Bachelor of finance and banking thesis the test of CAPM in vietnam stock market

LISTS OF TABLE Table 3.1: The government 2-year bond rate and default risk Table 4.1: The number of listed stocks in the sample Table 4.2: Regression results on the CAPM by price return

MINISTRY OF EDUCATION AND TRAINING

FPT UNIVERSITY Bachelor of Finance and Banking Thesis

The Test of CAPM in Vietnam Stock Market

GROUP 8

GROUP MEMBERS

VõThịMỹLinh - FB60224TiếtKhaiNguyên - FB60019ĐỗDuyHòa- FB60041DươngHữuTrí- FB60008

TABLE OF CONTENTS LISTS OF TABLE 4

ABBREVIATION 4

ABSTRACT 6

CHAPTER 1 - INTRODUCTION 7

1 Background 7

2 Theoretical problems 9

3 Practical problems 9

4 Research questions 10

5 Research objectives 10

6 Research scope 11

7 Methodology and data overview 11

8 Thesis outline 11

CHAPTER 2: LITERATURE REVIEW 13

1 Introduction 13

1.1 Overview of reviewed sources 13

1.2 Scope and limitation 13

2 Model discussions 14

2.1 The single factor model: Sharpe and Lintner version 14

2.2 The two factors model: Fisher Black version 17

2.3 The three factors model: Fama-French 19

3 Empirical Studies 21

3.1 An Empirical Analysis of CAPM and Fama-French in China Stock Market 22

3.2 Estimation of Expected Return for Individual Stock: CAPM vs Fama-French 24

3.3 Empirical Evidence from America Stock Market 24

3.4 The Application of CAPM in China Stock Market 26

3.5 Empirical evidence from Karachi Stock Market 27

3.6 Dividend yields and Stock returns 28

3.7 Conclusion 29

4 Summary 29

CHAPTER 3 – METHODOLOGY 31

1 Introduction 31

2 Data collection methods 31

2.1 Sampling techniques 31

2.2 Secondary data 33

2.2.1 Determining the stock exchange 33

2.2.2 Dividend 33

2.2.3 Determining risk-free rate 34

2.2.4 Rate of stock return 36

2.2.5 Rate of market return 37

2.2 Sample characteristics 38

3 Data analysis methods 38

3.1 Determination of β for an individual stock 39

3.2 Examination on the relationship between the expected return and risk 40

4 Ethical considerations 41

5 Limitations of the research project 41

5.1 Access: difficulties in getting data 41

5.2 Approaches: difficulties in using models 42

5.3 Scope of the research project 43

6 Conclusion 43

CHAPTER 4 – ANALYSES FINDINGS 44

1 Introduction 44

2 Systematic presentation of data 50

3 Analysis of the model elements 59

3.1 The analysis to the β 59

3.2 The analysis to intercept 60

3.3 The analysis to R square 61

3.4 Test relationship between risk and return 62

CHAPTER 5 – CONCLUSION AND RECOMMENDATION 65

1 Conclusion 65

2 Recommendation 66

REFERENCE 67

APPENDIXE 69

LISTS OF TABLE

Table 3.1: The government 2-year bond rate and default risk

Table 4.1: The number of listed stocks in the sample

Table 4.2: Regression results on the CAPM by price return methodTable 4.3: Regression results on the CAPM by total return method

ABBREVIATION

AMEX : American Stock Exchange

APT : Arbitrage Pricing Theory

BE/ME : Book equity value/ Market equity value

BH : portfolio of big size and high book to market equity

BL : portfolio of big size and low book to market equity

BM : portfolio of big size and medium book to market equityCAPM : Capital Asset Pricing Model

CFA : Chartered Financial Analyst

CRSP : The Center for Research in Security Prices in US

CSMAR : China Stock Market and Accounting Research Database

HNX : Ha Noi Stock Exchange

HSX : Ho Chi Minh Stock Exchange

KIBOR : Karachi Interbank Offer Rate

KRX : Karachi Stock Exchange

KSE : Korea Stock Exchange

MAVA : The mean absolute value for the alphas

MSCI : Morgan Standley Capital International

NYSDAQ : The National Association of Securities Dealers Automated Quotation NYSE : The New York Stock Exchange

SH : portfolio of small size and high book to market equity

SL : portfolio of small size and low book to market equity

SM : portfolio of small size and medium book to market equity

SMB : Small minus big

SML : Security Market Line

UPCOM : Vietnam over the counter market

ABSTRACT

This study provides a traditional valuation technique in estimating the risk and expected return

of assets in the stockmarket Specifically, this paper discusses the challenges of applyingCapital Asset Pricing Model (CAPM) model techniques in Vietnam stock market, one of themajor Asia frontier markets

The sample size is picked about 150 stocks from the HSX for testing, and the sample periodsbeing from March, 2012 to March, 2014 With corresponding monthly yield data, the studyuses quantitative method such as Central Limit Theory and Point Estimator that the CAPMmodel is estimated and tested by using time-series test and cross-sectional regression

On many fronts, our findings show that there is not substantial alignment with CAPMvaluation practices in Vietnam's stock market because the Vietnam stock market is not mature,the market has been speculative and stock prices were easily controlled.Besides, the followingresearch may eliminate the limitations of this study in order to get better results

Keywords: CAPM, Vietnam stock market, valuation

to use Therefore, they tend to base on the company’s published information orrecommendations of security organizations when they consider and look for investing in anindustry or a stock For the above reasons, it is really necessary for Vietnam market to apply amodel that can determine expected return and risk of a stock and provide a helpful andefficient method for investors

CAPM was developed by William Sharpe (1964), John Lintner (1965) and Jan Mossin (1966)independently It describes the relationship between the systematic risk that the investmentadds to a market portfolio (presented by (β)) and expected rate of return on an asset AlthoughCAPM has been doubted about its application in many empirical studies in recently years, it isstill the fundamental model in most real world analysis Because CAPM can help investors inclassifying stocks, avoiding risk and realizing return through β Besides, CAPM also provideinvestment guidance to investors through estimating risk-return trade-off, investors canexplore if stocks are undervalued or overvalued in order to make decisions The CAPM modelcan be represented as:

E(R i)=R f+β i[E(R m)−R f]Where:

E(R i) : The expected return of the stock i

R f : Risk-free rate (of assets from which the expected returns are certain)

E(R m) : The expected return on the market portfolio

β i : The degree of systematic risk of firm i’s stock returns relative to the risk of the(stock) market portfolio’s returns

SML is the representation of CAPM It displays the risk – expected rate of return of anindividual stock under the condition of an efficient market In SML, the vertical axis is the

risk-free rate, the horizontal axis represents the β and the slope of SML is E(R m)−R f This is a

helpful tool to consider whether investors should invest in a stock or not Every stock isplotted on the SML individually If a stock is above SML, it means that this stock is

undervalued because with a given amount of risk (β¿, investors get higher return Conversely,

if a stock is below SML, it is overvalued because we get lower return with a given amount ofrisk

Based on the model of CAPM, for any individual stocks, we can realize that the expected

return will increase when β increase, therefore, it is a positive relation between the value of β

and the expected return of stock in the market

The model always starts with the necessary assumptions that have the effect to simplifying butstill ensure not change the nature of the problem In general, CAPM also ignores somecomplexities of financial market to obtain the linear relationship between risk and expectedreturn According to Sharpe-Lintner, there are seven assumptions when applying CAPM:

 Investors are risk-averse, utility-maximizing, rational individuals

 Markets are frictionless, including no transaction cost and no taxes

 Investors plan to invest for the same single holding period

 Investors have homogeneous expectations or beliefs

 All investments infinitely divisible

 Investors are price takers

 The investors can borrow and lend unlimited amount at the risk-free rate

There are some problems arose from conducting CAPM structure model and assumptions as

follows Firstly, CAPM is based on single-factor model that just use systematic risk (β) and

eliminate no other investment characteristics in estimating expected return of assets.Therefore, CAPM may not evaluate the entire risk although it is easy to understand and apply.Secondly, CAPM is applied in a single - period model that does not consider multi-periodimplications because β is calculated based on the historical stock price Thus, β in the currentperiod may be negative for the future investment objectives

Although CAPM makes the restricted assumptions about how markets work and do notperfectly suitable for the realistic situation, the model requires little inputs Under theseassumptions, it helps investors in obtaining the risk-return, and generating the efficient assetpricing model

In addition to the theoretical limitations, implementation of the CAPM raises several practicalconcerns, some of which are listed follow Firstly, Richard Roll (Richard Roll critique 1977)

Thirdly, estimate β for long history of return may be inaccurate representation of the current

or future state of company (time-period bias) Because of the different estimation of β fromdifferent period, CAPM may estimate different risk-return for same asset For example, a two-year β is unlikely to be the same as a six-year β Fourthly, CAPM cannot determine assetreturns by non-systematic risk So that in empirical study support for CAPM is weak, and itgives poor predictability of returns Fifthly, there is obvious to not be similar to CAPMassumptions that assume investors have the same expectations for a single optimal riskyportfolio In fact, the different investors have different expectations for the same asset

1 Is Capital asset pricing mode valid in Vietnam stock market?

2 How does the systematic risk (β) influence to the investor’s the expected return?

Positive or negative correlation?

3 Dividend can increase the compatibility of CAPM in Vietnam stock market?

The study focus on testing whether CAPM suitably apply for Vietnam stock market

Firstly, systematize the basic theory of CAPM and review some empirical tests

Secondly, estimate β of stocks in HSXthrough two methods: price return and total return.

Thirdly, clarify the affect’s dividend and test relationship between risk and return

Finally, make conclusion and recommendation

With research objectives, the study just focuses on analyzing and processing the sample data

be made through the results This study will not analyze the factors of the market that affect tothe investor decision making All decision depends on skills and hobby of each investor The sample data of this study are gathered through the company in Vietnam stock market(including only the stocks that are traded on HSX) From the data about capital market ofthese companies, we will use normal distribution and then pick the absolute size to decide asuitable sample size The time period will be taken from March, 2012 to March, 2014

To verify the application of CAPM in Vietnam, the study gathers data from public firmsregistered on HSX through statistical tool and using point estimator to choose study samplesize The research period is from March, 2012 to March, 2014

There are three independent variables (risk-free rate, β, and risk premium) and one dependentvariable (expected return of stock) Each independent variable is practiced via differentmethods The result of risk-free rate and risk premium are based on AswathDamodaranestimation methods.β is estimated through regression linear method that shows the relationshipbetween systematic risk and return on specified stock

After gathering and processing database, the study uses descriptive statistic to test whetherCAPM is suitable model when applying in HSX The study uses some statistical software such

as Excel, Eview

This study is conducted to test the application of CAPM in Vietnam stock market from the end

of March, 2012 to the end of March, 2014 This study contains 5 main chapters:

Chapter 1 mainly provides the background and the introduction of the objective of the study

To specific, this chapter will introduce the CAPM, state the CAPM theoretical problems andpractical problems, clarify research question and objectives, and give an overview aboutmethodology and data

Chapter 2 discusses the different versions of CAPM including Sharpe and Lintner version,Black version Describe three factors model Fama and French.Give the evidences about testingCAPM in different markets that have the methodology related to this study

CHAPTER 2: LITERATURE REVIEW

1.1 Overview of reviewed sources

Since the capital asset pricing model was discovered, there have been numerous testing studies

of CAPM However, the results of these studies are still conflicting Some authors support forthe CAPM theories when they find the empirical evidence on the relationship between theexpected return and risk of the stock One of the first studies of this model is "A Theory ofMarket Equilibrium under Conditions of Risk" conducted by William F Sharpe (1964), "TheValuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios andCapital Budgets" conducted by John Lintner (1965) Next to Fisher Black (1972) proposed theZero β CAPM in the study “Capital Market Equilibrium with Restricted Borrowing”, by usingthe basic theory CAPM and replacing risk-free rate with Zero β, these authors found therelationship between the return and risk of the portfolio This means that the higher risk get thehigher return

Conversely, the other authors doubt about the validity of the CAPM on the basis of theirempirical researches In historical, the rejected studies of the CAPM by author Richard Roll(1977) in study “A Critique of the Asset Pricing Theory's Tests” and Engene F Fama andKenneth R French in study “The Cross-Section of Expected Stock Returns” gave empiricalevidence that rejects the validity of the traditional CAPM theory Besides, there are also manyempirical studies that test the effectiveness of CAPM in different markets includingdeveloping and developed countries in recent years In general, those studies demonstratedclearly about the poor performance of CAPM in reality that the result was not consistent withthe actual rate of return Therefore, the authors tend to improve the CAPM in order toeliminate its defaults (such as Fama-French model) However, CAPM still one of the mostpopular asset pricing models despite the critiques about its application and feasibility because

it will be dropped and not researched until now if it completely defeats

1.2 Scope and limitation

As this study mentions above, CAPM is developed in the long time by the different authors,thus, CAPM has a lot of versions that are built on assumptions, circumstances, and the

purposes of those authors However, it is impossible to review all of the versions, so this studyjust focuses on Sharpe-Lintner version and Black version that are known as the most well-known model of CAPM because of its simplicity, utility and relative faultlessness Besides,the study examines the validity of CAPM so the other models that the study mentions just areused to support

There are a lot of empirical tests of CAPM in different markets and different period time.However, the study cannot cover all of the researches that relate to this topic Therefore, thisstudy lists a few representative studies as a basic for research The researches that test CAPM

in the markets as nearly similar to Vietnam, at the same time, have the recently period timewill be selected in order to increase the suitability and application

The following parts will give an overview about the theoretical review of these two aboveversions, next show some critiques of Fama-French about CAPM and introduce theiralternative model – three factors model, then present some approving or disapprovingempirical tests in US, China and Pakistan stock market

2.1 The single factor model: Sharpe and Lintner version

Markowitz (1959) and Tobin (1958) informed the one period mean-variance portfolio modelwhich was built on the expected utility mode of Von Nuemann and Morfenstern (1953) and isextended into the Sharpe (1964) and Lintner (1965) in turn Markowitz mean-varianceportfolio is the portfolio that minimizes the variance of portfolio return in a given expectedreturn and maximizes the expected return in a given variance (Fama and French, 2004) Thisanalysis stated that investor should allocate their wealth among the variety of assets available

in the market, given that investors want to maximize utility in one-period According theinvestor wealth allocation decision characteristics, the Sharpe-Lintner asset pricing modelbuilt the relationship between the expected return and risk for assets and portfolios

In fact, the Sharpe-Lintner model is also similar to other versions of CAPM that has to complywith some assumptions about the real world in order to make the model more rational Theseassumptions include (a) all investors are risk-averse investors who maximize the expected

expectations about asset returns that joint normal distribution, (c) the investors can borrow andlend unlimited amount at the risk-free rate, (d) the quantities of assets are fixed and all assetsare marketable and perfectly divisible, (e) asset markets are frictionless and information iscostless and available to all investors, and (f) there are no market imperfections such as taxes,regulations, or restrictions on trading (Attiya Y Javed, Alternative Capital Asset PricingModels: A Review of Theory and Evidence)

When investors can borrow and lend unlimited amount at the risk-free rate, the expected

return of asset that is uncorrelated with expected return of market (E(R m)), at least must be

equal to the risk-free rate Therefore, under the above assumptions, CAPM’s goal is tominimize the variance and maximize the expected return of their portfolios (Athayade andFlores, 1999) with the amount of risk-free rate Sharpe-Lintner version of CAPM can beequated as:

E(R i)=R f+β i(E(R m)−R f)

E(R i) is presented as expected return on stock i, R f is risk-free rate, E(R m) is expected return

on market portfolio and β i is the measure of systematic risk of stock i to market and β ican be

calculated through formula cov (R i , R m)

var(R m) Therefore, combining the equation with the

assumption of risk-averse investors, it seems to be rational to conclude that high risk (high β)stock should be received the higher expected return than low risk (low β) stock Tocircumstance, systematic risk equal zero (β= 0), investors will expected to get the amount of

return that is equal to risk-free rateR f at least When systematic risk of stock is higher thanzero, the expected return of investors will be higher than risk-free rate by multiplying riskpremium and the proportion of systematic risk (β) Through that, we can draw some importantfollowing:

 If β equal to 0 – the expected return of stock have a β equal to 0, is riskless profit, R f,because in this case:

E(R i)=R f+β i(E(R m)−R f)=R f+0(E(R m)−R f)=R f

 If β equal to 1 - the expected return of stock have a β equal to 1, will be market return,

E(R m), because in this case:

E(R i)=R f+β i(E(R m)−R f)=R f+1(E(R m)−R f)=R f+E(R m)−R f=E(R m)

 In Sharpe-Lintner model, these authors still didn’t mention about β negative’ssituation For this reason,a frequently asked question is whether or not β is negative Infact, the answer is yes when some stocks move in the opposite direction of the stockmarket and make the overall risk of the portfolio decrease Although these stocks arerare, they do exist For example, the companies that do most of their business overseasmay get the negative β because it is not affected by the domestic market Inconsequence, negative β cause that the expected return is lower than risk-free rate.However, it is reasonable because it reduces the risk

The expected return of a stock can positively related to the risk of stock, meaning thatinvestors expect the stock high risk will have high profit and vice versa In other words,investors will hold risky stocks if only the expected profit is large enough to offset the risk.Sharpe and Lintner were found a new field in asset pricing model They detected the linearrelationship between the expected return of asset and the risk of asset

Otherwise, from the equation of CAPM, the risk premium can be written:

expected value of the error term is zero for all observations E(ε¿¿i)=0¿ and rm is

deterministic and uncorrelated with the error cov(r m , ε i¿=0 Thus, when testing and using

regression, CAPM is usually written as: (Attiya Y.Javed, Alternative Capital Asset PricingModels: A Review of Theory and Evidence)

r it−r ft=α i+β i(r¿¿mt−r ft)+ε it¿

In the equation, r it is the rate of return on stock i at time t, r mt is the rate of return on the

market portfolio at time t and ε i is error term This regression can help us to estimate β i

through the stock price return and market return β i Coefficient is defined as the coefficient ofvariation measure individual stock returns with volatility profitable market portfolios Forexample, stock A have β is 2 indicates that stock A returns double fluctuate profitablemarket, meaning that when the economy is good, a rising profit of stock A faster than themarket, but when the economy is bad, the stock A returns more rapid decrease than themarket β is defined as the coefficient of variation measure of profitability Therefore, βcoefficient is considered as measure of stock risk Because authors started coefficient β is used

to measure the risk of a stock Therefore, the expected return of a stock can positively related

to its β coefficient

2.2 The two factors model: Fisher Black version

Realized that borrowing and lending unlimited amount at the risk-free rate is unrealisticassumption, Fischer Black (1972) eliminated this assumption and suggested using zero- β

portfolio (R¿¿ z )¿ as the substitute of risk-free rate in Sharpe-Lintner version In this version,each investor can hold a different portfolio of risky asset, and market portfolio will be aweighted sum of the investors’ portfolios Following Black, he stated that if a portfolio has therisk-free rate (such as Sharpe-Lintner version), it will be less risky than the portfolio that haszero-β portfolio Because Black model treats all assets as risk but it classifies the risky assetportfolios that has minimum variance of all portfolios and is uncorrelated with market

portfolio (R m ) is called as a zero-β portfolio Reasonably, the expected return on portfolio R z

must be greater than the return on portfolios that has risk-less asset availably Therefore, Blackthinks that expected return on zero- β will reflect more accurate about the return-riskrelationship of assets than using risk-free rate

Theoretically, Black version of CAPM depends on two factors: zero β and non-zero βportfolios, thus, it is also known as two-factor CAPM and it has some different results in

estimation of the expected return of stocks Black (1972) required two assumptions that aremore restrictive than the usual assumptions used in CAPM First, it is assumed that markethave two cases There is no riskless asset and no risk-free rate borrowing or lending.Otherwise, if there has a riskless asset, investors can perform long positions in the risklessasset, however, the short positions (borrowing) in the riskless asset are not allowed Second, inboth cases, investors have been assumed that they can take unlimited long or short positions inthe risky assets

Black’s equation may be presented as following:

E(R i)=E(R¿¿z )+ β i¿ ¿

Where:

E(R i) : The expected return of asset i

E(R¿¿z)¿ : The expected return of a zero- β portfolio z

E(R m): The expected return of the market portfolio

The above equation can apply for any asset and portfolio that obeys the assumptions of Black

version If β is equal to 0 (β=0), it is obviously that the expected return of stocks will have the same expected return of portfolio z (E(R¿¿z)¿) because the return of portfolio z isindependent from the return of market portfolio If there has the existing risk-free rate that isuncorrelated with market portfolio; it seems to be a zero-β portfolio and we can use it for

calculating Nevertheless, almost circumstances of zero-β portfolio require the calculation and estimation based on time-series data of stocks if stable over time, unfortunately, zero- β is not

immediately observable (Diderik Lund, 2004) because there is difficult to distinct from theriskless asset that is completely uncorrelated with market portfolio, the data that is set in themodel may have some variances Thus, some researches assumed that zero-β portfolio isconstant (Shanken, 1985)

Although Black found that the evidence indicates the existence of a linear relation betweenreturn and risk when is consistent with a form of the two factor model which specifies the

the Zero-β portfolio can be considered a weak factor given its low signal to noise ratio (low

explanatory power of the cross-section of stock return by itself and difficulty in obtaining the

expected return of zero-β portfolios), not taking it into account in the time - series regression

leads to a worse fit of the data by the model (the data is used in estimating usually is in thepast), generating more intercept significantly different than zero that produce more abnormalreturns (Seung C Ahn& Alex R Horenstein) A positive value of intercept can lead to therejection of the CAPM theory and the CAPM considers that the intercept is zero for everyasset (Kapil&SakshiChoudhary)

The result of Black indicated that the expected return on any risky asset is a linear function of

its β , just as it is the risk-free rate borrowing and lending in Sharpe-Lintner version It means

that expected return of a stock is related to the risk of stock, if investors expect to get a highreturn, they must bear high risk and if investors want to get rid of risk, they will just receive alow return However, if there is a riskless asset in Black version, the slope of the line relating

the expected return to its β must be smaller than no restrictions on borrowing Thus, both

models of Sharpe-Lintner and Black concluded the linear relationship between the expectedreturn and risk despite some differences in the estimation results

Alternatively, Black, Jensen, and Scholes (1972) also did a research about “two-factor model”

that analyzes the returns on portfolios of stock at different level ofβ i They found that thismodel does not provide a consistent result with the Sharpe-Lintner model It estimates the

expected returns on portfolios of stocks are higher at low levels of β i and are lower at high

levels of β i than Sharpe-Lintner version Therefore, the empirical findings of Black, Jensen,and Scholes are consistent with the Black model in which borrowing is restricted

2.3 The three factors model: Fama-French

According the assumptions that CAPM requires to calculate the expected return of assets inthe real world, many researchers concluded that CAPM still has not given accurate results.There are two problems that were mentioned by Fama and French (2004) Firstly, it isbehaviorists Their view is based on evidence that stocks with high ratios of book-to-market(BE/ME) are typically firms that have fallen on bad times, while low ratios of BE/ME isusually growth firms With the information of sorting firms on BE/ME ratios, investors tend tooverreact to good and bad times The result is the change of stock price that is too high for

growth firm (low BE/ME) and too low for distressed firms (so-called value firms) (highBE/ME) In fact, some investors tend to feel extremely excited about stocks that have donevery well in the past or had the good news They buy them and make other follow, so thatthese stocks become overpriced Similarly, to stocks that have the poor performance in thepast, they will not be attractive so it is underpriced Therefore, when the overreaction happens,there is high return for value firms and low return for growth firms (Josef Lakonishok, AndreiShleifer and Vishny) Secondly, the investors need a more complicated asset pricing modelbecause CAPM is based on too many unrealistic assumptions For instance, CAPM assumethat investor want to maximize the expected return at the end of period and do not care aboutlabor income or future investment opportunities, so a portfolio’s return variance does notreflect all of aspects of risk therefore, β is not the description completely of an risky asset andthis cause the difference in expected return among investors by the differences in β

To response to the poor performance of the CAPM, Fama and French (1993) proposed a threefactors asset pricing model (it also called as Fama-French model) for calculating the expectedreturn This model are based on three factors namely: excess market portfolio return, thedifference between return on portfolio of small stocks (relative to market capitalization) andthe return on the portfolio of big stocks, and the difference between the return on a portfolio ofhigh BE/ME (book-to-market equity) stocks and the return on a portfolio of low BE/MEstocks The formula is written as:

E(R i)−R f=β i(E(R M)−R f)+β is E (SMB )+ β ih E(HML)

Where:

E(R i) : The expected return of portfolio

R f : Risk-free rate of return

E(R M) : The expected return of market portfolio

SMB : (small minus big) the expected value of the difference between the returns ondiversified portfolios of small and big stocks

HML : (high minus low) the expected value of the difference between the returns ondiversified portfolios of high and low BE/ME ratio on stocks

β i , β is , β ih: are the corresponding coefficients

This model provides a competitive advantage comparing to CAPM because CAPM is just asingle factor model Fama and French (1993) find that the three factors model captures much

of variance in average return for portfolios based on size, BE/ME that cause problems forCAPM Therefore, the investors typically concede that the three factors model can determinevariation in returns missed by the market return and the size and value effects in averagereturns that is unexplained by the CAPM However, from a theoretical perspective, the mainshortcoming of three factors model is its empirical motivation that investors are usually notmotivated to predict the SMB (small minus big) and HML (high minus low) in calculate theexpected return (Fama and French) Besides, this model is not cost effective that does also notperform significantly better than CAPM when it applies to individuals stocks (J Barthody andPeare)

In this part, author will show some empirical studies and evidences of testing CAPM and threefactors model Fama-French in different markets and samples to support ideas and objectivesfor this paper The empirical part, author divides into three main purports Firstly, the testingCAPM and three factor model in different samples will be said in 3.1, 3.2, and 3.3 In part 3.1,the study examines which model can give better result in estimating stock portfolio return, andthe result of study stated that the three factors model can explain better return rate of stockportfolio than the CAPM In addition, the study also said that the other factors can influence tothe expected return of CAPM equation In contrast, the study 3.3 give contrast result whenexamined whether the effectiveness model by using two separate portfolio groupings, the firstgrouping is 25 size and book to market equity portfolios and the second grouping is portfolio

of 12 industries The first group portfolio result is the three factor model maintained itsdominance over the CAPM but the result of testing second group portfolio is more interesting,the CAPM now demonstrated superiority the three factor model For other sample test such asstudy 3.2, J Bartholdy and Peare provide the result the CAPM work much better than thethree factor model for estimating the expected return of individual stock Secondly, the study

examines the validity of CAPM in emerging and developed markets Inspecifically, the study3.3 tests CAPM and three factor model in U.S developed markets, and the result stated thatboth CAPM and three factor model cannot rejected On the other hand, the study 3.4 tests thevalidity of CAPM in China stock market, and the result of study is insignificant and β valuecannot apply to present the expected return accuracy To contrary, the study 3.5 is also therejection of CAPM in Pakistan stock market when using hypothesis for determining theexplanatory power of CAPM in estimating return of oil, gas and fertilizer companies listed onKSE.Thirdly, the last study 3.6 talks about the effect of dividend yield to stock return throughthe study “Dividend yields and Stock returns: Insight from the Empirical Evidence of Korea”

conducted byJinwoo Park in 2010

3.1 An Empirical Analysis of CAPM and Fama-French in China

Stock Market

Some empirical studies have pointed out that CAPM cannot estimated the return of stockportfolio accurately, and employed the other models can give better result such as three factorsmodels for example That also reported that the CAPM had poor performance in estimatedasset return

In 2009, Professor Liu Yaoguang published his study was entitled "An Empirical Analysis ofCross-Section Stock Returns on the Chinese A-Share Stock Market." The research objectives

is to check the effectiveness of the three factors model Fama-French (1993) reported inestimated expected return of the A-share of China's stock market, in the period from 1996 -

2005 At the same time, the authors conducted a review of this model is more effective inpredicting return the stock compared to the traditional CAPM

The data used in the research include return rate of the companies listed on the A-shares Chinamarket, during the period January 1996 to December 2005 Samples of companies in theresearch including companies have normal equity capital and a positive book value of equity.However, the return rate of the companies has negative book value of equity still used tocalculate the market return Data of book value and market equity was collected from CSMARdatabases

In Liu’s study was tested three factor model of Fama-French and the CAPM for both theShanghai and Shenzen stock market The research's methodology based on the methodology instudies of Drew (2003); studies have inherited methods in the study of Fama and French(1993) applied to the stock market with small size The list is set up every year, the entiresample is divided into two types of categories on the scale By using the midpoint of marketvalue for the whole sample, with a market value collected at the end of December each year,the sample was divided into categories of small companies, including the company's marketvalue of equity is less than the midpoint, and the list category of large companies, includingcompanies with a market value of equity is greater than the midpoint value Then the samplewas divided into three categories have equal number of companies based on the BE/ME ratio

of each company in the sample Accordingly, we will have been collected into six categories:

SL, SM, SH, BL, BM, BH All six of this list will be re-established at the end of Decembereach year, when the value of scale and proportion of BE/ME are changed at the end of theyear Regression testing is conducted in accordance with the idea of adding turn, size factors-SMB and factors BE/ME ratio- HML into market factor of CAPM model, consider the impact

of these factors by observers see the explanatory power of the model after adding otherfactors

Adjusted R2 for six securities portfolios are averagely increased by 3% when the size SMB was added to the CAPM All regression coefficients of market factors remain positiveand statistically significant Portfolio of small capital securities have regression coefficient onthe scale is a positive value, and negative regression coefficient for portfolio of big capitalsecurities That means that the scale factor negatively affecting the stock market in China.Compared with the regression results for the CAPM, after adding size factor on the market

factor-factor model, although adjusted R2 values was not increase too much, but it also providesevidence that the model CAPM was increase the explanatory power of estimated cost of equity

by the size factor On average, the regression coefficient of the securities portfolio with high

BE/ME ratio have higher value than securities portfolio with low ratio BE/ME Adjusted R2

average increased by 3% while the BE/ME ratio factor was added to the market model CAPM

To consider models in two model CAPM and three factors model Fama-French which will be

operated more efficiently, Professor Liu comparing adjusted R2 values and the intercept term

of each model The results show that the R2 of the three factors model have higher value thanthe CAPM average by 6.6% Three-factor model can explain better expected return than theCAPM When running the regression for CAPM, the intercepts coefficients portfolios aresignificant at the 1% significance level This is showed that there are other factors thatinfluence the expected return, such as the size factor and the BE/ME ratio In contrast, theintercepts coefficients when run three factors model are not statistically significant at the 1%significance level Thus it can be stated that the three factors model can explain better returnrate of stock portfolio than the CAPM

3.2 Estimation of Expected Return for Individual Stock: CAPM vs

Fama-French

The most practitioners tend to use a single factor model (CAPM) to estimate the expectedreturn for an individual stock and three factors model (Fama-French) for portfolio returnsacademic J Bartholdy and Peare (2002) conducted the research about “The estimation ofexpected return: CAPM vs Fama-French” in order to compare the performance of the Fama-French model with the CAPM for individual stocks The data of this study was collected thedaily adjusted prices from CRSP (The Center for Research in Security Prices in US) with thetime period from 1970 to 1996 Particularly, the daily return was calculated by the simpleholding period rate of return between days Weekly return was taken from Wednesday to thenext Wednesday to eliminate the effects from weekends and Mondays because there has thevolatility of stock returns over weekends (Peter Fortune) And end of month stock prices wereused as monthly returns Besides, the 3-month T-bills was used for the risk-free rate for thetime-series regression The methodology of the study follows the two main steps Firstly, theycalculated the expected return of individual stock based on CAPM that are obtained by usingdifferent time frames, data frequencies and indexes The research found that five years ofmonthly data and an equal-weighted index (every stock is given the same weight or important

in a portfolio or index) provide the best calculation However, the performance of this modelwas still poor that it causes for the average three percent of differences in returns Secondly,they used Fama-French model to estimate for individual stock return by using five years ofmonthly data Unfortunately, this model did not work much better than CAPM because itexplained on average five percent of differences in return Therefore, the results provide a

rational explanation for why CAPM is used so extensively by practitioners that calculate theexpected return of individual stocks

3.3 Empirical Evidence from America Stock Market

With the purpose is to compare and test the effectiveness of two asset pricing models that arethe Sharpe &Lintner CAPM (single factor model and Fama-French (three factors model),NimaBillou conducted a research named “Tests of the CAPM and Fama and French Three-Factor Model” in 2004 through testing in two separate portfolio groups The first groupcontained 25 portfolios that was constructed and represented by the intersections of 5portfolios formed on size and 5 portfolios formed on the ratio of BE/ME The study will testthis group in two different time period, including from 7/1963 to 12/2003 for a total of 486observations and from 7/1926 to 12/2003 for a total of 930 observations The second groupwas 12 industry portfolios that have the available data, but this group was examined in threeperiods: 7/1926 to 12/2003 for a total of 930 observations, 7/1963 to 12/1993 for a total of 366observations, and from 7/1963 to 12/2003 for a total of 486 observations The portfoliosinclude all NYSE, AMEX, and NYSDAQ stocks and the risk-free rate was taken by the onemonth Treasury yield that is provided by Ibbotson and Associates Besides, the independentand dependent variables for both the CAPM single factor model and Fama-French threefactors model were sourced from Kenneth French’s website

The methodology for evaluating two asset pricing models of this study was to use the MAVA(The mean absolute value for the alphas) by looking at the t-statistics for the alphas in order toobserve the statistical significance This method indicates that the model with the lowestMAVA for the alphas, or intercepts, is a better model theoretically in estimating the portfoliosreturns because the CAPM implies that the value of alphas or intercept should be zero.Looking at the finding results of this study, at the first portfolio group, it becomes clear thatthe Fama-French model demonstrates its superiority To specific, from 7/1963 to 12/2003, theCAPM displayed the MAVA of 0.3 versus the MAVA of 0.13 for the Fama-French In

addition, the Fama-French model had a higher value of R2 than CAPM where 0.89 versus0.72 From 7/1926 to 12/2003, it was the same that the MAVA of CAPM is 0.23 and higher

than the MAVA of 0.19 for Fama-French, but R2 is lower where 0.77 versus 0.88 At thesecond portfolio group, it was inversely From 7/1926 to 12/2003, the CAPM showed the

MAVA of 0.11 versus 0.14 for Fama-French with R2 is 0.75 for CAPM and 0.77 for French From 7/1963 to 12/1993, the MAVA of CAPM and Fama-French were 0.1 and 0.14

Fama-with R2 is 0.73 and 0.77, respectively From 7/1963 to 12/2003, it was similar, CAPM had a

lower MAVA and R2than Fama-French with 0.11 versus 0.13 and 0.66 versus 0.7

With the above results, for 25 portfolios, Fama-French model is better than CAPM but for 12industry portfolios, CAPM is judged the more effective model Thus, this evidence indicatesthat the author should not be based on only one type of portfolio group in order to evaluatewhether or not an asset pricing model is superior to others All in all, the study concluded thatCAPM single factor model and Fama-French three factors model had the effectiveness in USStock Market

3.4 The Application of CAPM in China Stock Market

Many researchers conducted a number of empirical cases which concluded both positive andnegative results in order to test the effectiveness of CAPM since it was announced anddeveloped Therefore, with the uncertain results of previous studies, Fan Wang (2013) did aresearch “A test of CAPM in China’s Stock Market” to answer the question whether or notCAPM is the correct model for the emerging stock market as China To specific, the objective

of the study is to examine the relationship between the expected return and risk of stocks.Being along with this purpose, the study focus on the test of CAPM on China stock marketwhich mainly contains the stocks traded in Shanghai Stock Exchange and Shenzhen StockExchange by using the supportive statistical software such as SPSS, Stata, and Eview forcalculating and analyzing data Besides, the sample data of the study was collected throughthese above two stock exchanges that randomly selected 90 stocks The time period is set fromJan 4th, 2012 to Dec 31st, 2010, thus, the data set just contains 1 year data of the listed stocks

To execute the examination of the study, Fan Wang will clarify and obtain the factors ofCAPM such as risk-free rate (this study used bank loan rate of Shanghai banks as a risk-freerate), risk premium (although there are a number of indexes in Shanghai stock exchange, thestudy just use Shanghai & Shenzhen 300 index as the return of market because this indexreflects the market trend for both of the stock exchanges), and apply a two-step regression toactualize the whole examination In the first step of regression, the study calculated the β of 90

return of the market index by using a time series analysis In the second step used a section regression which targeted every stock in the sample through conducting a regressionbetween the β that was obtained in the first step and the geometric mean rate of return in order

cross-to obtain the SML The purpose of this step is cross-to compare the result with the estimated result

of CAPM Furthermore, SML also help them in indicating what stock is underpriced and whatstock is overpriced

With the empirical test conducted, Fan Wang concluded that CAPM still is not the right modelfor China stock market for some following reasons Firstly, the parameters of the estimationmodel is insignificant, the correlation and the covariance between the expected return of thestocks and the predicted systematic risk are relatively weak Similarly, the explaining ability

of systematic risk to the rate of return is relatively low (Adjusted R2 is just 29%) Therefore,the linear relationship between rate of return and the systematic risk is not consistent Forexample, a high risk of stock does not always get a high return and conversely Secondly, theChina stock market is still an emerging market which the market is inefficient and immature

so it does not obey all theories and assumptions of CAPM Thus, when the study obtained the

data in China stock market, the result is insignificant and β i value cannot apply to present theexpected return accuracy

3.5 Empirical evidence from Karachi Stock Market

H JamaZubairi, ShaziaFaroog announced “Testing the validity of CAPM and APT in the oil,gas and fertilizer companies listed on the Karachi stock exchange” in Pakistan business reviewOctober 2011 The research aimed to investigate whether CAPM is a valid model forevaluating the relationship between risk-return of fertilizer and oil& gas sector companieslisted on Karachi Stock Market The consequence of investigating showed that CAPM isarrived as a weak correlation between realized excess return (the actual return) and expectedreturn (based on CAPM)

The sample was collected quarterly from 17 fertilizers, old and gas companies listed onKarachi Stock Market The time period was from 2004 – 2009, excluding the last two quarter

of 2008 when a floor was imposed on the market

To explain the power of CAPM, the author had used CAPM equation:

R i−R f=α+β i(R M−R f)

Where:R i is required rate of return on stock, R fis the compensation received when inventor

placing money in an asset with a certain expected return β iis a measure of systematic or

non-diversifiable risk of the asset R Mis expected rate of return on the stock market The researchhad used Karachi Interbank Offer Rate (KIBOR) as the risk-free rate that is used benchmark

with a high degree of certainty R i andR Mis obtained actual quarterly return on individual stockand stock market

The author had used regression analysis to test the hypothesis; and the result is to reject the

null hypothesis that the intercept α when CAPM is imposed on the stock returns data is equal

to zero The research also indicates that the level of significant is 10% where the intercept isvery high Moreover, R-square was very low, show that 1.9% variation in realized excessreturn was interpreted by CAPM The result also indicated that high standard deviation ofrealized excess return shows that there is no consistency in stock price of these companies Insum, the data analysis revealed almost no correlation between realized excess returns andexpected return based on CAPM

3.6Dividend yields and Stock returns

In reality, CAPM is preferred to apply due to its simplicity and unsophisticated, each investorcan be easy to use this model to calculate the expected return for stocks However, theseadvantages are also its short-comings because it does not cover all risks of assets For thisreasons, apart from Fama-French considered adding two factors of size and value companies

to CAPM, several researchers proposed the dividend as an additional factor because theinvestors rationally need to require the higher amount of returns on stock with higher dividendyields in order to compensate for the higher tax of individual income when they receivedividend But this is still a controversial issue Black and Scholes (1974) found no statisticallysignificant between the portfolio’s return and its dividend yield while Litzenberger andRamaswamy (1979) indicated a significant positive relationship between return of commonstocks and dividend yield for the period of 1936 - 1977 Recently, Jinwoo Park (2010)conducted the research “Dividend yields and Stock returns: Insight from the EmpiricalEvidence of Korea” to examine whether the dividend yield effect exists The sample consisted

of common stocks traded on the Korea Exchange (KRX) from March 31, 2000 to March 31,

2008 and was divided into five portfolio based on dividend yield

To specific, individual stock return was computed by stocks prices at the end of each monthand dividend yield, and then it multiplied by its weighted where market capitalization at theend of March each year was used as weight in order to calculate the value-weighted returns ofportfolio After that, the study used CAPM model that a time-series regression between thevalue-weighted returns of portfolio and market return was conducted for each of fiveportfolios as the following:

R pt−R ft=α p+β p(R m−R ft)+ε pt

Where R pt is the value-weighted return of portfolio at time t The result of the study showedthat Korean market had the positive relation between dividend yield and return that the highestdividend yield portfolio was higher by 1.94% each month than the lowest yield portfolio andzero-yield had negative average return of 1.2% per month

3.7 Conclusion

Based on evidences of empirical studies are provided above, the estimated expected return ofstock portfolio has many differ greatly when using CAPM to calculated, such as study 3.1 and3.3 for examples So that, the result of CAPM depend on types of portfolio, and it is still in thedebate and testing period In contrast, study 3.2 show the result of CAPM for individual stock

is more validity Besides, the study 3.3, 3.4 and 3.5 show the CAPM is valid or not in differentmarket, such as study 3.3 CAPM and three factors modelsare valid in U.S stock market, study3.4 and 3.5 stated that CAPM cannot apply for China stock market and Pakistan stock market

in turn So that the validity of CAPM still in the process of examination In this paper, theauthor will test the validity of CAPM for Vietnam stock market by using individual stock data.Because of the last study 3.6, this study considers adding dividend to the testing

The studies are written and discussed above show that there are many researchers havecontinued to research and development since the CAPM was published by Sharpe and Lintner

in early 1960 Until now, the CAPM is still a controversial model and it is still in the process

of development and perfection Follow to the studies and findings and arguments of

researchers, apparently, it stated that there are many doubts about the validity of CAPM andconsidered factors can add to CAPM to support it can more stable and exact In other word, itshow the evidences and verification of the real relationship between the expected return andrisk of financial asset, and stock is the mainly asset in the discussion of study Nevertheless,the versions of CAPM have been required too many assumptions in using the model, thus, itdoes not hold the hypothesis in the real world Accordingly, the researches about the testingand rejection have contributed many new factors, including those factors are still beingconsidered along with the development of the market and economy It further expand andincrease the depth of the model, making the model more and more accurate than the last ones,this is also encourage the researchers will continue research more about CAPM

The empirical studies, are indicated above, have more practical implications and relations thanthe discussion about the theoretical of model versions The empirical researches are discussed

in this study are the great examples of the application of the CAPM in emerging anddeveloped markets Some of empirical studies stated that traditional CAPM is not appropriatefor market which they are researched because of various reasons and characteristics of eachmarket However, in some researches about testing CAPM in different size of financial assethad found out the validity of CAPM in estimating the expected return

Because of various results and different conclusions of each study was mentioned above, andthere are still have many doubts and argument about the new factors added to the CAPM orother factors are being considered and researched Therefore, in this study, authors just stillfocuses on the examination of traditional CAPM in Vietnam's stock market, in specific it is HoChi Minh Stock Exchange

in Vietnam It also aims to examine the relationship between the expected return and risk ofsome representative stocks listed on Vietnam Stock Market (specifically in Ho Chi MinhStock Exchange) Therefore, the philosophical stance positivism will be adopted that the studyworks with the data reality and the end result of research is similar to natural scientist,however, the researcher is independent and cannot change the facts is one of thecharacteristics of this philosophy Furthermore, deductive approach is used in this study viausing the existing CAPM theory to develop hypothesis that CAPM is valid in Vietnam, thengenerating a research strategy to collect data, finally testing and confirming the hypothesis.Besides, quantitative analysis technique (such as statistic, mathematical, numerical data andEviews software) will be applied to explore the relationship and trends of the obtained data.This methodology plays an important role in implementing this study so that its details areexplained and described in the following parts in this chapter

2.1 Sampling techniques

Inheriting the ideas and basic methods has been presented in the previous studies, especially inthe study of Fan Wang (2013) in China The study will execute the testing of CAPM onVietnam stock market, but it is not completely identical to the distribution of sample data byportfolio industries; this article will set sample data by individual stocks Due to the limitedscale in Vietnam stock market and the limitation of the article, the study will narrow the scope

of research just examine the traded companies on Ho Chi Minh Stock Exchange. The listed

150 companies are taken from 305 companies listed on the Ho Chi Minh Stock Exchange thateliminate the smallest capital companies and highest capital companies To sort the stocks inorder, authors have used the standard normal distribution method for select samples However,data is not form as a normal distribution because of market characterizes To put the data intothe form of a normal distribution, in third step, the study has used the Natural Logarithmfunction in Excel After the data has been transformed to a similar normal distribution, theauthor continues to apply Central Limit Theorem and use Excel to calculate the z-score to putthe reference frame zero The equation to calculate z-score following as:

Z−score= x−X

s

Where:

x: Natural logarithm of market capitalization of stock

X: the mean of natural logarithm of market capitalization data

s: standard error (sample standard deviation)

The final step, the sample is set by 150 companies’ symmetry through the z-score equal zero.Exceptionally, in sample size, the author has removed the funds that have the different return

calculation, and the companies are listed and delisted after March, 2012 due to the lack ofdata The chosen range of average market capitalization is from 143 billion to 1,170 billion

2.2 Secondary data

2.2.1 Determining the stock exchange

There are three stock exchanges in Vietnam stock market: HSX (Ho Chi Minh StockExchange), HNX (Ha Noi Stock Exchange) and Upcom (including the stocks that is traded onOTC market) Nonetheless, this study just undertakes the test on HSX because of its potentialdevelopments in Vietnam stock market According to HSX report in June, 2012, HSX had 302listed companies, 6 fund certificates, 44 kinds of bond, attracted more than 668 trillion VNDthat increased by 400% compared to 2001 More than 100 security companies and the number

of accounts in total was over one million including 98.78% of domestic investor Besides,HSX dominated 85% market capitalization of Vietnam Stock Market The proportion ofliquidity was about 56.62% HSX is known as the stock exchange where gather the large-scale, high market capitalization and good liquidity companies Recently, HSX are expandingthe rate of room for foreign investors to attract investments Through the characteristics above,

Ho Chi Minh Stock Exchange is considered as a representative of Vietnam stock market andthere are the reasons why this study just focus on testing the companies listed on HSX

2.2.2 Dividend

Dividend is an amount of profits that a company pays to people who owns shares in thecompany The aims of pay annual dividend are to share benefits, encourage shareholders,attract other investors and so forth In reality, a company can pay dividend by cash or stocks toinvestors depending on the goals and conditional activities of company This action may affect

to the return of investors Therefore, this study will include the dividend in calculating theexpected return of stocks in order to discover whether or not dividend can help increase thecompatibility of CAPM in Vietnam Stock Market However, stock dividend and bonus stocks

do not affect to investor’s profit basically Besides, it will be more difficult to predict exactlyits return because it is determined at the price and time when the stock is sold Thus, the onlycash dividend is accepted in this study due to its handy For example, if a company pay 10%dividend by cash, it means that investors will receive 1,000 VND per share Dividend yields

are obtained from report of companies in the time of research and it will be computed in themonth it happens

2.2.3 Determining risk-free rate

Risk-free rate is defined as the interest where the investors know the expected return withcertainty or no risk of financial loss over a given period of time and it seems that investors aretrading in an absolutely risk-free investment In the perspective of CAPM, according toSharpe-Lintner an asset with the higher risk will be expected the higher return and vice versa,however, investors always demand the amount of the risk-free rate in order to compensate for

systematic risk (β) that cannot be eliminated by holding a diversified portfolios

In most empirical tests of CAPM, many researchers use the government bond rate as risk-freerate in calculating the expected return because it meets the basic condition of risk-free rate thatthere can be no default risk (AswathDemodaran) In fact, the largest and safest companiesalways have some degree of default risk and they may run out of their business anytimewithout restraint, but government securities can limit this risk through controlling the printing

of currency, thus, they are able to pay at least in nominal term and provide the given interestfor investors to fulfill their promises However, it does not always hold up when governmentborrow more foreign currencies than their own According to AswathDamodaran, in manyemerging market economies where governments are perceived as capable of defaulting even ifthey borrow in their local currencies To this circumstance, we need to adjust the localgovernment bond rate by estimating the default spread of this country on the bond todetermine risk-free government rate

Moreover, the expected return requires the different risk-free rate for each period to avoidreinvestment risk For example, we should not use the six-month Treasury bill rate to estimatethe expected return over a two-year period because we cannot know the reinvestment riskwhat the Treasury bill rate will be in the next six months Therefore, this study will use the 2-year government bond rate as the risk-free rate

Risk-free government rate = Government bond rate – Default spread

Following the AswathDemodaran, the local currency rating assigned to the Vietnam

5.5% Hence, the detailed risk-free rates from April, 2012 to March, 2014 are presented in thebelow table:

Table 3.1: The government 2-year bond rate and default risk

Time Government Bond

Rate (per year)

Rate (per month)

Default risk (per month)

Risk-free rate (per month)

2.2.4 Rate of stock return

Return rate of the securities in the portfolio are calculated based on the closing price of thesecurities traded on the market as well as the added value is based on dividends paid toshareholders The data rate of return for each stock in the sample is calculated by monthly, forthe period from March, 2012 to March, 2014 Although Vietnam stock market has establishedfor 14 years, it has very strong fluctuations during this period including both increase anddecrease sharply in the specific period Thus, it will not match the reality if the study uses

yearly data for calculatingβ and the expected return In addition, if it runs model by daily or

weekly data, there is not enough database for all stocks in the market because the liquidity ofstocks on HSX is not the same, some stock is unattractive or just trade a few day of month,hence, the data can affect to the reliability of research results.bien dong cuagiatrong 1 ngayqua lon, nhung no phananh dung ban chat cuacong ty ma do sudau co Consequently, in therange of topic, specifically the rate of return will be calculated by monthly database.Furthermore, one of the differences of this study from researches is to add the dividend Manypapers do not mention adding to the dividend-yielding, whereas a few other studies stated thatthe dividend affected the return rate That is why this paper will be divided into two samples totest whether dividends can increase the reliability of the model or not

The monthly return rate of individual stock calculation is based on the change of stock pricebetween that month and the previous month The closing price of month will be taken bydatabase from Ho Chi Minh Stock Exchange For stocks that do not have enough monthlyprice data, the author will substitute by taking the closing price of nearest month This studyuses the adjusted closing price that is the changed price when company split, bonus or addstock or pay dividend, calculate the return of stocks The equation (1) calculates rate of returnfor stock with dividend, and the equation (2) calculates rate of return for stock withoutdividend

(1) R it=¿t+(P t−P t −1)

P t−1

(2) R it=P t−P t −1

P t −1

Where:

¿t:The dividend value in period from month t-1 to month t.

P t: The closing price of month t

P t −1: The closing price of month t-1.

2.2.5 Rate of market return

VN Index is the market index of Ho Chi Minh Stock Exchange that reflects the market trendand is determined through the weighted average of all stocks in the market In the empiricaltests of CAPM, the researchers often apply the market index to calculate the return rate ofmarket portfolio as well as because it is fast and high utility Unlikely, this study will apply thenew method that is in CFA program instead of using the VN Index directly To obtain the rate

of return of market, the study needs to find out the monthly weighted market capitalization ofeach stock from April, 2012 to March, 2014 More specific, through the monthly marketcapitalization of each stock that obtained from sample technique, the author can know itsmonthly weighted market capitalization of stock and it is presented as:

W i M= P it Q it

Total Market capitalization

Where:

P it : The price of stock i at time t

Q it : The number of shares of stock i at time t

The rate of return of market portfolio is equal to the total sum of the return of each stockmultiply by its weighted market capitalization In the below formulas, the equation (3)calculates the return market with dividends while the equation (4) calculates the return marketwithout dividends

is small and its return calculation is different so it is still eliminated This will be a limitation

of study

2.2 Sample characteristics

Objective data of study here is the common stocks of companies listed on the Ho Chi Minhstock exchanges without the distinguish between stocks of the industries but excluding thefunds The transaction time has to lie on the time of research The reason for choose samplecharacteristics above is the finance companies such as investment funds will be differences inthe return calculation so it can be affected the results of this study, as well as companies withtransaction time less than two years as the companies listed and delisted after March, 2012will not have sufficient data The data spans from March, 2012 until the end of March, 2014.Around this time was chosen to run the model because the data source was updated and suitedfor model to reflect with the current economic situationand the applicability of this study.Furthermore, the market capitalization of the sample companies is neither highest nor lowest

so that it can be more representative for market

Based on the description of two CAPM models in literature review chapter, this study decide

to choose Sharpe-Lintner models to test the compatibility of CAPM on the Vietnam stockmarket Particularly, the study has to determine the variables of the model of CAPM such as

the risk-free rate, return of market and most important is to estimate β of each stock in the

sample size Addition to, if the study wants to examine the relationship between the expectedreturn and the risk of stock, it still needs to follow the restricted assumptions of Sharpe-Lintner

that is mention before despite some its unreality In the examination part of this study, it willapply the empirical test of Wang Fan in China in 2010 by undertaking two-step regression.Firstly, the study conducts the time-series regression between the excess market return and the

excess return of each stock in the sample in order to obtain βof 150 stocks Secondly, the

cross-section regression between the β that is obtained from the first step and the rate of return

of each stock will be applied to draw SML line and identify the relationship between returnand risk

However, there are two methods to calculate the return, including price return and total return.Price return (no dividend) is based on the only stock price that helps investors look at theirreturn over time; specifically this study uses the end of monthly stock price and index Tocontrary, total return method (with dividend) encourages putting the amount of dividendreceived into calculating rather than price alone Because there is not sure that what methodwill give the higher reliable results about the significant of CAPM, the study will use bothmethods to make conclusion To sum up, with the same sample size and market return, thestudy will execute the test of CAPM based on price return and total return The following isthe details of two-step regression

3.1 Determination of β for an individual stock

The β risk factor is the degree of systematic risk of the individual company stock risk return and the market portfolio risk return Therefore, the calculation on β may be executed by using

the time-series regression of Eviews software with two variables, including the monthly

expected value of risk premium (the market return minus risk-free rate, R m−R f¿ and the

monthly expected value of stock’s excess return (the stock return minus risk-free rate, R i−R f¿

To specific, the dependent variable is R i−R f and the independent isR m−R f and the factors of

CAPM such as risk-free rate, stock return and market return are determined as the above parts.The estimated regression equation of each stock can be presented as:

R it−R ft=α i+β i(R¿¿mt −R ft)+ε it¿

Where:

R it : The rate of return of stock i at the t.