Application of fama french factors to industrial corporations in vietnam stock market bachelor thesis of banking and finance

Keywords: Fama French five-factor, asset pricing model; market capitalization; to-market equity; profitability; investment; trading businesses... 1.2 Research objective The aim of this

MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM

BANKING UNIVERSITY OF HO CHI MINH CITY

BACHELOR THESIS

Major: Financial – Banking

Number : 7340201

Topic: APPLICATION OF FAMA FINANCIAL MODEL

TO INDUSTRIAL CORPORATIONS IN VIETNAM

Student’s name : Dương Đại Phát

Student’s ID : 030631152010

Guiding teacher : Msc Nguy n Minh Nh t

HCMC, February 2021

MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM

BANKING UNIVERSITY OF HO CHI MINH CITY

BACHELOR THESIS

Major: Financial – Banking Number : 52340201

Topic: APPLICATION OF FAMA FINANCIAL MODEL

TO INDUSTRIAL CORPORATIONS IN VIETNAM

Student’s name : Dương Đại Phát

Student’s ID : 030631152010

Guiding teacher : Msc Nguy n Minh Nh t

HCMC, February 2021

Keywords: Fama French five-factor, asset pricing model; market capitalization; to-market equity; profitability; investment; trading businesses

book-DECLARATION OF AUTHENTICITY

I affirm that I wrote this and have provided credit for each quote I certify that I have completed all processes and methods faithfully and honestly I mentioned to all of the people who contributed significantly to this effort

I would like to report that all representations and material found here are valid, right and authentic

Ho Chi Minh City, February 2021

ACKNOWLEGEMENTS

First of all, I'd like to express my appreciation to Mr Nguyen Minh Nhat for providing

me with helpful advice and motivation during this project

Secondly, I would like to thank my family and friends who have been there every step

of the way during my four years in Banking University

Lastly, best wishes to my lecturers and BUH for their knowledge, encouragement, and understanding

COMMENTS FROM GUILDING TEACHER

HCMC, .2021

Signature of guiding teacher

Table of Contents

CHAPTER 1: INTRODUCTION 8

1.1 Reason to research 8

1.2 Research objective 9

1.3 Research questions 9

1.4 Research subject and range 10

1.5 Methodlogy 10

1.6 Research contribution 11

1.7 Research outline 11

CHAPTER 2: LITERATURE REVIEW AND PREVIOUS RESEARCHES 13

2.1 Literature review 13

2.1.1 Arbitrage Pricing Theory (APT) 13

2.1.2 The Fama French three-factor model 14

2.1.3 Carhart four factor model 16

2.1.4 The Fama French five factor model 17

2.2 Previous researches 19

2.2.2 Previous researches from developed countries 19

2.2.3 Previous researches in developing countries 21

2.2.4 Previous research in Vietnam 23

CHAPTER 3: DATA AND METHODOLOGY 26

3.1 Data construction and processing method 26

3.2 Model 27

3.3 Factors calculating 31

3.4 Testing methods and Hypotheses of research 32

CHAPTER 4: EMPERICAL RESULTS 35

4.1 Descriptive statistics 35

4.2 Regression details 37

4.3 Relevant test 39

4.4 About the result 40

CHAPTER 5: CONCLUSION AND RECOMMENDATIONS 42

5.1 Conclusion 42

5.2 Recommendations 43

REFERENCES 47

CHAPTER 1: INTRODUCTION 1.1 Reason to research

The financial exchange and the banking sector are critical aspects of the national economy Early years, clearly for all investors (institutional or individual), the key aim

is to get the best possible return from investments Choosing stocks for your portfolio are close to gambling Knowing the statesman will definitely have a chance to find the side which will benefit a certain match A business share price can change regularly to match its actual market valuation, resulting in higher profit margins and thorough examination of pricing fluctuations, risk, past success and unpredictable future Investors like to consider whether or not their investments are successful before buying Understanding of different fundamental forces is the key option to make successful investment, the same with the skilled bettor that the football game requires

to be understood which influences can carry the outcome During over one hundred years of study, researchers have identified many pricing models Studies started in the mid-1960s and went on as part of the global economy, usually including the Capital Asset Pricing Model (CAPM) from Sharpe (1964), Lintner (1965) and Mossin (1968) (1966) In this model, only beta (market risk factor) is used to calculate the anticipated return of the stock There is a considerable denial regarding the reliability of CAPM theory According to Basu (1977), he noticed that all the above alternative interpretations fail absolutely in the Indian sense As a result, Rolf W Banz (1981) found that the CAPM was misspecified and that others have accepted that the calculation is inadequate for NYSE stocks After that, Fama and French conducted observational research that investigated the relationship between income and stocks, company scale, B/M ratios and beta Finally, the French three-factor model was released This model was later replaced the CAPM model after 30 years of use The three-factor model was, by all accounts, a popular model for forecasting business demand in the 1980s and in the future The Fama-French three-factor model was checked for its usage in the global capital markets in Australia, Canada, Germany, France, Japan, the United Kingdom and the United States Price and scale play a part

in both sectors In 1997, Mark Carhart substituted the three-factor model with a revised four-factor model that used a momentum factor to measure the monthly valuation of an asset The Carhart model is also used as an example to evaluate and administer mutual funds Analysis has shown that the complementarity effect can affect returns for the plurality, but not everyone Novy-Marx (2013) concludes that businesses with significantly higher earnings produce significantly more sales Aharoni, Grundy, and Zeng (2013) find that a rise in spending and a decline in profit margins were associated with an increase in profit From these results, Fama and French developed that diversification enhances return A five-factor model for understanding financial decision-making was released in the Journal of Financial Economics in early 2015 Their aim is to remove gains from the equation and

prioritize investments (CMA-Conservative Minus Aggressive Investment) This model has been tested in 23 developing markets, and reported to be successful in four regions – North America, Japan, the Asia Pacific and Europe (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, UK, )

The Fama five-factor model is attracting massive interest from investors in general and from the equity market in particular However, most researchers have not yet explicitly solved the problem In the analysis of Vo Hong Duc and Mai Duy Tan (2014), they graded the portfolio by running several regression models and splitting the portfolio according to their findings However, implementing the same portfolios will lead to surprise, such as various sets of variables that might be associated and bound to each other In comparison, modelling portfolios on just 14 individuals is not necessary to achieve reputation

However, to the best of the author's understanding, "Application of Fama French factors to industrial companies in Viet Nam stock market", I think the article would analyze the introduction of the concept into the Vietnam stock market and help investors maximizing their value in the stock market

1.2 Research objective

The aim of this thesis was to:

Firstly, analyze the influence of the five-factor model, including industry, scale, valuation, benefit, and investment factors has on listed industrial stocks returns in the Vietnam stock market

Secondly, describe the relevant valuation model and the fluctuation of the Vietnamese

capital market returns in a simple and detailed manner

Finally, offer several ideas on how owners, regulators, and other stockholders may enhance the continuing management of the fund

1.3 Research questions

To accomplish the above study's purpose, these are the questions it seeks to address:

- Does a company's book-to-market ratio, profitability, scale, market premium, and investment risk impact the portfolio's returns? Is there a favorable or negative connection between the stock results and the external factors?

- The Fama French five-factor model is sufficient method for describing the shifts in returns in the equity market in Viet Nam?

- Why investors make use of analysis to raise equity capital and reduce investment risks?

1.4 Research subject and range

The study emphasis is on utilizing the Fama French Five-Factor Pricing Model for mentioned manufacturing firms on the HNX and HOSE exchanges

- Space: This analysis used closed market details of the reported market capitalization of industrial firms on HOSE and HNX Companies outside of the banking industry, including insurance companies, insurers and brokerage companies, are not listed in these rankings

- Excel Office is used to synthesize data and equations accompanied by the usage

of Stata version 13 to execute regression and other related hypothesis testing procedures

Research model:

𝑟 𝑟 (𝑟 𝑟 ) 𝑠 𝑟

Where:

the expected return on asset i, the risk-free rate of Treasury bill,

the excess market return, , (Small minus Big) the size factor,

(High minus Low) the value factor, (Robust minus Weakness) the

profitability factor and (Conservative minus Aggressive) the investment

factor The coefficients is the asset’s sensibility, the intercept and the

error term of asset i at time t

1.6 Research contribution

The thesis provides many unique contributions:

The purpose of the study is to validate the usability of Fama French five-factor pricing models Thus, the study can clarify more precisely the factors of the Fama French model for investors and researchers who are studying and discovering the ways

to predict future income rates by limiting the immediate risks As a consequence, the concept can be extended directly to the Vietnam capital exchange

Experimentally, by assessing the feasibility of the templates, analyzing the test findings, and presenting any hints to investors and individuals when choosing and handling the portfolio

1.7 Research outline

Chapter 1: Introduction

This chapter introduces the motives for conducting this project, the research aims, the research subject, the research range and the scope of work

Chapter 2: Literature review

This chapter presents the theoretical background behind the current study, and previous research into a similar subject

Chapter 3: Data and methodology

This chapter outlines the study architecture and the specifics of the experiment The author defines the dependent and influencing variables, gives guidance for constructing a portfolio, and describes regression analysis and the steps involved in using it

Chapter 4: Empirical results

This chapter includes a regression study to demonstrate the effects of the key model discussed in Chapter 3 This section includes data on all variables, including association, graph, and compare and contrast of models Any segment concludes with

a description of the findings and a reference to previous research

Chapter 5: Conclusions and recommendations

Overall, I noticed that this study was useful in many respects The author offers a deeper interpretation of this analysis and gives suggestions for company owners, bank officers and public policy leaders The shortcomings of the analysis are stated and recommendations for future studies are made

CHAPTER 2: LITERATURE REVIEW AND PREVIOUS

RESEARCHES2.1 Literature review

2.1.1 Arbitrage Pricing Theory (APT)

In 1976, Ross did not merely expand an established theory but to establish a new idea This theory, regarded as the Arbitrage Pricing Theory (APT), became extremely popular The derivative is used in exchanging stocks and goods from one market to another, and a currency between various markets, in order to arbitrage The APT is a general principle of asset valuation whereby the projected return on a financial asset may be uniquely modeled as a linear feature of some macro-economic variables or theoretical market indices

However, it is not a model, but rather a simplified hypothesis of financial returns The Expected Return of a stock i is a function that represents both systemic and non-systematic risk factors

𝑟 (1)

Where:

is the expected return on asset i

𝑟 the riske-free interest rate in government bonds

the asset beta sensitivity of different risk factors

the risk premium of the factor

k= (1,2, n) the number of the factor

i the variable of stock

We accepted that non-systematic threats can be almost reduced by diversification of the portfolio as long as the compensatory considerations can only be attributed to systematic risks Systematic risk factors come under the concept of the APT hypothesis, including:

- Inflation

- Economic cycle

- Economic prosperity, GNP

- Evaluates a difference between short-term and long-term interest rate

- How different government and business bonds vary

- Exchange rate

- Gold price change

Comparing APT and CAPM, the latter is more of a limited strategy The APT would not require that a stock portfolio exists, but unlike the CAPM does not point out all of its risk factors The APT allows for specific stocks to be mispriced, and hence only refers to investments that are diversified Additionally, different variables may be used for multifactor models because the number of factors and individual factors are not known Despite not following any of the unrealistic CAPM expectations, the CAPM tends to gather attention because of its versatility and broad sector proxies Research has suggested alternate asset valuation mechanisms to the CAPM Research has often specifically criticized the CAPM assumption As a consequence, the APT is a financial asset model, which was given various macroeconomic elements for a suitable level when interpreting the shift of expected returns in some particular economy and at some specific point However, it is not the best result of the APT model, and is tougher

to decide which variables and what variables to pick into the model

2.1.2 The Fama French three-factor model

For scholastics through the 1990s, the capital asset pricing model (CAPM) as a model for acknowledging the pricing of companies in a sector – was essentially the biggest distraction around the local region Moreover, the CAPM was renowned for its expansive business acknowledgments Nonetheless, as was furthermore observed, the CAPM was absolutely not succeed as a historical asset pricing model, which further incited Eugene Fama and Kenneth French's confidence in a non-beta model as providing an increasingly clarification of the data Following the footsteps of William Sharpe, an analysis was found out which had a major effect on how the CAPM model was designed and created Their analysis is focused on a model that integrates all the variables that usually influence the predicted return, including company scale, financial leverage, E/P ratio, BE/ME ratio, and stock beta They conclude that the association between beta and standard deviation does not justify average stock returns since the 1960s through the 1980s They decided that this model would kick off a great hunt for factors that can help justify stock returns than that of the single variable, the sector β implemented in the Sharpe (1964), Lintner (1965), and Black (1972) asset-pricing model Others also studied the average stock returns with respect to scale, book-to-market ratio (value), and market premium They have found that these variables are very relevant and have stronger signals The firm scale and book-to-market ratio are outlined in the paper since they are related to equity returns The rest element (P/E and financial leverage) are blurred by placing these variables into the formula

Continuing with this analysis, Fama and French (1993) perform a review on two forms

of stock: stocks with limited capital market value and stocks with broad capital market value (also called valuable stocks) When the size factor and value factor were used in the regression model before including beta, the findings showed that the size factor and value factor had a greater influence on market price movements than did the beta

factor According to the reports, Fama and French had applied two variables, scale and meaning, to the model to represent the role of the factors in portfolios They say that the following regression model can describe equity prices

( )

(2)

Where:

is the expected return of asset i at time t

is the risk-free interest rate of government bonds

is the excess market return

(Small minus Big) the size risk factor

(High minus Low) the value risk factor

The coefficients , 𝑠 , and are the asset’s sensibility

is the constants intercept

is the error term at time 𝑡

The Fama French model illustrates how citizens who take greater chances earn greater returns In this analysis, the variables SMB and HML have an effect on the

profitability of a portfolio i Portfolio i is composed of stocks that have strong growth potential and low risk Portfolio i includes valuable stocks with high and growth stocks with low Besides, portfolio involves what relates to the financial sector in addition to what happens in the equity market

This model appeared to fit well in summarizing the findings of previous study studies, including analyses of well-known research studies CAPM Other than being checked, observational data were collected from various playing fields in South Africa, India, Ukraine and Taiwan Following the Fama French three-factor, the rate of return in the portfolio has proved to be consistent However, some researchers simply believed these three variables could not strictly decide the systematic risk premiums and did not expect there might be other factors

impacting profitability Novy-Marx (2013) found that improved gross profitability clarified the difference in stock returns rather than the book-to-market ratio Hou

et al (2015) observed that investment and return levels clarified variance in stock results

2.1.3 Carhart four factor model

Nartea et al (2009) analyzed markets and noticed that the Carhart four-factor model largely clarified momentum returns, but the Fama–French model didn't Centered on the Fama-French three factor model, this model introduces a new factor: momentum Carhart expands the Fama-French three factor concept by adding the momentum factor

in the combination The momentum factor is described as the difference between the return on winners' portfolio (the stocks which performed best in the last 3 -12 months) and the return on losers' portfolio (the stocks which performed worst in the last 3 -12 months) According to the analysis of Jegadeesh and Titman (2001), they noticed that purchasing stock that was doing well and selling stock that were doing poorly in the previous 3 to 12 months would improve your overall earnings This case is seen because you have a limited time to determine what stocks you would like to purchase The explanation is that being the case, the economy still self-corrects Some buyers prefer to cash out their gains and sell their stocks so that they can get a cheaper deal Another hypothesis suggested that after a significant increase in valuation, a stock was beyond its true value and would soon revert to it Therefore, Carhart (1997) changes the Fama and French model by introducing a fourth element: anomaly, which is described as the difference between the returns on one-year winners and losers 'Robust minus Weakness' (RMW) The WML factor is measured in the same way as the HML factor except that the second type is done on stock results from the previous year instead of from the current year (excluding the last month, t-1) The explanation behind the B/M or momentum breakpoints emerging from a universe of large capitalization firms is such that small capitalization stocks don't show the same traits

as large capitalization firms The outcome was of a rough formula

𝑟 𝑟 (𝑟 𝑟 ) (3)

Where:

𝑟 is the expected return on asset i

𝑟 is the risk-free interest rate of government bond

𝑟 𝑟 the excess market return

(Small minus Big) the size risk factor

(High minus Low) the value risk factor

(Winner minus Loser) the momentum risk factor

The coefficients , is the asset’s sensibility

is the constants intercept

the error term of asset i at time t

Since then, the four-factor approach has been implemented to a range of established economies like the United States, Europe, Southeast Europe and several others The model has been found to suit the data better than a three-factor model In comparison, Wei Zhang (2018) updated the Carhart four-factor model, and pointed out that reversal effects cannot be explained by the Fama-French three-factor except for Carhart's, their findings were better explaining on the relation between Chinese stock returns and their historical results, and provide alternative investment strategies for investors The French and Fama (2014) model also combines the five elements

2.1.4 The Fama French five factor model

∑

𝑟

Where:

is the share price at time t

E(dt+τ) is the expected dividend per share in period t+τ

r is (approximately) the long-term average expected stock return (the internal

rate of return on expected dividends)

Miller & Modigliani (1961) suggest the overall market valuation of the firm's portfolio at time t by (4)

, is total equity earnings for period 𝑡

the change in total book equity Dividing by the time t book equity gives:

a 5-factor model, which is likely to become the current benchmark for asset pricing studies:

𝑟 𝑟 (𝑟 𝑟 ) 𝑠 𝑟

(4)

Where:

𝑟 is the expected return on porfolio i for period t

𝑟 is the risk-free interest rate of government bonds for period t

𝑟 𝑟 is the excess market return for period t

(Small minus Big) the size risk factor

(High minus Low) the value risk factor

(Robust minus Weak) the profitability risk factor

(Conservative minus Aggressive) the investment risk factor

The coefficients 𝑠 𝑟 are the portfolio’s sensibility

is the constants intercept

is the error term of asset i at time t

According to statistical model and paper published by Stephen Cochrane, expenditure factors and profitability factors are more susceptible to economic times than scale factors Thus, these considerations are very important in evaluating the asymmetrical actions of hedge fund strategies over the market cycle One of the key targets of many hedge fund strategies is to capture the risk premium correlated with market anomalies; such as where the typical small business outperforms the market This asset pricing paradigm has largely used industrialized world data and industry data from the United States In addition, Chan and Hamao (1991) also noticed that the value aspect of return has a strong position in understanding market portfolio returns of Japanese stocks (contradictory to the Fama and French (2010) findings) Vietnam stock market also lacks scientific research promoting the use of the five-factor model in asset price calculation, however, there are methodological and empirical evaluations supporting the use of the five-factor model over the three-factor model At the end of the forthcoming chapter, the methodology and findings from the four experiments will be addressed in greater depth

2.2 Previous researches

2.2.2 Previous researches from developed countries

 Research in US of Ferson & Harvey (1999)

This research is focused on describing unconditional mean returns, and several studies have studied the capacity to characterize average returns Autocorrelations of fund returns are normally poor approximately 0.1 for limited size portfolios, although some are statistically important The HML section does not give us the opportunity to measure estimated returns depending on different time horizons The regressions, the coefficients on HML become smaller and t-ratios irrelevant The business beta coefficient is typically higher where there is a fit The intercepts are usually much narrower while the model is also used In short, the regression intercepts are similar to zero for their three-factor construct The alphas are there, but they are often time-varying It says that the Fama-French three-factor model describes neither the returns

of this portfolio nor its Sharpe ratio Also a variant of the Fama French model which implements time-varying betas can be rejected

 Research in Japan of Daniel, Titman and Wei (2001)

The analytical study presented a statistically important association between the average excess returns and the ex-ante factor loading rankings The study revealed that Fama-French three-factor model over-predicts there be a considerable stock market returns link among factors This loss could conceivably come from a low variance HML beta Furthermore, the investigators have found that there is a monotonic ordering of ex ante HML factor and ex post factor loadings On the basis of their individual stock portfolio, there is a 0.586 contribution from the HML factor, with a t statistic of 14.14 According to the three-factor model, a zero intercept should be predicted According to the model, the expected slope is negative 20.205, with 1.80 standard errors from zero The gap between the two portfolio returns is too minimal, which calls for the Fama-French model to be dismissed

 Research in French of Souad Ajili (2002)

For all equity portfolios, Souad Ajili contrasted the Fama French three-factor model and the CAPM in the case of the French economy between July 1991 and June 2001 with the equal-weight returns of all the commodities, the value-weight returns of all the securities, the four indices CAC40, SBF80, SBF120 and SBF250, and considered CAPM not to be inferior The findings indicate that the Fama French three factor model is preferable in describing returns on common stock than CAPM At the conclusion of three-factor regressions, the typical is 0.905

 Research in US of Zhu (2016)

To fill the void, Zhu expanded the Fama French five factor model with SSAEPD (Standardized Standard Asymmetric Exponential Power Distribution) and GARCH-type volatility This study is to evaluate whether the factor model is greater than the initial Fama French 5-factor model We use US stocks data gathered from July 1963 to December 2013 (2015) Empirical evidence from the historical share prices indicate that the Fama French five variables have an impact on asset valuation and the cost assessment

 Research in Australia of Chiah and partners (2016)

This research used Fama-French portfolio of stocks for 31 years According to the proof, the scale, demand, rate of return, and profitability elements have a mutually

interdependent relationship with each other In general, in developing economies, the five-factor Fama French model gives a clearer description of returns than the three-factor Fama French model and the CAPM model

 Research in Japan of Keiichi Kubota and partner (2017)

For the long-run data for Japan, Keiichi Kubota and Hitoshi Takehara find that the market prices are well calibrated They oppose that the Fama and French five‐ factor model can't differentiate between Japanese data better than standard Specifically, the effects of experiments using the RMW (Robust–minus–Weak) and the CMA (Conservative–minus–Aggressive) factors of Fama French five-factor were not good explanatory variables when they were used for generalized GMM tests with the Hansen–Jagannathan distance scale It was concluded that three-factor model represents at the same strength as the five-factor model, and it was the best way to view the details The test figure of the four-factor model is strong at 9.989, which is an almost equal as that of the Capital Asset Pricing Model (CAPM) at 10.064 Despite the moderate performance of the four-factor and five-factor versions, the three-factor model performs higher than all of them

2.2.3 Previous researches in developing countries

 Research in European countries of Steven L, K Geert and Roberto (1999) This research explores the potential of beta and t factor by CAPM and Fama French three factor to clarify the return diversity in 12 European countries The authors rated accessible securities according to their betas The analysis shows that the lowest asset allocation investments produce the best potential returns Results revealed that the chosen beta portfolios were actually growing return portfolios (t=2.08 and t=2.58).Each portfolio size has a declining logarithmic trend Statistically, the small firm portfolio (ie, enterprisers) has a significant optimistic intercept 0.62% per month (t=3.43) Despite the point figures that indicate negligible amounts of the intercepts, the joint F-statistic of Gibbons et al (1989) firmly opposes the assumptions that the actual intercepts are equivalent to nil This is because the beta and size-sorted portfolios have a greater diversification than does the traditional nation portfolio by the

high .The return premium associated with size-based portfolios may be attributed to the similarity risk between portfolios of various sizes

 Research in China of Grace Xing Hu and partners (2018)

This analysis suggests the demand returns to firms' scale in China The point sample is from 1990 to 2016 In general, smaller businesses outperform bigger companies This essentially decreases the uncertainties by growing the variety of portfolios average returns of 1.23% To look for the Fama-French technique, SMB gains an economically high return of 0.61 per month, not just statistically important but also economically large.In comparison, stocks' average returns do not show consistent relationship with their B/M ratios.The HML factor returned an average monthly return of 0.23, which is above zero but not important There would be no relation between the demand parameter and premium in this situation SMB has consistent positive coefficient of Fama French cross-sectional experiments and association with the return

of the sector Among three variables, SMB is the most significant for catching sectional fluctuations in Chinese stock returns Both studies suggest that the variations

cross-in returns are largely cross-induced by elevated uncertacross-inty cross-in early years Their effect would become much lower as you impose the correction on data that have been gathered for a long time

 Research in India of Harshita and partners (2015)

The analysis of data on the CNX500 over fifteen years is provided Results indicate that Indian equity market has a favorable relationship between market capitalizations and returns, profitability and returns, and B/M ratio and returns The Fama and French (1993) three factor asset pricing model (CAPM) is best for one portfolio, whereas the Fama and French (2015) five factor model is better for multiple portfolios This model provides the maximum results when there is no element in the portfolio For assets investing, the five factor approach is preferable

 Research in Turkey of Songul Kakilli Acaravci and partner (2017)

This research checked the validity of the five factor model by implementing it in Borsa Istanbul (BIST) during the 132-month period between July 2005 and June 2016 These

14 intersection portfolios built on the basis of size, B/M ratio, profitability and valuation parameters have been used When the GRS-F test is performed, the null ( )

is acknowledged Therefore, it is assumed that the consumption model is right The five-factor approach seems true for the BIST as well In addition, it tends to influence fund efficiency dramatically Once average is examined, mean average value in this model is 0.33 This gives help to the nature of Fama French five-factor model describing excess portfolio returns

2.2.4 Previous research in Vietnam

 Research of Truong Dong Loc and Duong Thi Hoang Trang (2014)

This research offers analytical data of extending the Fama-French three factor model

to the HOSE stock market The numbers came from January 2006 to December 2012 The findings indicate that the profitability of listed firms on HOSE is positively correlated with the risk of the sector, size of companies and B/M ratio The data reveals that in the six portfolio, the business conditions have a major influence on profitability of all portfolios.The size factor is favorably linked with the profitability

of small-size companies (S), but negatively linked with the rate of return of large-size companies (B) Finally, the HML is only positively associated with high (H) and medium (M) B/M ratio portfolios but negatively correlated with low (L) B/M ratio portfolios We may confirm that Fama-French three-factor model is suitable in explaining the change in profitability reported on the HOSE indices

 Research of Vo Hong Duc và Mai Duy Tan (2014)

Fama French three-factor and Fama French five-factor model where evaluated in this report The data used in the project is focused on 281 companies published on the Ho Chi Minh City Stock Exchange from January 2007 to December 2015 Regarding the three factor model, the factor has the most consistent impact on such factor The following variables, all of which are relevant in the estimation model but add to reserve the model The model describes that the demand factor still bears positive anticipation and original negative as well as statistically meaningful and accurate The size factor is optimistic and the importance factor is statistically significant Aside from profitability, the positive element in expenditure is profitability In conclusion,

Fama French five-factor isn't sufficient to clarify return outcomes for Vietnam stock market

 Research of Nguyen Thi Thuy Nhi (2016)

This research is primarily focused on two versions of variables and factors of the Fama French model and the four-factor model by Hou (Q-factor model) This paper uses data collected from two stock markets in HOSE and HNX over the period from January 2009 to June 2015, as well as 3 strategies to divide portfolios As a consequence, the demand effect is positive, the SMB factor is positive with limited portfolio scale, the HML factor is negative with a large portfolio value, the RMW factor is positive with a high ROE, the CMA is positive with low OP of the regression model increased from 80% to 96% This paper utilizes the Fama French five-factor model to illustrate more than the Q four-factor model

 Research of Huynh Ngoc Minh Tram (2017)

Based on the analysis, the findings indicate that the SMB factor ( ) has multiplied importance of HML factor ( ) and the MRP market return factor ( ) sufficient to understand predicted return of stocks because of the coefficient estimates of factors which is statistically significant at the 5% Even, only the SMB factor and MRP factor are supposed to stay optimistic while the HML factor is almost negative This means that businesses that have a reduced scale or lower B/M ratio, they will still garner income All of the remaining RMW and CMA factors are not important Therefore, Fama French five-factor is not totally account the investment return in the Vietnam stock market There is a good association between equity price variability, market risk index and stock returns in Vietnam

2.3 Research gap

Research on asset pricing is comprehensive in the world Also, recent findings have provided other findings multiple study goals and implications worldwide on assets pricing and taking plenty more from this focus

For example, research in developing nations, they provide several different analytical observations with several different types of measuring: OLS, GRS, GMM, GARCH-

type Or re-process the data in different forms and shapes The researches had unfavorable findings with the influences of Ferson & Harvey (1999), Japan of Daniel, Titman, Wei (2001) and Keiichi Kubota and partner (2017) but they showed an understanding completely in accordance with the Fama French model According to research from Zhu, Souad Ajili, Chiah and collaborators, conducted on US, French and Australia find that their model worked better than that of Fama: APT, CAPM, Carhart model but Fama French model is outperformed them all

Centered on research of Steven L, K Geert and Roberto (1999), this research clearly confirms that by utilizing portfolio beta and size-sorted portfolios are more diversified than by high of the regressions

There are more experiments on measures such as Fama French three-factor than the five's There are several weekly, annual, and quarterly Fama French model that have not been measured Most variables are optimistic such as HML, Nguyen Thi Thuy Nhi (2016), but certain factors are not on the authority of Truong Dong Loc and Duong Thi Hoang Trang (2014) and Huynh Ngoc Minh Tram (2016) These results regarding Vietnamese companies make them fascinating country and subject of more studies

Conclusion of Chapter 2

Chapter 2 attempts to summarize recent research on asset pricing that applies to Fama French five-factor model Other variables include the three-factor built by Fama French, four-factor generated by Carhart, and five-factor created by Fama French The findings of this research are combined with those of previous reports Chapter continues with references to other works and fields that require more study

CHAPTER 3: DATA AND METHODOLOGY 3.1 Data construction and processing method

3.1.1 Data sources

This research is focused on industries dealing in HOSE and HNX The year spans the period from 2014-2019 The author is using quarterly data from January 2014 to December 2019 That is why only freshly listed manufacturing companies are chosen

to create this survey Many companies are omitted from the study, and this is attributed

to the bad results of financial operations and regulation After mulling through those parameters I eventually pick the top 100 firms scattered over the 6-year era

Trinh Minh Quang (2017) used a Thomson Reuters database These details on monitoring and independent variables are taken from various newspapers in Vietnam: Vietstock, Cafef, VnDirect, Sbv, these sources are incorporated in the annual reports

of the projects in Vietnam The aim of this analysis is to evaluate the Fama French five-factor model of stock return with listed industrial companies in Vietnam stock market

3.1.2 Data processing method

Step 1: Data collecting

The details on variables such as the outstanding bonds, properties, net profit after tax (quarter), closed-price of securities, book value (BE), market value (ME), the VN-index (day)and the yield on treasury bill is taken from the website of the State Bank of Vietnam

Step 2: Data processing

I use the database from phase 1 to measure the cost of return of each stock , the rate

of return of the market fund , the valuation quota – B/M ratio, the size quota – Size (ME.complete outstanding shares), the benefit quota – Net profit after tax OP, the investment pattern quota – Inv (The development of total asset), and the risk-free interest rate from Vietnam Treasury bill

Step 3: Dividing and building up portfolios

According to the 4 quotas, including scale, B/M ratio, OP, and Inv divided yield to 18 portfolios will be created, and the detailed information will be given in the following section

Step 4: Measuring five factors

Summarizing the five sample variables in Microsoft Excel, which reflect Small minus Big (SMB) - the difference between returns on small and big size stocks for period t, HML (High minus Low) – the difference between returns on high and low book-to-market ratio stocks for period t, RMW (Robust minus Weak) – the difference between returns on robust and weak profitability stocks for period t, CMA (Conservative minus Aggressive) –the difference between returns on conservative and aggressive investment for period t Calculate these variables, explain it statistically and look at the association between them Calculate these factors by utilizing regression methods to see the interaction between them

Step 5: Running the simulations, then doing the regression study

Sorting portfolios in Excel with Stata in order tomanage confusing of variables, return variance of explanatory variables, run regression models and verify the utility of these models for the business in question

Step 6: Analysis of research results and give conclusions

The findings suggest that the causes, in particular, affect rates of investment In this way, go into the mathematical research for regression and render the final decisions for the investors and business holders

3.1.3 Data analysis tool

Data is analyzed using Stata version 13 and regression results are generated Microsoft Office Excel is used to incorporate the sample results

is the expected return on porfolio i for period t

is the risk-free interest rate of government bonds for period t

is the excess market return for period t

: is the Small Minus Big cause on the quarter t that was added in the Fama

French (1993) The line reflects the gap in average return between the portfolio of small stocks and large stocks in the industry Portfolios are developed with market capitalization (a proxy for size) for financial statements prepared for the quarter ended

in t -1

: is the High Minus Low typical risk factor on the day t that was implemented by Fama and French (1993).It indicates the relative gap in the return between a portfolio investing in stocks with the maximum book-to-market ratio and a portfolio invested in stocks with the lowest book-to-market ratio Portfolios are shaped in a quarter t dependent on the ratios of inventory values to revenue for the fiscal quarter ending in t -1

: is the Robust Minus Weak Low typical risk factor on the day t that was

implemented by Fama and French (2015).It reflects the average gap in the industry between the top performing stocks and the worst performing stocks Portfolios are created every quarter t in each department in order to calculate profitability based on accounting results t -1

: is the Conservative Minus Aggressive typical risk factor on the day t that was implemented by Fama and French (2015).The gap of performance between the most cautious portfolio and the most bullish portfolio in the capital market.Portfolios are created in a quarter t dependent on the rise in net assets for the preceding fiscal quarter

t -1 divided by the total assets at the end of the last fiscal quarter t -1

3.2.2 Measurement of variables

The inquiry is pursued the Fama and French (1993, 2015) strategy of process and computation In the quarter of each year (quarter t), firms are sorted and allocated into portfolios dependent on four factors, which are market capitalization, book-to-market ratio of shares, profitability, and investment These are as follows:

Stock return : the average rate of return by days of quarter If is the ending price

of the stock at quarter 𝑡, then is the ending price of the stock at quarter t-1 if the stock's rate of return at quarter 𝑡 can be approximated as follows:

Risk-free rate of return (stands for “Market”): the principal interest rate 1-year term

of Treasury bill issued by the Reserve bank of Vietnam from January 2014 to

December 2019 This risk-free rate is equal to risk-free interest rate quarterly t divided

by 4 quarters

Market capitalization (stands for “Size”): the product of number of shares

outstanding and the market price per share, as on the last day of each quarter t:

=𝑠 𝑎𝑟 𝑝𝑟𝑖 × 𝑜𝑢𝑡𝑠𝑡𝑎 𝑖 𝑔 𝑠 𝑎𝑟 𝑠

Profitability (stands for “OP”): the return on equity (ROE), which is measured by

number of sales remaining after all operating expenses, interest, depreciation, taxes and preferred stock dividends has been deducted from a company's total revenue

𝑡 𝑖 𝑜

𝑜𝑜 𝑞𝑢𝑖𝑡

Investment (stands for “Inv”): using asset growth as a proxy for investment If the

total assets in quarter t and the total assets in quarter t-1, following Cooper et al

(2008), Fama and French (2008), Gray and Johnson (2011) and Fama and French (2014) Asset growth is defined as follows:

𝑜𝑡𝑎 𝑠𝑠 𝑡 𝑜𝑡𝑎 𝑠𝑠 𝑡

𝑜𝑡𝑎 𝑠𝑠 𝑡