difficulty in defining the market portfolio. The assumptions of CAPM imply that the
market portfolio reflects the universally preferred combination of risky assets. The
market portfolio in CAPM should ideally include all assets. Naturally, for testing
purposes only a reasonable proxy for the market portfolio has to be used. Thus, if the
market proxy is not properly defined tests of CAPM may give misleading results.
However many studies have used different indices, namely, RBI Index, Economic Times
Index and the BSE Sensitive Index, as market proxy. Thus, the possibility that the results
are distorted due to problems in the construction of the market index appears to be quite
low and other more probable causes need to be explored.
As indicated earlier, the results of a Korean study, Bark (1991), do not support
CAPM. For the entire period (1980-87) of the study, there was a negative sign in the beta
coefficient and the residual risk was found to be statistically significant. The South
Korean market in many ways is similar to the Indian market. Unlike stock markets in the
developed countries the markets in both South Korea and India are relatively new and
growing. As the author of the paper noted, the Korean market suffers from inefficiency
due to information barrier and inadequacies in the infrastructure. The influence of large
shareholders, who trade on monopolistic information, also impair the efficiency of the
Korean market. The Korean investors also hold non-diversified portfolio, which
contradicts one of the assumptions of CAPM.
The Fama & French (1992) study was conducted on return data between 1963-90.
The results of this study do not support the positive risk-return hypothesis of CAPM.
The authors find that the size and book to market value of equity explain the crosssectional variation in average returns during the period. However, the authors are not
sure whether asset pricing is rational and whether the two factors, size and book to
market of equity, can be regarded as a proxy of risk.
Thus, it can be seen that there have been less empirical support to CAPM in the very
recent studies abroad and the ability of beta to reflect the risk of a security is doubtful. In
this background the results of various studies in India do not come as a major surprise.
Moreover the efficient market assumptions behind CAPM is likely to be less valid in
India compared to the developed country markets, where the securities trading is much
more efficient in terms of greater transparency in transactions, faster and easier
availability of information related to the market, shorter settlement periods, less
transaction cost, greater liquidity and depth of the market, etc. Some of the more
important factors which may cause CAPM to be ineffective in the Indian context and has
the potential to reduce the efficiency level of the Indian Capital Market are described in
the following page.
Research Papers in Applied Finance
1. Non-Diversified Portfolio Holding
Like the Korean investors mentioned in the study of Hee-Kyong Bark (1991), the Indian
individual investors also hold undiversified portfolio. The median size of share portfolios
for Indian households is only 4.7 (L.C. Gupta, 1991). The percentage distribution of
share portfolios as found by L.C. Gupta from a survey is reproduced below.
Table 1: Portfolio Holding Pattern among Investors
No. of
Companies
1
2
3
4-5
6-10
11-20
20
Distribution of Share Portfolio
% Distribution
13.1
11.9
9.9
17.4
18.1
13.9
15.7
Cumulative %
13.1
25.0
34.9
52.3
70.4
84.3
100.0
Source: Indian Share Owners -A Survey, L.c. Gupta, 1991, Page 55.
Table 1 clearly indicates that the average investor in India holds very few scrips in
their portfolio. This goes directly against the expectations of CAPM where the investors
are expected to hold a combination of risk-free asset (or zero beta asset) and market
portfolio. The investors are not expected to hold an undiversified portfolio as they are
not rewarded for bearing unsystematic risk according to CAPM. It is also to be noted that
as the study by Vaidyanathan and Ray (1992) indicates, unsystematic risk constitutes
more than 60 percent of total risk for many companies. Hence, holding small number of
securities or undiversified portfolios can add to market inefficiency.
2. Liquidity
Liquidity is possibly the most serious problem faced by the Indian investors. A
consultative paper by SEBI indicated a poor liquidity situation at the stock exchanges in
India. Based on 1984-85 data this paper indicated that only 6% of shares are traded daily
on all the stock exchanges, 12% are traded one in a fortnight, 28% are traded once in a
month and another 28% are traded once in a year. A more recent data on the frequency of
trading at BSE is provided in Table 2. From the table one can see that at Bombay Stock
Exchange only 20% of the shares were traded frequently. More than 50% of the shares
were traded on less than 10% occasions. Overall, the liquidity position in the exchange is
highly unsatisfactory.
Capital Asset Pricing Model: The Indian Context
Table 2: Frequency Distribution of Trading at BSE (April, '88-March, '89)
% of Trading Days
No. of Companies
% of Total
20.0
> 90%
456
6.7
80-90%
152
4.1
70-80%
94
2.5
60-70%
57
3.2
50-60%
72
2.9
40-50%
66
2.2
30-40%
51
3.5
20-30%
79
4.1
10-20%
93
50.8
Up to 10%
1155
Source: Stock Exchange Trading in India, L C. Gupta, 1992, Page 56.
The trading in the exchanges in India is highly concentrated on a few scrips. The
trading velocity (total trading volume in the year divided by market capitalization) is a
good indicator of the level of activity in a scrip. Table 3 gives a comparison of share
trading velocity at various exchanges.
Table 3: Share Trading Velocity in Major Stock Exchanges
Japan
USA
UK
Germany
France
Netherlands
BSE
Top 5 Cos
Top 25 Cos
Top 50 Cos
Other Cos
All Shares at BSE
0.64
0.57
0.39
1.72
0.29
0.57
1.81
1.45
1.04
0.19
0.57
Source: Stock Exchange Trading in India, L. C. Gupta, 1992, Pages 8 and 9.
As can be seen the trading velocity at BSE, if the top 50 shares (by trading volume) are
excluded, is far below the figures of the developed countries.
As the above discussion suggests, the stock markets in India are lacking in both
breadth and depth. Much of the trading in the exchanges are concentrated in a few scrips.
Most of the scrips outside the specified list suffer from infrequent trading problem.
Large institutional holdings (almost 40%) have further contributed to the problem. The
absence of a large and well spread out investor base has reduced the amount of floating
stocks available in the market, and thus seriously impaired the liquidity.
Lack of liquidity can violate the assumptions of CAPM in two ways. Firstly it results
in a transaction cost for the investors. If the transaction cost is added to the CAPM
model, there will be a price band around the SML in which the scrips can lie. Within this
band, it will not be profitable for investors to buy or sell shares. Secondly, CAPM
assumes that all assets are infinitely divisible and readily marketable. This assumption is
Research Papers in Applied Finance
also violated in India, due to the low liquidity observed in majority of the shares, as
discussed earlier. Low liquidity can also result in inefficient pricing of scrips and price
setting behavior by investors (non-price taker).
3. Insider Trading
Insider trading is believed to be rampant in the Indian market. The lack of
transparency in the trading system facilitates insider trading. Earlier there was virtually
no law against insider trading. After SEBI was formed, it has taken several steps to
protect the small investors and prevent insider trading. In specific cases it can carry out
investigations on alleged insider trading. Greater transparency in transactions will make
insider trading more difficult to hide. However, the task of detecting insider trading is a
difficult one. Even in developed countries, where there are elaborate systems to prevent
insider trading in existence, insider trading allegedly takes place. The best way to reduce
the possibility of insider trading is to reduce the scope of making profit through it. This
can be achieved by ensuring speedy availability of price sensitive information to the
public.
Insider trading in a way can improve the efficiency in the market, as it can correct
prices of scrips for information, which is not even publicly available. However, in a
market dominated by insider trading, the investors cannot have homogeneous
expectations as assumed in CAPM. Moreover, the very presence of insider trading
implies that market
price do not reflect all information (otherwise insider trading will not be profitable), i.e.
market is not perfectly efficient.
4. Lack of Transparency
Indian stock markets suffer from lack of transparency between members and
constituents. Members perceive that the prices of transactions are not properly reflected
in their gains. All intra-day quotations are not readily available. Since exact time of the
transaction is not known, disputes persist. Also it is felt that some transactions are not
reported. In such a context any analysis has to consider the limitations of available price
series.
5. Inadequate
Infrastructure
The infrastructure in the stock markets in India are woefully inadequate. The stock
exchanges are faced with inadequate office space, lack of computerization and
communication system, etc. These inadequacies in turn has affected the quality of the
investor service provided by the members of the exchanges. Though the number of
investors as well as the volume of transaction has gone up many fold in recent years, the
basic infrastructure and system has almost remained unchanged.
Besides problems of office space and inadequate technology the present number of
brokers in the exchanges are also not sufficient to provide proper (L.C. Gupta, 1992)
services to the vast investor population. Moreover as the number of brokers are small,
they almost have an assured volume of business. As the brokers now do not have to
compete with each other much to get business there is no incentive for them to improve
the quality of the investor service. The cost of the service provided by them also tend to
be high. The monopoly of the brokers increases the transaction cost of investors.
Capital Asset Pricing Model: The Indian Context
The settlement system in India is antiquated, requiring large volumes of paperwork,
which results in inordinate delays. The settlement period of 14 days is also very long
compared to settlement periods in exchanges in developed countries.
The lack of infrastructure adds to the transaction cost of the investors. Moreover
inadequate infrastructure and delays in settlement can slow down the absorption of price
sensitive information in the market, affecting its overall efficiency. Both increased
transaction cost and low operational efficiency violates the assumptions of CAPM.
Conclusion
In order to carry out a through analysis of the capital market we need to strengthen
the database. Unlike the U.S. context where data is available dating back to 1920s, we do
not have historical data on tapes. We also do not have data adjusted for bonus/rights, etc.
over a long period. This is one area where analysts, market participants and regulators
should give more attention.
A weak database, combined with lack of sense of history can only add to market
inefficiency. To facilitate the making of a twenty-first century market, we need to
strengthen the infrastructure, improve liquidity, minimize insider trading and enhance
transparency. Till then asset pricing will continue to be inefficient and provide
opportunities for extra gains to the initiated - those initiated into the intricacies of the
imperfections of the Indian market!
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