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Af6301 | The Concept Of Assessment Answers

You are given a notional SGD 100,000 to invest on the Singapore stock market in shares selected from the list of shares in the FTSE ST ALL Share Index (listed on the SGX). You need to split your investment 50:50 between two portfolios of shares, one where you select the shares by technical analysis and the other by fundamental analysis. Your aim is to beat the market with both portfolios. It is important you can demonstrate that you know the difference between these methods. You need to compare and contrast the two portfolios and you need to make explicit reference to EMH in your analysis.

Answer:

Introduction:

The assessment aims in identifying the significance of technical and fundamental analysis by preparing two defence types of portfolios and analysing it in a period. This evaluation would eventually allow the investor to identify the instruments, which can be used for detecting investment opportunities. Moreover, for fundamental analysis we have used P/E ratio and P/BV ratio for detecting stock, whose have higher value in P/E ratio and less than 1 value of P/BV ratio. Furthermore, the technical analysis uses the simple moving averages for detecting the short-term trend in the stock and identifies the investment opportunities within the constituents of S&P Indices for Singapore. Adequate discussion of the EMH and behavioural financial are also conducted for identifying the investors mind set during the evaluation period. The result analysis section depicts the overall performance of the two created portfolio and depicted, whether they beat the market or not.

Literature Review:

The concept of EMH and Behavioural finance depicts the mindset of investors, while conducting investment decisions. The efficient market hypothesis is mainly segregated in three different levels, which are Strong form, Semi-strong form, and weak form of Efficient Market Hypothesis. The different level of efficient Market Hypothesis directly indicates the level of information, which is presented by the company to the investors. This transparency in the information sharing process directly helps in improving the level of decisions, which is made by the investors. Hence, with the strong form of efficient market hypothesis there is no possibility of investors making abnormal returns, as the market discounts the news adequately to portray the accurate share price of the stock. However, with the semi-strong and weak form of Efficient market hypothesis the information flow from the company to the investor is relevantly low, which increases the chance of some investors to make high end abnormal gains. The efficient market hypothesis directly increases the level price changes that will be conducted on a stock after evaluating the relevant news. On the contrary, Bartos (2015) argued that due the rigidity in the efficient market hypothesis the organisations and investors were not paying attention to the declining value of the housing market before the financial crisis of 2007. Hence, from the evaluation it could be indicated that with the presence of efficient market hypothesis the information flow about the stock is consistent, which helps in depicting the correct valuation of their share price.

The behavioural finance is the second concept, which is used by investors in making relevant decision for their investment. In addition, the behavioural finance is a study of psychology, which is used in making relevant decisions. The cognitive, emotional, cultural, and social factors are some emotions, which is faced by the investor while making relevant decisions. The different economic factors directly have impact on the investment decisions of organisations. The theory also depicts the participants in the economy behave rationally, where wealth maximisation is the only concept, which helps them improve the level of returns from investment. Furthermore, the psychology of investors directly depicts the level of investment, which they have conducted after evaluating the information. Hence, it could be detected that investors take irrational decisions during investment, as they are influenced by behavioural and psychological factors. In this context, Mouna and Jarboui (2015) stated that the panic attributes of an investor instigate the large fluctuations in share price of stock within a day, when financial position of the company declines. Therefore, the behavioural finance directly explains the anomalies, which exist in the real world and where conventional financial theories have no effect. The investors are keen on behaving differently to the same information that is been provided to them, which instigates different price movement for the stock. Hence, investors with the help of technical and fundamental analysis are able to gather relevant information regarding the current position of the stock, as it increases the probability of high returns from investment.

Rational and Methodology:

The rational and methodology used in the preparation of the portfolio directly helps in depicting the strategy, which has been used for selecting the stocks for investment purposes. Two portfolios have been created for investment purposes, which has used fundamental and technical methods in selecting the stocks. In this context, Dimpfl and Jank (2016) stated that investors with the help of technical analysis are able to detect trends of the stock, which help in pinpointing the stocks that could generate higher returns from investment. On the other hand, Arthur (2018) indicated that fundamental analysis is used for long-term investment purposes, as the investor banks on dividends and growth from their investments.

Moreover, the portfolio for fundamental analysis is created by using P/E ratio and P/B ratio. The stocks with higher P/E ratio are selected, where its P/B ratio needs to lower than 1, which mainly helps in detecting the level of returns that can be generated from investment. The fundamental analysis is used on the basis of long term principles, where the stocks selected for investment is aimed to generate higher returns from investment. The P/E ratio directly indicates that growth prospects on stock, which can be used by investor to increase their return from investment. Moreover, the P/B ratio is used for detecting price to book ratio, where the values lower than 1 indicates that companies shares are undervalued and can be used for investment purposes. Eiamkanitchat, Moontuy and Ramingwong (2017) stated that with the use of fundamental analysis tool investors are able to formulate a portfolio, which can boost the returns from investment.

In the similar context, technical analysis is used for selecting stocks that have short-term investment opportunities. Therefore, investors detecting short-term trend could eventually improve the level of income that can be generated from investment, while reducing the total risk from investment. The current portfolio is prepared by using moving averages of 10 days and 30 days for detecting the investment opportunity. The stocks are selected, when the moving average of 10 days crosses upwards from the moving average of 30 days. This process is used for detecting the investment opportunity in stocks and formulating the portfolio, which can generate higher returns from investment. In this context, Ewing and Malik (2016) stated that investors with the use of technical analysis is able to understand the risk and return attributes of a stock before making any kind of investment decisions.

Result and Analysis:

i. Fundamental Analysis portfolio:

Date Buy : 04/06/2018

S/N

Company Name

Code

Industry

P/E

P/BV

  

1

United Engineers Limited

U04

Diversified Real Estate Activities

30.35x

0.84x

-8.31%

Didn’t BEAT market

2

Sembcorp Industries Ltd

U96

Industrial Conglomerates

30.27x

0.71x

-5.52%

BEAT market

3

Keppel REIT

K71U

Office REITs

21.90x

0.82x

0.08%

BEAT market

4

Wheelock Properties (Singapore) Limited

M35

Real Estate Development

21.16x

0.85x

26.81%

BEAT market

5

OUE Limited

LJ3

Diversified Real Estate Activities

17.41x

0.36x

-4.38%

BEAT market

6

Singapore Airlines Limited

C6L

Airlines

16.46x

0.81x

-17.05%

Didn’t BEAT market

7

City Developments Limited

C09

Diversified Real Estate Activities

14.38x

0.83x

-19.07%

Didn’t BEAT market

8

Chip Eng Seng Corporation Ltd

C29

Construction and Engineering

11.28x

0.65x

-12.40%

Didn’t BEAT market

9

CapitaLand Limited

C31

Diversified Real Estate Activities

10.30x

0.74x

-5.29%

BEAT market

10

Sunningdale Tech Ltd

BHQ

Industrial Machinery

10.07x

0.70x

-0.91%

BEAT market

      

-8.33%

Didn’t BEAT market

 

FTSE

    

-6.49%

 


The above calculation depicts the returns, which has been provided from the fundamental analysis portfolio. The calculation directly indicates that the loses from the fundamental portfolio is at the levels of -8.33%, which is more than the loss depicted from the FTSE ST ALL index during the period of 04-June-2018 to 24-August-2018. The stock selection process used in the fundamental analysis was not accurate for short-term investment process, which can be seen from the losses incurred from investment. In addition, the decline in the current valuation system for fundamental analysis can be used for long-term investment situations. Moreover, from the listing of 10 stocks, only 4 of the stocks did not beat the market, where the market is considered the returns from FTSE ST ALL which is at the level so of -6.49%. Hence, the total fundamental portfolio was not able to beat the market, as the losses from investment inclined and crossed the threshold of -6.49% obtained by FTSE ST ALL. In this context, Fagereng, Gottlieb and Guiso (2017) stated that investors with long time investment horizon mainly uses the fundamental analysis approach, as in short duration the stock does not provide the required level of returns.

ii. Technical Analysis portfolio:

No

Company Name

Transaction

 Profit/loss

1

BOC Aviation Limited

Monday, June 4, 2018

 $ (24,567.37)

1

BOC Aviation Limited

Wednesday, July 4, 2018

 $ 14,195.00

1

BOC Aviation Limited

Wednesday, August 1, 2018

 $ (14,994.91)

1

BOC Aviation Limited

Friday, August 24, 2018

 $ 29,471.10

2

BW LPG Limited

Monday, June 4, 2018

 $ (17,715.74)

2

BW LPG Limited

Monday, July 2, 2018

 $ 16,621.26

2

BW LPG Limited

Friday, July 20, 2018

 $ (17,826.40)

2

BW LPG Limited

Monday, August 20, 2018

 $ 17,560.00

3

China Aviation Oil (Singapore) Corporation Ltd

Monday, June 4, 2018

 $ (821.62)

3

China Aviation Oil (Singapore) Corporation Ltd

Monday, June 18, 2018

 $ 770.00

3

China Aviation Oil (Singapore) Corporation Ltd

Wednesday, August 1, 2018

 $ (776.53)

3

China Aviation Oil (Singapore) Corporation Ltd

Friday, August 24, 2018

780

4

ComfortDelGro Corporation Limited

Monday, June 4, 2018

 $ (1,247.47)

4

ComfortDelGro Corporation Limited

Wednesday, June 20, 2018

 $ 1,155.00

4

ComfortDelGro Corporation Limited

Tuesday, July 17, 2018

 $ (1,182.34)

4

ComfortDelGro Corporation Limited

Monday, August 13, 2018

 $ 1,165.00

4

ComfortDelGro Corporation Limited

Friday, August 24, 2018

 $ 1,155.00

5

Genting Singapore Limited

Monday, June 4, 2018

 $ (641.26)

5

Genting Singapore Limited

Monday, June 18, 2018

 $ 605.00

5

Genting Singapore Limited

Thursday, July 19, 2018

 $ (641.26)

5

Genting Singapore Limited

Wednesday, August 8, 2018

 $ 550.00

5

Genting Singapore Limited

Friday, August 24, 2018

 $ 535.00

6

Mapletree North Asia Commercial Trust

Monday, June 4, 2018

 $ (597.34)

6

Mapletree North Asia Commercial Trust

Friday, June 22, 2018

 $ 561.14

6

Mapletree North Asia Commercial Trust

Monday, July 16, 2018

 $ (597.34)

6

Mapletree North Asia Commercial Trust

Friday, August 3, 2018

 $ 556.13

6

Mapletree North Asia Commercial Trust

Friday, August 24, 2018

 $ 576.15

7

Singapore Press Holdings Limited

Wednesday, July 11, 2018

 $ (1,390.51)

7

Singapore Press Holdings Limited

Thursday, August 16, 2018

 $ 1,362.74

8

Soilbuild Business Space REIT

Monday, June 4, 2018

 $ (343.17)

8

Soilbuild Business Space REIT

Tuesday, June 19, 2018

 $ 310.00

8

Soilbuild Business Space REIT

Monday, July 16, 2018

 $ (340.66)

8

Soilbuild Business Space REIT

Thursday, July 26, 2018

 $ 310.00

9

Wilmar International Limited

Monday, June 4, 2018

 $ (1,653.28)

9

Wilmar International Limited

Friday, June 22, 2018

 $ 1,560.00

9

Wilmar International Limited

Monday, July 16, 2018

 $ (1,518.01)

9

Wilmar International Limited

Friday, August 24, 2018

 $ 1,605.00

10

Wing Tai Holdings Limited

Monday, June 4, 2018

 $ (1,037.05)

10

Wing Tai Holdings Limited

Thursday, June 7, 2018

 $ 1,040.00

10

Wing Tai Holdings Limited

Wednesday, July 18, 2018

 $ (1,027.03)

10

Wing Tai Holdings Limited

Wednesday, August 15, 2018

 $ 975.00

  

 Total Profit

 $ 4,499

  

 Portfolio Value

 $ 50,000.00

  

 Return

9.00%


The calculations conducted in the above table represent the portfolio, which has been made by stocks listed in technical analysis portfolio. The calculations conducted in the above portfolio depict the level of returns, which can be provided from technical analysis method. In addition, the measures used in the formulation of the technical analysis portfolio was fruitful, as returns from investment was positive and depicted higher returns from investment. The returns of the portfolio are at the levels of 9.00%, while the market returns have declined to the levels of -6.49%. According to Gay (2016), with the help of technical analysis investors are able to detect short-term trend and investment opportunities, which could increase the chance of short-term abnormal returns.

Therefore, from the evaluation of the above two perilous, it could be detected that technical analysis method can be used for generating higher revenue from investment. The calculations have depicted that the portfolio created for fundamental analysis did not depict the current financial trend, which was essential for understanding the short-term investment scope. However, the technical analysis portfolio depicted the highest value for investment, which can be used for generating high rate of return from the created portfolio.

Conclusion:

The calculations conduced in the above assessment mainly depicts the significance of technical analysis over fundamental analysis, which can be used by investor for maximising the returns from investment. In addition, the method used for the selection of technical analysis and fundamental analysis portfolio were accurate. However, only technical analysis was able to beat the market, while fundamental analysis lost, as the trading period was short and did not support the requirements of fundamental analysis. Moreover, technical analysis was mainly helpful in improving the returns from investment, as the prepared portfolio increased returns and beat the market. Hence, investors could use the portfolio for improving their current return generation capacity and raise the level of invested capital. Therefore, the investors who are interested relying on the short-term trend of the stock can use technical analysis method, while long-term investors can use the fundamental analysis method. Lastly, The EHM and behavioural theory directly affects the decision-making capability of the investor, when they are making investment decisions.

References

Arthur, W. B. (2018). Asset pricing under endogenous expectations in an artificial stock market. In The economy as an evolving complex system II (pp. 31-60). CRC Press.

Au.finance.yahoo.com. (2018). Au.finance.yahoo.com. Retrieved 28 August 2018, from https://au.finance.yahoo.com/quote/W05.SI/history?period1=1527964200&period2=1535049000&interval=1d&filter=history&frequency=1d

Bartos, J. (2015). Does Bitcoin follow the hypothesis of efficient market?. International Journal of Economic Sciences, 4(2), 10-23.

Capitaliq.com. (2018). Capitaliq.com. Retrieved 28 August 2018, from https://www.capitaliq.com/CIQDotNet/Index/Constituents.aspx?CompanyId=226679791

Degutis, A., & Novickyte, L. (2014). The efficient market hypothesis: a critical review of literature and methodology. Ekonomika, 93(2), 7.

Dimpfl, T., & Jank, S. (2016). Can internet search queries help to predict stock market volatility?. European Financial Management, 22(2), 171-192.

Eiamkanitchat, N., Moontuy, T., & Ramingwong, S. (2017). Fundamental analysis and technical analysis integrated system for stock filtration. Cluster Computing, 20(1), 883-894.

Ewing, B. T., & Malik, F. (2016). Volatility spillovers between oil prices and the stock market under structural breaks. Global finance journal, 29, 12-23.

Fagereng, A., Gottlieb, C., & Guiso, L. (2017). Asset market participation and portfolio choice over the life?cycle. The Journal of Finance, 72(2), 705-750.

Gay, R. D. (2016). Effect of macroeconomic variables on stock market returns for four emerging economies: Brazil, Russia, India, and China. The International Business & Economics Research Journal (Online), 15(3), 119.

Lim, S., Oh, K. W., & Zhu, J. (2014). Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market. European Journal of Operational Research, 236(1), 361-368.

Mensi, W., Hammoudeh, S., & Kang, S. H. (2015). Precious metals, cereal, oil and stock market linkages and portfolio risk management: Evidence from Saudi Arabia. Economic Modelling, 51, 340-358.

Mouna, A., & Jarboui, A. (2015). Financial literacy and portfolio diversification: an observation from the Tunisian stock market. International Journal of Bank Marketing, 33(6), 808-822.

Schwager, J. D., & Etzkorn, M. (2017). 50 Market Wizard Lessons. A Complete Guide to the Futures Market: Technical Analysis, Trading Systems, Fundamental Analysis, Options, Spreads, and Trading Principles, Second Edition, 575-587.

Schwager, J. D., & Etzkorn, M. (2017). Selecting the Best Futures Price Series for System Testing. A Complete Guide to the Futures Market: Technical Analysis, Trading Systems, Fundamental Analysis, Options, Spreads, and Trading Principles, Second Edition, 279-287.

Syriopoulos, T., Makram, B., & Boubaker, A. (2015). Stock market volatility spillovers and portfolio hedging: BRICS and the financial crisis. International Review of Financial Analysis, 39, 7-18.

Wang, Y. (2016). Construction and simulation on stock price forecasting model based on fundamental analysis and technical analysis. RISTI (Revista Iberica de Sistemas e Tecnologias de Informacao), (E10), 295-304.

Yao, J., Ma, C., & He, W. P. (2014). Investor herding behaviour of Chinese stock market. International Review of Economics & Finance, 29, 12-29


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