Portfolio selection in Vietnamese security market:a multiple – objective optimization approach

[5] Mehdi Majafi, Farshid Asgari, “Using CANSLIM Analysis for Evaluating Stocks of the Companies Admitted in Tehran Stock Exchange”, Journal of American Science 2013. [6] Mark Saunders, [r]

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28 https://www.semanticscholar.org/paper/A-structured-approach-to-the-

evaluation-and-of-CASE-Blanc-Korn/43fc318bbfce41c287119fda8f23f88f9fb094d8

29.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4623860/

30 https://en.wikipedia.org/wiki/ISO/IEC_9

Portfolio selection in Vietnamese security market:a multiple – objective optimization approach

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Tô Thị Thuỳ Anh Phạm Anh Đức Class: AC2015D

Science advisor: Asso Prof Nguyễn Hải Thanh

1 THE NECESSITY OF TOPIC

Developing an optimal portfolio, maximizing expected return under given risk, has long been an active research topic among academicians and business practitioners for decades, specifically since the pioneering work of Markowitz in 1956 There have been researchers continuously taking part in investigating this topic since then

For very firstly, in Markowitz’s mean-variance model, estimating the pairwise correlations between all stocks are needed as input data to build up the optimal portfolio13 Therefore, between 1992 and 1993, a research on performance of portfolio selection in Hong Kong stock market was also done by some researchers: Kin Lam, Henry M.K Mok, Iris Cheung and H.C Yam14 Recently, in 2012, Colby Wright has 13 Nguyen Hai Thanh and Nguyen Van Dinh, Portfolio Optimization: Some Aspects of Modeling and

Computing

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already researched how to perform optimal portfolio problems by using mathematical programming in Excel15.

Hence, there are several reasons for researchers to keep going on digging deeply in this topic The most primary one is that this topic plays a very important part in helping practitioners run better in stock market Other motivation is that through investigating, researchers have a good chance to build up knowledge as well as the major in university Therefore, researchers are able to build up knowledge in relevant fields

In short, with all the above reason, we have chosen the scientific researching topic, which is expected to contribute to other following researches in other markets: “Portfolio seclection in Vietnamese security market: A multiple-objetive optimization approach”.Method contributes to increase the accuracy in forecasting investment with the effort of saving unexpected costs

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CHAPTER 1: GENERAL DOCUMENTATION AND THEORETICAL FUNDAMENTALS ABOUT EXISTING FORECASTING METHODS. 1.1 THEORETICAL FUNDAMENTALS

The combination of scientific methods and experience, the qualitative of investors, individuals involving in market in general and Vietnamese market in specific, is one of the important premises creating scientific forecasting or an artistic predict about the variability of investing objectives in future market

Overall, all investors have not evaluated one-sided about the growth or reduction of investing objectives in market in a specific condition that every other existing factors are constant Actually, investors generally focus on predict the variability of investing objectives based on dependent variables, which are interdependent The most common interdependent variables are expected return and risk16 However, in practice, almost portfolio selection methods consider the comparison between two objectives Specifically, methods have to continuously repeat regarding to the random pairs of market’s objects

Results of forecasting portfolio selection are not totally accurate Even though predicting methods are carefully processed, it still has errors, which is dependent on the actual variability in the future Hence, it is seldom to have an extremely accurate method, compared to actuality Nevertheless, portfolio selection optimization still is one of premising conditions, directly affecting the process and results of investment

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1.2 RESEARCH METHOD 1.2.1 Qualitative method

Consult the majority advices of investors and potential investors.

Personal ideas of investors’ majority are consulted and gathered This represents the market’s investing demand The advantage of this method is that it can catch the majority of expectation of demanding source, then, stimulating investors attending the market The drawback of method, however, is that investors are directly affected by the market’s variability, so they usually underestimate to reduce risk This method is suitable for initial published

Consult financial advisors.

Each advisor gives independent predict, then, the average predict is calculated; or a group of advisors discuss and lead to an advice This method quickly gives out the predict data, collect a number of objective idea, eliminate relatively subjective ideas The disadvantage is that the classification of objects is not really clear

1.2.2 Quantitative method.

“Modern Portfolio Selection” was primarily called Mean-Variance Analysis Expected return of portfolio is calculated along with risks represented by standard deviation and the interaction among securities (covariance and correlation) Then, “Portfolio Diversification” was formed Almost important premises of investors are based on two variables: Expected return and risk17.

E(r )=∑

i=1 n

Pᵢ R ᵢ

σ2

=∑

i=1 n

(Rᵢ−E (r))Pᵢ

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1.3 GENERAL DOCUMENTATION ABOUT OPTIMIZING MULTIPLE OBJECTIVES–PORTFOLIO SELECTION.

Optimizing multiple objectives-portfolio selection is affected by some factors Indeed, the interaction between Expected return and Risk is the most important

Nowadays, in Vietnamese market, predicting optimal portfolio selection has not concentrated on cases of 3-4 objects When investors bring out plans, they often combine historical data and financial advisors’ experience for 1-2 objects Therefore, it is essential to build up an arithmetic and statistical model18.

Optimizing multiple objectives-portfolio selection is not able to avoid general characteristics of forecast Although we not expect predict perfectly accurate, we desire errors among predict data not too large Model still gives investor confidence to make investing decisions

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CHAPTER 2: THEORETICAL FRAME WORK AND APPLICATION PROCESS

2.1 INVESTIGATING CASE

“Researching Strategy, including an actual experiment about a specific object at present context by using diversifying evidence sources, is called investigating case.”19

Investigating case is applied for predicting optimal portfolio selection for two objectives including the four target securities (as decision variables) ACB, FLC, FPT and AAA20 in Vietnamese economy 2017-2018 Forecast is conducted in Vietnamese security market generating premise to develop better model in other markets

2.2 DESIGN RESEARCH CASE The aim of research case

Analyze predicting process and clarify characteristics of forecasting optimal multiple objectives portfolio selection along with affected factors

Choosing research method

Mixed strategy is chosen to be researching method because it has the combination between collecting data method, and quatitatively and qualitatively analyzing method

Duration of research

There is a limitation in researching duration However, there still exists the length of time factors Then, the development and the variability of objectives through periods are obvious

19Mark Saunders, Philip Lewis & Adrian Thornhill.2010, “Phuong phap nghien cuu kinh doanh”, Translator Nguyen Van Dung, Finance Publisher, page 156

20ACB: Asia Commercial Joint Stock Bank FLC: Finace, Land & Commerce Group

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2.3 APPLICATION PROCESS.

Part 1: Choose samples for portfolio selection using CAN SLIM method to find out security desired to invest21.

C-current quarterly earnings per share

A-Annual earnings increases over the last five year N-new products, management, and other new event S-Small supply and large demand

L- Choose leaders over laggard stocks within the same industry

I-Pick stocks who have institutional sponsorship by a few institutions with recent above average performance

M- Determining market direction by reviewing market averages daily Part 2: Develop optimal portfolio selection for two objectives.

Step 1: Using formula of Log return to compute continuously compounded interest

over periods based on data collected (Return)22. r=ln ⁡(FV PV)

Step 2: Compute Excess return, Expected return and Standard Deviation.

1 Excess Return of Security of time t = Return of time t – Average Log Return of Security

2 Return = Average Log Return of Security

3 Standard Deviation (Using STDEV.P function in excel)

Step 3: Covariance Matrix23.

Σ=1/n(XTX) Nis the number of scores in each set of data X is excess return

XTis the transpose of X

Cov(X, Y) = Σ ( Xi - X ) ( Yi - Y ) / N = Σ xiyi / N

21A system for selecting stocks, created by Investor's Business Daily founder William J O'Neil

Mehdi Majafi, Farshid Asgari,“Using CANSLIM Analysis for Evaluating Stocks of the Companies Admitted in Tehran Stock Exchange”, Journal of American Science 2013

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N is the number of scores in each set of data X is the mean of the N scores in the first data set

Xi is the ith raw score in the first set of scores

xi is the ith deviation score in the first set of scores

Y is the mean of the N scores in the second data set

Yi is the ith raw score in the second set of scores

yi is the ith deviation score in the second set of scores

Cov(X, Y) is the covariance of corresponding scores in the two sets of data

Step 4: Compare Expected Return and Standard Deviation based on Sharp rate Sharp

Rate = Expected Return / Standard Deviation24.

Step 5: Compute Expected return and Standard Deviation based on Weight of

objectives, then, compute new Sharp rate25.

Step 6: Using Excel Solver to compute weights in case Mean and Sharp rate are

maximized and Standard Deviation is minimized26.

The weights already had found out is an optimal portfolio

CHAPTER 3: COLLECTING AND PROCESSING DATA 3.1 COLLECTING DATA

3.1.1, C (Current quarterly earnings per share)27

We can see that almost stocks have EPS increase at least 29% from the same quarter’s earnings reported in the prior year

3.1.2, A (Annual earning over last five years– from 1/1 to 31/12 each year )28

24, 18, 19 Portfolio Optimization in Excel - Colby Wright Published on Jan 11, 2012 on youtube.com

25 26

2720, 21 Information on finance.vietstock.vn

28

2015 2016 2017

ACB 1,145 1,483 2,148

FLC 1,952 1,795 599

FPT 5,209 4,643 5,908

AAA 962 2,792 3,767

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ACB:

In 2016 Income before tax were VND 1.667 billions, increased 27% from 2015 During 2016, net income raised 17% Service revenue also increased 27% almost focus on personal customer and financial service, while reduced risk in credit Almost expenses were used for improving information technology, maintaining branding system however always controlled closely

In balance sheet, total asset, debit balance increased 16% and 21%

FLC:

In 2016, Sales return increased 0.78%, income before tax and profit after tax decreased 1.72% and 0.72%

FPT:

Profit after tax in Audit Separate Financial Statement of 2017 reached VND 2.987 billions, increase 161% compared with 2016 thanks to gain on the divestment of two companies: FPT Digital Retail Join Stock Company and FPT Trading company Limited

Year ACB FLC FPT AAA

2012 737534000000 4829775185 1717468517764 43575265498 2013 825596000000 80225652012 1016245622188 43810669080 2014 922249000000 267118206298 1782280958870 36270141145 2015 1012086000000 934114153469 1777106882168 54758545610

Object 74

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Profit after tax in Audited Consolidated Financial Statement of 2017 reached VND 3.528 billions, increased 37% compared with 2016 thanks to good performance of its business lines and gain divestment of two companies FPT Digital Retail Join Stock Company and FPT Trading Company Limited

AAA:

Profit after tax increased 92% compared with 2016 thanks to good performance of new factory, factory and and gain divestment of VBC and Yen Bai plastic and mineral corporation

3.1.3, N (New product, management and other new event)

ACB:

+ Privilege Banking Project: Project is holding the lines of supplying products, services and/or activities suitable to privileged customer segment to keep contact with customer

+ Transaction Banking Project: To raise non-term deposits, increasing non-credit income collected from services fee, developing outstanding loan balance of individual customers and SMEs by sponsoring distributors

+ Developing business procedure ACMS

We can see that ACB is focusing on improving banking services and customer services more than credit

FLC:

+ Continuing raise resources so as to exploit some real estate project such as FLC Ha Long Bay Golf & Luxury Resort, Quang Binh Beach & Golf Resort

+ Carrying out some real estate home : FLC Twins Tower, Star Tower, Garden City, Eco-house Long Bien

+ Developing some potential field such as agriculture, industry

+Participating in social activities in order to improve corporation’s fame

FPT:

+ Promoting global development

+ Be a global partner of famous corporation in the world + Expanding customer list in Forbes 500

+ Improving international competing capability

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+Intensifying management, supervise manufacturing in order to raise worker’s responsibility in each position, purpose is ensure safety, quality and saving for company

+ Operating factories, Factory and +Building Factory

+ Raising market share in Japanese, Australia, America market 3.1.4, S (Supply and Demand)29

In our opinion, we choose stock in which Supply and Demand increase at least 50% because it shows that they have possibilityof increasing in price

3.1.5, L (lead)30

We choose stock which will take the lead in stock market in future 3.1.6, I (investor)31

ACB:

1, Standard Chartered APR Ltd 2, Connaught Investors Ltd

3, Dragon Financial Holdings Limited 29, 24 Information on finance.vietstock.vn

3023Mehdi Majafi, Farshid Asgari, “Using CANSLIM Analysis for Evaluating Stocks of the Companies

Admitted in Tehran Stock Exchange” Journal of American Science 2013 31

unit : stoc

k

FPT AAA

Deman supply Deman supply

201

2 74,064,560 71,017,490 90,861,800 87,413,200 201

3 128,999,220 121,215,670 133,860,700 139,396,700 201

4 427,971,320 454,171,030 187,557,300 194,206,500 201

unit : stoc

k

ACB FLC

Deman supply Deman supply

201

2 209,782,600 220,178,700 210,391,100 196,742,000 201

3 163,111,900 155,412,500 1,338,736,620 1,332,745,380 201

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4, Standard Chartered Bank (Hong Kong) Ltd

FPT:

Although they don’t have big investor however they have many partner such as Microsoft, Amazon Web Service,

AAA:

Almost their partner is distribution channels both domestic and foreign 3.1.7, M (market orientation)32

At the end of 2016 many professor consider that VN-Index will fluctuate at 800 point, even the others see that it will reach 850 point According to Sate Security Commission of Vietnam’s data, in December 19,2017 ,VN-Index reached 951.42 point, increase 43% compared with 2016

HNX-Index reached 111,61point raised 41.5% compared with 2016

In 2017, many famous company and banking jointed in stock market and helped expand Vietnamese stock market in size In December 19, Capital stock reached 3.360 billion Vietnam dong, increased in 73% compared with 2016 equal to 74.6% GDP About transaction, the value of transaction was 13.870 billion Vietnam dong in which stock reached 4.981 billion Vietnam dong increase 63%

Beside that in 2017, business result in many corporation have many positive signal especially banking, real estate, technologies and environmental protection product According to market movement, we believe that 2018 will be a successful year of Vietnamese stock market

3.2 Data processing and outcome analysis. 1 Mathematical model

For the sake of simplify maths to jude and comments about portfolios selection actions It’s necessary to have some conventions about relative variables and to make clear for some mathematics symbols33:

Ri = (R1, R2, R3, …, Rn) (matrix of n x return variables) W = (w1, w2, w3, …, wn) (matrix of n x weights of portfolios) μ = (μ1, μ2, μ3, …, μn) (matrix of n x portfolios’s expected return)

32 Information on finance.vietstock.vn

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μp = W1μ1 + W2μ2 +W3μ3 + …+Wnμn = WTμ (expected return corresponding to n weights)

σ = (σ1,σ2,σ3, …,σn) (matrix of n x variances)

σp = √WTΣW (variance corresponding to n weights)

(variance, co-variance matrix)

D= σσT(the matrix of paired products of the standard deviations)

D= [

σ1σ1 σ1σ2 σ2σ1 σ2σ2…

σ1σn σ2σn ⋮ ⋮ ⋱ ⋮ σnσ1 σnσ2… σnσn] C= Σ/D (correlation matrix) Objectives and their constrains:

1 Minimize the risk (with μp max) W1+ W2+ W3+ …+Wn=

σp ≤ β (β is σn min) W1, W2, W3, …, Wn ≥

2 Maximize rate of return (with σp min) W1+ W2+ W3+ … +Wn=

μp ≥ α (α is µn max) W1, W2, W3, …, Wn ≥

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W1+ W2+ W3+ …+Wn= W1, W2, W3, …, Wn ≥ 2 Data processing

With all the data had collected above has been shown in quarterly EPS table.Its starts in the first quarter of 2013 and ends in the third quarter of 2017 Thus we have 19 numerical data for each portfolio(ACB, FLC, FPT, AAA)3435

Furthermore, for the sake of computing compound interest rate, we can not computing return in the first quarter in 2013 due to missing variable in formula of continuously compound interest Its can not measures rate of return in the first quarter

of 2013 unless we have data of the fourth quarter of 2012 To sum up, we are going have 18 returns from the second quarter of 2013 to third quarter of 2017 (n= 18)

Quarterly rate of return table is the result of the first step of data processing, every number represent return in each quarter They could compute through this formula:

R = FVPV (36) Where:

R: rate of return FV: future value PS: present value

Rate of return in each quarter have been distributed to expected return (μ) and variance for each (σ) variable Result in table 3.2b Despite the expected return and variance, 34 ACB: Asia Commercial Joint Stock Bank

FLC: Finace, Land & Commerce Group

FPT: The Corporation for Financing and Promoting Technology AAA: An Phat Green Plastic and Environment Joint Stock Company 35 Information on Finance.vietstock.vn

36Financial mathematics for actuaries, Mc Graw Hill Education (Asia) Wai-Sum Chan, Yiu – Kuen Tse (2013)

Date ACB FLC FPT AAA

Q1/20

13 430 489 5,689 3,841

Q2/20

13 39 661 5,801 3,438

Q3/20

13 1,022 990 5,765 3,111 Q4/20

13 878 1,250 5,849 2,775 Q1/20

14 818 1,443 5,901 2,646 Q2/20

14 726 1,873 5,495 2,755 Q3/20

14 581 1,620 5,379 2,915 Q4/20

14 1,015 1,402 5,024 1,898 Q1/20

15 1,048 1,310 4,919 1,581 Q2/20

15 1,012 1,380 4,816 1,095 Q3/20

15 1,033 1,540 4,642 1,073 Q4/20

15 1,099 1,733 5,032 1,124 Q1/20

16 1,130 1,649 4,663 1,684 Q2/20

16 1,197 2,032 3,660 2,164 Q3/20

16 1,250 1,659 3,711 2,404 Q4/20

16 1,483 1,527 3,459 2,736 Q1/20

17 1,626 1,581 3,605 3,208 Q2/20

17 1,747 885 4,449 3,265 Q3/20

17 1,927 885 4,093 3,379 Quarterly EPS of portfolios table

RACB RFLC RFPT RAAA

-2.4002

24 0.301391 0.019496

-0.110 84 3.2659 551 0.403 951 -0.006 23 -0.099 95 -0.1518

7 0.233194 0.014466

-0.114 29

-0.0707

84 0.143581 0.008851

-0.047

-0.1193

12 0.260817

-0.071

28 0.040368 -0.2227 99 -0.145 12 -0.021

34 0.056452 0.5578

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there is a third measure to helps better judements toporfolios and better helps investing decisions, it’s the revert of coefficient of variance (sharp rate - μ/σ)

Sharp rate measures return in a unit of risk

The next step to compute variance and covariance matrix Its helpful in mathematics when its necessary to measure means and variances of weights On the other hands, the matrix itself can not be uses to make

some judement activities Thus to make things clearly, correlation matrix is useful

.C= Σ/D = σxy/σxσy Where:

C:

correlation matrix Σ: variance- covariance matrix

D: the matrix of paired products of the standard deviations 3 Analysis outcome

All the objectives above had been simplified by setting all weights to be positive This constrain had limited another application of this method to measure short sale Though this is not affected to the first purpose of the team (application of maxi-mizing

Expected returns, Standard deviations and sharpe rate of portfolios

Var-cov matrix

ACB FLC FPT AAA

AC

B 0.931704 0.020904

-0.00443 -0.01136 FL

C 0.020904 0.049149

-0.00807 -0.00258 Correlation matrix C=Σ

/D ACB FLC FPT AAA

ACB 0.097685

-0.0528 126 -0.0607 137

FLC 0.097685

1 -0.4187 912 -0.0602 073 FPT -0.0528 126 -0.4187 912 -0.1856 041 AAA -0.0607 137 -0.0602 073 -0.1856 041 Σ=1/n(XTX)

Where:

Σ: variance- covariance matrix

n: is number of samples taken

X: excess return

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portfolios selections in Vietnam’s stock market), cause Vietnam government does not allowing to short sale at this time of stock market (4/2018) However, the application to other market that has alowed short sale is still possible Thus, short sale will not be mentioned in this report cause our team want to focus to Vietnam’s stock market

Unfortunately, the result in correlation matrix let us know there is no correlation between four of our port-folios Obviously when all of portfolios have corre-lation measures are negative or very close to zero, this means these four portforlios are independence from each other business Maybe, in the greater of scale, they have related or in another words this interpretation of nearest four years that they are independence

As the result of method had mentioned above, optimization selections table gives us very specific number to jude or study.Base on the result, the first comment should be on the high level of risk that four fortfolios are giving us Even with very

low rate of return (0.6647%), the risk is too high (8.6970%) This means four companies rate of returns were not stable in the past years Although with the highest

Portfolios Equal

weight Max returnratio St.devMin Max sharperatio constraining

variable None at σ<= at μ = None

value of

constraint N/a 8.697% 8.333% N/a

Portfolio weights

ACB 25.00% 3.01% 100.00% 10.52%

FLC 25.00% 39.37% 0.00% 89.48%

FPT 25.00% 42.35% 0.00% 0.00%

AAA 25.00% 15.28% 0.00% 0.00%

Σwi

100.00

% 100.00% 100.00% 100.00% μp

2.2719

% 0.6647% 8.3330% 3.8258% σp

25.1081

% 8.6970% 96.5248% 23.1525% Correlation matrix

C=Σ/D ACB FLC FPT AAA

ACB 1.00 0.10 -0.05 -0.06 FLC 0.10 1.00 -0.42 -0.06 FPT -0.05 -0.42 1.00 -0.19 AAA -0.06 -0.06 -0.19 1.00

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rate of return (8.33%), the investor has stills suffer the risk of 96.52% Despite all of that, this method still provides us another way to measure both risk and return rate through sharp rate (transpose of coefficient of variation), its shows that FLC and ACB is a safe choice to investment with weights at 89.48% and 10.52% respectively

CONCLUSION

Our research has clarified the factors affecting optimal portfolio selection forecast for objectives We have applied existing models, using data as an input tool to process the forecast Forecasting model brings out classified data for each objectives based on hypothesis’ conditions and the interdependence of four target securities Based on the research, further development and improvement of the optimal portfolio selection model may be made in the future

Academic contribution

Codifying and developing theory about building optimal portfolio selection model37 for four target securities in Vietnamese security market, which may lead to the development of a similar model for other securities in Vietnamese markets as well as foreign markets Moreover, model may be applied for other markets in a similar process including the case of Short sale, an uncommon case in Vietnam

Collecting data following CAN SLIM method38 to find out four target securities desired for portfolio selection, then, building the forecast following covariance matrix to figure out the forecasting results

Practical contributions

Regarding the aim of clarifying factors that have impacts on forecasting process of optimal portfolio selection for two objectives, disadvantages ofthe existing models have been found out

Hence, developing a forecasting model for multiple objective optimization based portfolio selection is necessary The new one has been developed based on existing models, actual data’s survey and analysis Within the new model, mathematic calculation and computer software are used

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Nevertheless, the optimal multiple objectives portfolio selection still has some drawbacks:

- Data collected is chosen following some criteria

- Collecting data is disvantageous if collectors not have information resources from company issuing securities

Next research proposal

Optimizing portfolio selection based on the multiple – objective optimization approach has not progressed in case of short sale because Vietnamese market’s conditions not allow To solve above disavantages, we would like to further develop the model for foreign security markets, continuing collecting data, studying and experimenting in foreign markets

REFERENCES

[1] Colby Wright, Portfolio Optimization in Excel, published on Jan 11, 2012 on

youtube.com https://www.youtube.com/results?

search_query=colby+wright+portfolio+optimization <access date: 20/9/2017 at 9h30>

[2] Colby Wright, Generating the Variance-Covariance Matrix published on May 31, 2012

https://www.youtube.com/watch?v=ZfJW3ol2FbA <access date: 15/9/2017 at 10h30>

[3] Kin Lam, Henry M.K Mok, Iris Cheung and H.C Yam, Family groupings on performance of portfolio selection in the Hong Kong stock market, published on September 1994

[4] Lawrence J Gitman, Chad J Zutter, Principles of managerial finance 14th edition, published January 2014

[5] Mehdi Majafi, Farshid Asgari, “Using CANSLIM Analysis for Evaluating Stocks of the Companies Admitted in Tehran Stock Exchange”, Journal of American Science 2013

[6] Mark Saunders, Phillip Lewis & Adrian Thornhill 2010, “Phương pháp nghiên cứu kinh doanh” Dịch giả Nguyễn Văn Dung, NXB Tài Chính, trang 156

[7] Nguyen Hai Thanh*, Nguyen Van Dinh(28th June, 2017).Portfolio Selection: Some Aspects of Modeling and Computing By In VNU journal of science publish

[8] Wai-Sum Chan, Yiu – Kuen Tse (2013),Financial mathematics for actuaries, Mc Graw Hill Education (Asia)

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[2] AAA: Vietstock Electronic Magazine,Bao cao thuong nien

http://static2.vietstock.vn/vietstock/2017/13/20170213_20170213%20-%20AAA%20-20%20Bao%20thuong%20nien@202016.pdf

[3]ACB: http://cafef.vn/thi-truong-chung-khoan/co-phieu-dang-chu-y-ngay-27-5-tsc-tang-het-bien-do-acb-dan-dau-da-tang-nhom-ngan-hang-20150527174755652.chn

[4] FPT: http://cophieuvietnam.com/trien-vong-fpt-ky-vong-tang-truong-manh-vien-thong-va-phan-mem-trong-2017/

[5] FLC: http://flc.vn/tin-tuc/tin-flc-group/flc-thong-qua-ke-hoach-loi-nhuan-1230-ty-dong-nam-2017//

[8]http://www.dcfnerds.com/94/arithmetic-vs-logarithmic-rates-of-return/

APPENDICES

[1] “Modern portfolio theory helps investors control the amount of investments such as stocks and shows that certain weighted combinations of investments offer both lower expected risk and higher expected return than other combinations”

(Nguyen Hai Thanh, Nguyen Van Dinh, Portfolio optimization: some aspects of modeling and computing, VNU journal of science, published 28 June 2017)

[2] “In fact, technical analysis is regarded as complement of fundamental analysis Therefore, we need a method which is combination of both methods On this basis, a method has been used which contributes to our need for removing defects of fundamental and technical analyses This method which is called CANSLIM is regarded as method which is combination of both fundamental and technical analyses today and has been considered in global market in recent years”

(Mehdi Majafi, Farshid Asgari,Using CANSLIM Analysis for Evaluating Stocks of the Companies Admitted in Tehran Stock Exchange On Journal of American Science 2013)

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analyzing Monte Carlo for evaluating research stages, they have concluded that one can achieve long-term strategy by combining moving average crossover strategy with CANSLIM method of William Oneil (Iavnov & Beyoglu, 2008)”

(Mehdi Majafi, Farshid Asgari,Using CANSLIM Analysis for Evaluating Stocks of the Companies Admitted in Tehran Stock Exchange, Journal of American Science 2013)

Modeling and simulation of

wireless communication networks of VNU-IS.

Group sciences: Trần Hoàng Anh Nguyễn Văn Sơn Nguyễn Văn Dũng Lê Tự Quốc Thắng Class: MIS2015A