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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

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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).

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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.

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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.