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1 | P a g e
I Introduction
The risk-return profile of asset valuation is central in driving the investment decisions of investors
coupled with the firm understanding of the rate of return and the risk correlation and propensity. So
many measures have been employed to access the riskiness of securities. This is after Sharpe-Lintner-
Mossin had proposed the standard form of the Capital Asset Pricing Model (CAPM), many empirical
evidences have been established in line with the applicability of the standard model both in advanced
economics and emerging markets before the study of the model in the Saudi Arabia Bourse.
Therefore, the researcher attempted to test the validity of capital asset pricing model in the Saudi
Arabia Bourse.
a. Study Objectives and Motivation
Specify a model that may predict the stock return in in Saudi Arabia Stock Exchange (Taduwal) by
applying
i) To generate returns on each stock and the market portfolio (the market index).
ii) Plot the relationship between return on each individual stock and return on the market index.
iii) To find out the relationship between the respective stock returns and the market index.
iv) Draw conclusion from the results and make policy recommendations based on the empirical
validity of the CAPM model on Saudi Arabia Bourse.
Saudi Arabia Exchange Market is an emerging market. It is a modern market in Saudi Arabia which
has special features compared to other exchanges Market around the world due to the Islamic Sharia
which does not allow debt and interest .This makes it very difficult to apply known models for an
emerging market like Saudi Arabia Bourse. In addition there are no taxes in Saudi Arabia because it a
rich country, However, there is an Islamic Shara’a Zakat (2.5% tax) on assets but not profit.
b. Methodology
Black et al. (1972) analysed the relationship between risk and return and verified whether
therelationship is linear. They found that systematic risk or beta is an important determinant ofsecurity
return.
Calculation of Percentage Returns, Beta, Alpha and Total Risk
The daily returns are calculated using the following models:
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1
1
t
tti
P
PPR
1;0; imii uRR
Ri= Return on stocki during time period t;
Rmi= Return on market index during time periodt;
Pt = Adjusted closing price of security i for time t;
Pt-1 = Adjusted closing price of securityi for time t-1;
The following market model is used to represent expected returns on an individual stock. The
realizedreturns are used as the measure in place of expected returns. The risk measures like beta,alpha
are calculated using this model.
β= (Estimated Beta of stock asset i) the security's or portfolio's price volatility relative to the
overall market
α = Alpha (Regression Intercept) also known as "excess return" or "abnormal rate of return,"
measures the risk adjusted performance how bad or good the 10-stocks are performing in an index
c) Scope of Study
Collect monthly data on prices of 10 stocks listed on Saudi Stock Exchange and the marketportfolio
for the period 2006m1-2016m10. Using regression analysis, test the capital asset pricing model for 10
companies and explain whether your results are consistent with the model.
There are n number of companies listed on the TASI. The daily closing share prices of the sample
companies and Tadawul AllShare Index (TASI) data were collected and used in this study. The share
price and index price serieshave been used to construct daily return series which will be then
transformed into monthly periods.
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Table 1
d) Limitation
In this test of the CAPM, we didn’t use other variables than the market return and the risk-free rate of
return in order to have the risk premium for the analysis of the securities’ excess returns. Further
researches, especially the research of Fama and French - FF (1992), used other variables, like the
market value (MVE) of securities. Of course, FF’s tests lead to the examination of multifactor models
(the APT). We can understand that there were enough drawbacks during our data analysis. Sincerely,
a test on the Tadawul using the APT model, would give more complete results, as it could include
different variables like the inflation rate and the market value of securities. Thus, further researches
and more tests on the APT should be applied, in order for the researchers - and the managers of firms
- to have more accurate results and understand the risk-return trade-off of the Saudi equities market.
e) Significance of the Issue
The importance of this research is to investigate the applicability of Fama and French (1993) three
stockmarket factor model (size, book-to-market and market return) to Saudi Arabia; It is the first
study that uses the sameapproach of Fama and French in measuring the dependent and independent
variables. It will add evidence as towhich of these risk factors affect the stock return.
s/n Company Stock Sector TASI Code Custom Identifier (Code)
1 Alujain Corporation SJSC Petrochemical Industries (TADAWUL:2170) R_ALU
2 Banque Saudi Fransi Banks & Financial Services (TADAWUL:1080) R_BS
3 Makkah Construction & Development Co Real estate and property development (TADAWUL:4100) R_MAK
4 National Gypsum Company Building & Construction (TADAWUL:2090) R_NGC
5 Qassim Cement Company Cement (TADAWUL:3040) R_QCC
6 Saudi Chemical Company Industrial Investment (TADAWUL:2230) R_SCC
7 Saudi Public Transport Company Price Transport (TADAWUL:4040) R_SPT
8 Saudi Telecom Company Telecommunication & Information Technology (TADAWUL:7010) R_SAT
9 Tabuk Agriculture Development Company Agriculture & Food Industries (TADAWUL:6040) R_TAB
10 Tourism Enterprise Company (Shams) Hotel & Tourism (TADAWUL:4170) R_SH
Selected Company Stocks
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II Review of Literature
The portfolio theory developed by Markowitz (1952, 1959) provided the basis for CAPM.
Hesuggested that rational investor to optimize risk and return should choose portfolio rather
thanindividual stock. Therefore, rational investor uses diversification of portfolio to optimize riskand
return. According to Sharpe (1964), “in equilibrium there would be a simple linearrelationship
between the expected returns and standard deviation of returns for efficientcombination of risky
assets. In effect, market presents two types of prices: the price of time orthe pure interest rate and the
price of risk, the additional expected returns per unit of risk.Diversification enables the investor to
escape from all except the risk that results from theswings in economic activity- this type of risk
persists even in efficient combinations”. Blacket al. (1972) used regression equation to estimate alpha
(α) and beta (β) for the monthly shareprice data of NYSE from 1926 to 1964. The estimated beta was
used to divide stocks into 10portfolios. The parameters for each 5-year period were calculated and
used to test the realizedreturns for subsequent 12 months. Time series method was used to estimate α
and β for 420months data and 4 sub-periods data. They found that α and β are inversely related for
allsub-periods except for the first sub-period.Fama and French (1992) tested CAPM using stock
returns data between 1941and 1990 fromNYSE, AMEXA and NASDAQ. They discuss the
combination of size and book-to-marketequity to capture the cross-sectional variation in average stock
returns associated with marketbeta. They concluded that the variation in beta is not related to the size
and there is a flatrelation between market beta and average return, even though beta is the only
explanatoryvariable. The results do not support the Sharpe-Lintner-Black CAPM model’s positive
relationbetween average stock return and beta. They report that beta does not completely
explain“Cross-Sectional” variation in the average returns of stocks during the study period. Fama
andFrench observe that a firms size, book-to-market ratio (BE/ME) absorb the role of leverage andE/P
factors in stock returns.
Black (1993) rejected that “beta as the sole variable explaining returns on stock is dead”, andargues
that this is a misstatement of the results of Fama and French (1992). He argues that theresult of Fama
and French (1992) is the effect of data mining and the announcement of death ofbeta seems to be
premature. Fama and French (1993) suggest that a firm’s book-to- marketratio and size are in fact
proxies for the firm’s loading on priced risk factors. Fama and French(1996a) questioned the validity
of the results of Kothari et al. (1995) and argued against beta.They also showed that annual and
monthly betas produce the same inferences about the betapremium. They argued that beta premium is
more and cannot save the CAPM even thoughthere are evidences to support that the beta alone cannot
explain expected return.
The review of literature shows that most of the tests of CAPM have been conducted ondeveloped
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stock markets and are based on the basic methodology adopted by (Sharpe, 1964;Lintner, 1965;
Mossin, 1968; Black et al., 1972; Fama and MacBeth, 1973; Ross, 1976).Besides testing for CAPM,
many of the studies have firm size effect, P/E effect, dividend effect,and problems due to
misspecification in the CAPM model. In spite of the criticism of (Roll, 1977, 1981; Fama and French,
1992, 1996; and Davis et al., 2000) on the relevance of tests ofCAPM, it is clear that the studies on
CAPM have provided valuable insights to the stockreturns behaviour in markets. If systematic risk
and returns are linearly related and residual riskis unrelated to returns, it will have important
implication for investors.
Iqbal (2011) reviewed 36 research articles on relevance of CAPM and found that there aredifferent
views on the relevance of CAPM. Many researchers believe that CAPM is relevant tomeasure risk
and return and the argument on beta death is premature whereas there is anothergroup of researchers
who criticise CAPM and argue that the beta is dead.Singla and Pastricha (2012) in their study did not
find any positive relationship between thestocks’ systematic risk, beta (β) and their expected returns.
They found that the stocks’expected return is more closely related to their betas (β) in the negative
return periods than inthe positive return periods.
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III. Empirical Findings and Analysis
Introduction
The CAPM model in Saudi Arabia Exchange (Tadawul) are applied to using the same FF
methodology they measure the variables to check if those models can be applied in this emerging
market. Finally, we comparisons between the measured returns according to those models with real
variables and with each other were implemented.
a. Charting the Relationship between Return on Stock and Market Index
This relationship between the individual stock returns and market index can be more simply
illustrated in the graph below. The scatter plot showing the last 130-periods from January 2006 to
October 2016 for each company stocks and the market index (portfolio).
Figures 1-8: Scatterplot of Selected Stocks on Market Index
Figure 1: Alujain Stock vs Market Index Figure 2: Banque Saudi Fransi Stock vs
Market Index
Figure 3: Makkah Construction Stock vs Market Index Figure4: National Gypsum Stock vs Market
Index
-150
-125
-100
-75
-50
-25
0
25
50
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_A
LU
R_ALU=1.051-0.001656*MEX
-40
-30
-20
-10
0
10
20
30
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_B
S
R_BS=-0.1366-0.000751*MEX
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Figure 5: Makkah Construction Stock vs Market Index Figure 6: Saudi Telecom Company
Stock vs Market Index
-160
-120
-80
-40
0
40
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_M
AK
R_MAK=0.2868-0.0009128*MEX
-50
-40
-30
-20
-10
0
10
20
30
40
0 2,000 4,000 6,000 8,000 10,000 14,000
MEXR
_N
GC
R_NGC=-1.108-0.001005*MEX
-80
-60
-40
-20
0
20
40
60
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_Q
CC
R_QCC=-1.001+0.0002749*MEX
-120
-100
-80
-60
-40
-20
0
20
40
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_S
AT
R_SAT=-0.8166-0.0002296*MEX
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Figure 7: Saudi Chemical Company Stock vs Market Index Figure 8: (Shams) Stock vs Market
Index
Figure 9: Saudi Public Trans. Stock vs Market Index Figure 10: Tabuk Agriculture
Development CompanyStock vs Market Index
The red line is the best fit line showing the relationship between the market index and company
(Individual) stock returns. The slope of this line is the beta of stock return. In this case of Figure 1:
Alujain Corporation SJSC , the beta is equal to 0.0017, which means that when the market rises or
falls by 1% the stock of Alujain (ALU) tends to fall by about 0.0017%.
-120
-80
-40
0
40
80
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_S
H
R_SH=1.972-0.001425*MEX
-150
-125
-100
-75
-50
-25
0
25
50
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_S
PT
R_SPT=-0.03899-0.001131*MEX
-80
-60
-40
-20
0
20
40
60
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_T
AB
R_TAB=0.793-0.001012*MEX
-80
-60
-40
-20
0
20
40
60
0 2,000 4,000 6,000 8,000 10,000 14,000
MEX
R_S
CC
R_SCC=0.947-0.001371*MEX
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Obviously, the regression relationship between the stock return and the market index (portfolio) is far
from perfect. Many of the scatter plot points showing the actual returns for all the individual
company stocks and the market portfolio fall far from the best fit line. However, according to the
CAPM these “errors” should average out in a diversified portfolio.
b. Regression on the effect of the Market Index on the Individual Stocks: Best Fit
Examination
Beta coefficient, intercept and other key parameters are estimated using time series regression.
Contemporary monthly market portfolio for the period 2006m1-2016m10 was used. The aim of this
test is to establish the relationship between the respective stock returns and the market index.A result
for Alujain Corporation is presented in the equation below for demonstrative purposes. Results for the
remaining companies are presented in the table below.
imii urr
ri = 1.0512 – 0.0017rm +μi
t = (0.4901) (1.3745)
p = [0.6249] [0.1717]
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Table 2
There are two fundamental propositions of the CAPM (i) that asset returns are positive (and linear)
functions of beta, and (ii) that beta is the only determinant of asset/equity returns. As can be seen from
Table I, all the individual stocks have low positive/negative beta, proposition (i) is supported by our
results. In other words, investors in the Kenyan market, like investors elsewhere, expect to be
compensated more, the higher the systematic risk on their investment.
Per the evidence above, all ten companies have their beta coefficient hovering around 0 I relation to
the market portfolio. Thus these companies exhibit low variation in returns than the market portfolio
and hence, expected to be more relatively less risky. This might be due to the peculiarities of the
Saudi Arabia Bourse Market which does not allow debt and interest. In addition there are no taxes in
Saudi Arabia because it a rich country, However, there is an Islamic Sharia Zakat (2.5% tax) on assets
Company (Cross-Sections) β α R2 AIC SC(0.0017) 1.0512 0.0145 8.8652 8.9093
(1.3745) 0.4901
0.1717 0.6249
(0.0008) (0.1366) 0.0061 7.3367 7.3808
(1.3385) 0.1831
(0.1367) 0.8915
(0.0009) 0.2868 0.0067 8.4507 8.4948
(0.9321) 0.1645
0.3530 0.8696
(0.0010) (1.1080) 0.0159 7.7767 7.8208
(1.4370) (0.8902)
0.1532 0.3750
0.0003 (1.0010) 0.0013 7.6657 7.7098
0.4156 (0.8501)
0.6784 0.3968
(0.0014) 0.9470 0.0180 8.2677 8.3118
(1.5338) 0.5952
0.1276 0.5528
(0.0011) (0.0390) 0.0091 8.5775 8.6216
(1.0839) (0.0210)
0.2805 0.9833
(0.0002) (0.8166) 0.0007 7.9498 7.9939
(0.3012) (0.6017)
0.7638 0.5484
(0.0010) 0.7930 0.0078 8.5134 8.5576
(1.0011) 0.4408
0.3186 0.6601
(0.0014) 1.9722 0.0113 8.8233 8.8674
(1.2079) 0.9389
0.2293 0.3495
Saudi Public Transport Company
Saudi Telecom Company
Tabuk Agriculture Development Company
Tourism Enterprise Company (Shams)
Banque Saudi Fransi
Makkah Construction & Development Co
National Gypsum Company
Qassim Cement Company
Saudi Chemical Company
Time Series Regression Estimates for each Cross Sections
Alujain Corporation SJSC
11 | P a g e
but not profit. However, by investing in such companies investors will require lower returns due to the
low systematic risk, in contrast to (Sharpe, 1964; Lintner, 1965) postulation. The scatterplot that
shows the behaviour of the selected stocks supports the claim of low-risk and return metrics especially
for a typical investor that is risk averse. Cost of capital for these companies is also expected to be low.
The only equity that have a positive beta coefficient is the Qassim Cement Company (QCC) stock
which means that if the market portfolio were to increase by 1%, QCC stock will rise by 0.003%
implying a stock increase at a reduced rate of investment.
This evidence gathered in this study also lay claims to the explanatory power of beta and show that
systematic risk is not significant in explaining the pattern of returns generating process in the Saudi
Arabia bourse. The central theme of the CAPM says that the only risk that determines asset returns is
the systematic risk which is the risk that correlates with the market return. This is possible because
according to the CAPM, other half of risk, that is, unsystematic, is eliminated through diversification
(see for example, Markowitz, 1952, 1959; Sharpe, 1964; Lintner, 1965).
However, it is observed from the above results that there are no significant deviations from the CAPM
as shown by statistically significant intercepts. This implies that (beta) systematic risk on its own is
unable to capture all risks associated with equity returns and that risk factors that are unique to the
firm or other macroeconomic innovations may be important in determining equity returns (see for
example, Jensen et al., 1972; Ross, 1976; Fama and French, 1992).
The R2 for the individual regressions are very low, and this is buttressed by the high Akaike
Information Criterion (AIC) and Schwarz Criterion (SC), which are all well above the critical value of
7.33. The highest total variation in equity returns in the Saudi Arabia bourse for 10 selected company
stocks which can be explained by the CAPM, as measured by R2 , is only 1.8% (for Saudi Chemical
Company(SCC)), leaving more than 98 per cent of the variations in the company’s equity returns
unexplained by the model. For stocks likeSaudi Telecom Company (SAT) and Qassim Cement
Company (QCC) with respective R2 of 0.07% and 0.13%, the unexplained variations of 99.93% and
99.87% renders the appropriateness of CAPM even more suspect. This implies that there are other
risk factors other than systematic risk, including perhaps company-specific like dividend payoutand
industry/economy wide risk factors, which is essential to investor equity valuation. This is consistent
with Jensen et al (1972) Ross (1976) and Fama and French (1992).
12 | P a g e
IV Summary/Conclusion
The main focus of this study was to investigatethe risk-return relationship which serves asbasis of
estimating cost of equity capital in Saudi Arabia Bourse using CAPM. Empirical evidenceproduced in
this study supports the explanatorypower of beta. However, contribution made bybeta to variation in
equity returns in Saudi Arabia Bourse isless than the CAPM’s prediction as measuredby low R2 and
high AIC and SC. This meansthat other risk factors in addition to the marketbeta are likely in Saudi
Arabia Bourse.The literature revealed that other market indicators like size, BE/ME, P/Eand liquidity
may be contributing to the returngenerating process. Future studies in Saudi Arabia Bourse will
extend the test to include both size andBE/ME fundamentals and also factors relatingto P/E ratio and
liquidity.
This evidence will also make corporatemanagers think twice when using CAPM as abasis to
determine cost of equity capital forinvestment appraisal purposes and fundmanagers when allocating
assets andevaluating portfolio performance.
13 | P a g e
V. Recommendation
The study lend credence to the capital investmenttheory which suggests that corporate
managersshould go ahead and invest in capital projectsprovided there is a proof of
maximisingcorporate value. Subsequently, if someshareholdersdifferwithmanagementdecisions, they
can sell their shares and be welloff as if management have made differentdecisions. This underpins
the theoreticalrecommendation that managers invest only inthose projects that yield positive net
presentvalue (NPV).As academics are still busily debating thevalue of the CAPM, it puts practitioners
andcompanies who use the CAPM in their capitalinvestment process into a state of stupor.
Although capital investment decisions can bemade without the CAPM, evidence seems tosuggest that
those who choose to adopt itpresently in spite of the academic debate willactually not receive a
worthless advice. Forthose interested in the strategic view ofbusiness, the CAPM still appears to have
something to offer in the capital investmentdecision process. The capital asset pricing model provides
a method of assessing the riskiness of cash flowsarising from a project and also estimates
therelationship between that riskiness and the costof capital (or the risk premium for investing inthat
project). The CAPM asserts that theimportant measure of a project risk issystematic or common risk
known as the project’s beta. According to the CAPM, aproject cost of capital is an exact
linearfunction of the rate on risk-free project and thesystematic risk (that is, beta) of the projectbeing
evaluated.
However, test results documented in this studyappear to suggest that the risk adjusted onefactor
CAPM’s beta is not sufficient to fullyexplain the equity return generating process in Saudi Arabia
Bourse. There may be other important riskfactors that affect return due to country or firmspecific
characteristics. Thus, although beta issignificant in explaining firms returngenerating process in Saudi
Arabia Bourse one shouldinterpret this with caution. Corporate managersmust be cautious when using
CAPM as theirbasis of estimating cost of equity capital asthey may be misled into under
estimatingproject risk.
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