Risk Management Technique for Investors at DBS Bank: Analysis

This report delves into the risk management techniques employed by investors at DBS Bank in Singapore, examining how these strategies mitigate potential risks. It begins with an introduction to risk management in the banking sector, highlighting its significance in today's dynamic business environment. The report provides background information on DBS Bank and its risk management approach, including the use of the Value at Risk (VaR) model. It explores the rationale behind studying investor risk management, emphasizing the importance of balancing risk and return. The research aims to identify suitable risk management techniques for DBS Bank investors, focusing on the appropriateness of the CAPM and VaR models. Through a literature review, the report discusses the concepts of uncertainty and risk, and outlines the risk management process. The report further discusses the capital asset pricing model (CAPM) provides an initial framework for assessing the relationship between expected return and risk of an investment.

Running head: RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Risk management technique for investors at DBS bank
Name of the Student
Name of the University
Author Note

1
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Table of Contents
Chapter 1: Introduction:.............................................................................................................2
1.1 Introduction..........................................................................................................................2
1.2 Background of the study......................................................................................................2
1.3 Background of company......................................................................................................3
1.4 Rationale of study................................................................................................................3
1.5 Research aim........................................................................................................................4
1.6 Research objective...............................................................................................................4
1.7 Research questions...............................................................................................................4
1.8 Structure of study.................................................................................................................4
1.9 Conclusion............................................................................................................................5
Chapter 2: Literature review......................................................................................................5
2.1 Introduction..........................................................................................................................5
2.2 Uncertainty and risk.............................................................................................................6
2.3 The process of risk management..........................................................................................6
2.4 Summary............................................................................................................................13
Chapter 3: Research methodology...........................................................................................14
3.1 Introduction........................................................................................................................14
3.2 Research approach.............................................................................................................14
3.3 Justification of research approach......................................................................................14
3.4 Research design..................................................................................................................14
3.5 Justification of research design..........................................................................................15

2
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
3.6 Sampling strategy:..............................................................................................................15
3.8 Instruments of collecting data............................................................................................15
3.9 Procedure of collecting data...............................................................................................15
3.10 Gantt chart........................................................................................................................16
3.11 Ethical considerations......................................................................................................16
3.12 Data analysis....................................................................................................................17
Chapter 4: Discussion, Evidence and analysis.........................................................................17
4.1 Introduction........................................................................................................................17
4.2 Presentation of data............................................................................................................18
4.3 Analysis of data..................................................................................................................19
4.4 Limitations of proposed study............................................................................................20
4.5 Dissemination.....................................................................................................................20
Chapter 5: Conclusion and Recommendation..........................................................................21
5.1 Conclusion and Findings....................................................................................................21
5.2 Scope for future study........................................................................................................21
Reference list:...........................................................................................................................23
Appendix:.................................................................................................................................28
Chapter 1: Introduction:

3
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
1.1 Introduction
Management of risk has become very significant in the light of dynamic operating
environment and growing complexities of business of banking sector. Investors are exposed
to various types of market risks for investing in the stocks of bank. Risk management has
become one of the main functions of the service of bank that consist of risk identification and
controlling that keep the risk at an acceptable level. The basic objective of managing risks
pertains to investors and shareholders by optimizing the capital funds and maximizing the
profits that ensures long-term solvency position of business (Westbom et al. 2018). This
particular research paper concentrates on the risk management techniques adopted by
investors at the DBS bank of Singapore and how such technique helps in mitigating the risk.
1.2 Background of the study
The performance and nature of the performance of financial system in the country
must be judged in relation to the development at individual level. The principal reason for
transferring saving and fund to the private enterprise such as companies who are in need of
capital for productive investment is provided by the financial system. An efficient financial
system helps in channeling the resources to the activities that helps in generating highest
return for using the funds (Zhang 2017). Investors are offered with a variety of short and
long-term instruments via the formal and well-performed financial market. They are able to
make adequate and reasonable decision about the rewards and risk of investing the funds with
the help of qualified financial intermediaries. Risk management in banking sector is defined
as the logical development for executing a plan to tackle with the potential losses. Generally,
the practices of managing the risk in banking sector are to manage the exposure of investors
to the losses or risk. Financial risk management is the activity of monitoring the financial risk
and managing the impact of their risk. It is required to test the relationship between risk and

4
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
return and analyze the inter dependency and correlation between such variables (Mensah and
Premaratne 2017).
1.3 Background of company
DBS bank is a leading financial and banking services corporation headquartered in
Singapore that was earlier known as development bank of Singapore Limited. The
organization is well placed as partner to capture the opportunities across the region. Since the
focus of bank is on the market of Asia, the organization is exposed to risks concentration
within the region. Risks at DBS are effectively assessed by relying on specialist knowledge
of industry segments and regional markets. The approach to risk management at DBS
comprises of three building blocks including policies, risk methodologies and system, process
and report (Dbs.com 2019). The risk methodology used by the bank is VaR (Value at risk)
Model that helps in computation of potential losses of risk position due to movement of
movement of market in accordance with given level of confidence over a specified time
horizon. It is a model used by the bank, which is based on historical simulation with a
holding period of one day. The exposure to market risk is limited and monitored by using an
average of potential loss beyond a given level of confidence. The predictiveness of the VaR
model is verified by conducting the back testing with makes a comparison between the
positions at the close of each day with profit and loss arising from position of the next
business day (Dbs.com 2019).
1.4 Rationale of study
It is essential for investors to evaluate the risks associated with their investment to
create relationship between return and risk. Undertaking this research paper helps in ensuring
that there is sufficient basis of analysis for ensuring that loss generated from investment does
not exceed the acceptable boundaries. In addition to this, the importance of model of risk

5
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
management as a tool of mitigating risk is essential for the purpose of investment. In order
for investors to have best portfolio of investment, it is essential to evaluate the risks
pertaining to their overall investment.
1.5 Research aim
The aim of research is to identify suitable technique for management of risk for the
investors of DBS bank.
1.6 Research objective
The objective of research is to identify the most appropriate technique of managing
risks associated with investment for investors of DBS bank. In addition to this, the research
paper also intends to evaluate the appropriateness and measures of risk management
technique for investors using the model of CAPM and VaR.
1.7 Research questions
 How the application of CAPM determines the effectiveness of risk management at
DBS bank?
 What is the impact of risk management technique of VaR on investors?
1.8 Structure of study
For gaining a better understanding of the overall research study, the whole research
paper is divided into several chapters that are segregated further.

6
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
1.9 Conclusion
The first chapter presented an introductory approach to the research paper by
outlining the objectives and aims of research. This also includes a brief introduction on the
company selected and the risk methodology used by company for managing the risk.
Researcher has also provided rationale for conducting this research paper.
Chapter 2: Literature review
2.1 Introduction
This chapter deals with the in depth study of several theories and model used by
investors related to risk management. It sets out the conceptual framework and determines the
relationship between risk and uncertainty of investment. Literature review also provides
theoretical framework on the models of risk management. This section also outlines the
importance and theories associated with model of VaR and CAPM.
Chapter1IntroductionChapter2LiteraturereviewChapter3ResearchMethodologyChapter4Chapter5ConclusionandRecommendations

7
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
2.2 Uncertainty and risk
Risk can be defined in number of ways and the term risk and uncertainty are the two
common techniques in the risk management literature. Uncertainty is the occurrence and non-
occurrence of outcome because the probability of their occurrence is not known. Uncertainty
is related with the imperfect information and poor knowledge whereas risk is attributable to
situations with well-defined boundaries and considerable data (Abdoh and Varela 2018). The
difference between uncertainty and risks is widely acknowledged in the literature and these
terms are used interchangeably. For the purpose of review, the focus is on the management of
risk by investors at DBS bank.
2.3 The process of risk management
There are several definitions of risk management in literature and it is defined as a
systematic approach that helps in setting the best course of action under uncertainty situations
by the assessment, identification, understanding, communication and acting on risky issues.
Management of risk is a disciplined and structured approach that has purpose of managing
and evaluating the uncertainties faced by aligning the process, technology, strategy and
knowledge of organization. Process of risk management include all the process and
regulations of organization for the assessment, identification, control and analysis of the
potential risk along with supervision of efficiency and profitability of the measures that have
been taken. There are two approaches to the analysis of risk, which include qualitative and
quantitative analysis.
A considerable portion of research in investment management is devoted to
understand how the investors evaluate the riskiness of return and securities are associated
with risks. The discipline of finance has developed much theory about the management of
risk and its usefulness in assessing return. The capital asset pricing model (CAPM) provides

8
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
an initial framework for assessing the relationship between expected return and risk of an
investment. This particular model is widely used in the application for evaluating the
performance of managed portfolios and estimating the cost of capital for firms. The tradeoff
between the risks and return generated by the assets is well explained the CAPM because the
risk of an asset is measured as the covariance of the return of one assets with the overall
market return. The model is based on the prediction that there is a linear relation between the
expected return of any two assets and the covariance of the return of the assets with the return
generated on the market portfolio. There are two types of risks associated with each assets
and such risk include diversifiable risk and non-diversifiable risk.
The reason why CAPM is attractive amongst investors is that it offers intuitively
appealing and powerful predictions regarding the measurement of the relationship between
the expected return and risk and measurement of risk alone. It ideally depicts how the price of
securities are set by the financial market and ultimately determining the return on the capital
investment. The model provides a methodology for quantification of risk and translation of
such risk into expected return on equity (Sutrisno and Nasri 2018). In an attempt to develop,
financial managers mostly use the usefulness of computation of cost of equity and for
supplementing their own techniques and judgment, such model. However, the application of
the model continues to generate, but now it is rather applied as the course to manage
investment.
The portfolio model on the assets that is weighed in the mean variance portfolios
provides an algebraic condition. The algebraic declaration is transformed by the CAPM
model into a testable declaration and between the relationship between expected return and
risk by identifying efficient portfolios. CAPM relies on the theoretical market portfolio that
comprise of all assets such as foreign stocks and real estate. CAPM is tested and analyzed

9
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
that represents market portfolio by using stock market index. The mathematical expression of
CAPM is depicted as
E (Rf )= Rf + βj (Rm - Rf)
where, E (Rf) is the expected return on security
Rf is the risk free rate
βj is the beta of security
Rm is the market return
The above equitation indicates a linear relationship between return and risk. The basic
version of CAPM comes with a number of simplifying assumption that is listed below.
 The decision horizon of all investors is identical and the variance and means of the
distribution of one period of return on the assets over the common horizon period.
 The capital assets market composed of risk averting investors and all the investors
have expected utility of one period terminal wealth maximizes. Such investors are
able to make optimal decisions based on the standard deviation and mean of the
terminal wealth that is associated with several available portfolios (Lane and
Rosewall 2015).
 The opportunities of portfolio and expectation of investors are homogenous
throughput the market. This has the implication that there are same portfolio
opportunities for all investors and the standard deviation and expected return provided
by various portfolios is viewed in the same manner (Kim and Su 2018).
 It is assumed that all the assets are infinitely invisible which makes the capital market
perfect. The information is costless and taxes and transaction costs are equally

10
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
available for everyone. In addition to this, all the investors are offered with same
lending and borrowing rate.
While making investment portfolios, liquidity is regarded as the driver in influencing
the price of stocks. It was founded by the study that the data is explained in a better manner
with the help of liquidity adjusted CAPM as against the standard CAPM. Furthermore, it was
evident that there is weaker influence of the level of liquidity and importance of liquidity risk
over market risk. The pricing of liquidity risk in the Australian market was analyzed using the
data exploring the impact of several measures of liquidity risk on the stock return using the
CAPM model that is liquidity adjusted (Grace et al. 2015). The study strongly evident the co
movement between market illiquidity and stock return, market illiquidity and market return,
market illiquidity and individual stock illiquidity.
Many scholars have studies the capital asset pricing model and have came out with
different and mixed results. One of the studies conducted on the Greek stock market came
with findings that did not support the basic statement of the model that is the validity of high
return and high risk was proved wrong. For some years, the findings generated better results
but the model was not supported overall. Another study conducted on the model identified
that the exact return generated by the assets could not be explained using the CAPM. The
return was significantly negative that arises as a result of instability and it is a known fact that
the returns of stock is influenced the instability of market (Ajibola et al. 2015). However, the
time series of stock return is forecasted by the instability of the stock.
The association between the beta coefficient and the signs of market return and the
beta coefficient is studies by one author for the stocks listed on one of the stock exchanges.
CAPM was viewed as the additional return on the portfolio of market. It was also determined

11
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
that the cross sectional difference of additional expected returns on the stocks is seen as a
measure of risk of assets and is totally captured by the value of beta (Cornell et al. 2017).
It is believed that using the CAPM intends to satisfy the investors in two ways that is
in terms of risk associated with the security and for the time value of money. The risk free
rate is denotation of the fact that the investors are compensated for investing the money over
a period of time. For the additional risk undertaken by the investors, they are provided with
the risk premium for comportment. The validity of the model has been tested by conducting a
number of studies and the model has not always been supported by the result (Magnani and
Zucchella 2018). It was founded by one of the empirical studies that the model results in
moderating the statistical problems arising from the measurement errors in the estimates of
beta. In addition to this, it was also ascertained by the author that the relation between beta
and average return is very close to the linear and any portfolio have higher (lower) returns
having (higher) lower value of betas (Alshomaly et al. 2018). It was forecasted using the
model that there is linear relationship between the expected return on assets above the risk
free rate and non-diversifiable risk that is measured by the beta value of security.
Some of the empirical evidence supported that there exists linear and positive
relationship between the risk and expected return. It was found that the concept of CAPM is
valid and both the return and risk are integrated into the market. Research conducted on some
of other stock exchange such as Athens stock exchange that the volatility is positively related
to return as indicated by significant and positive risk premium. In one of the study that was
conducted on eight Taiwanese industries discovered that there is a mix influence of returns of
stock due to conditional volatility (Iosrjournals.org 2019). Nevertheless, it was found that
only the coefficient with negative returns are significant and such negative risk premium is
suggestive of the fact that for holding risky stocks investors are penalized. It is indicated by
most of the researches on the stock market that they have the characteristics of higher return

12
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
and higher risk. During the last decade, the interest of investors in the emerging markets was
exploded because because of the quest for further international diversification and higher
return (Pätäri and Leivo 2017).
Some other auditors have ascertained that the wrongness of basic assumption might
be due to lack of observed support for the model. It is observed from the most of the tests of
CAPM that assumes that the good alternative to return on market portfolio is the return on the
broad market indices (Kim and Su 2018). However, not all the assets do detent by these types
of market indexes in the economy such as capital.
The regularity of the statement rejected the competence of mean variance and in one
of the study where the model was applied on the different sets that are of high risk and low
risk. It was found that the data with low risk set are reliable with the CAPM and high risks set
data are not compatible with the model. Consequently, it was decided that the actual return
computed by the model is not the results of the capital asset pricing model as they cannot
determine the actual position, which is difficult to rely on, by the investors. The argument is
maintained with the help of results of some other study that single risk factor cannot
completely determine the return generated (Alqisie and Alqurran 2016). However, many of
the findings of research indicate that the model of CAPM generates correct and accurate
results, but with the time the results presented by the model was outperformed by some other
accurate tools.
VaR Model
VaR is the most commonly used method for quantifying the market risk associated
with the portfolios of bank. The potential loss arising from the market value of portfolio is
expressed using a probabilistic indicator by considering an established confidence interval.
There are three different methods that can be used for determining VaR that is parametric,

13
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
historical simulation method and Monte Carlo method (Neslihanoglu et al. 2017). It is
implied by the parametric method that the normal distribution is followed by daily return of
assets. On other hand, the values of past hypothetical data are quantified by historical
simulation method without making any assumption of the relation to return distribution.
Under Monte Carlo method, the scenarios for future prices based on the correlation and
volatility of the assets from past data is generated (Gao and Yang 2018).
The performance of VaR was studied for emerging markets where the extreme value
of the daily return was estimated. The results presented strong argument there are different
characterizes for daily returns for the left and right tail distribution. Another study included
the multivariate extreme values in the model and it was proved that quality of estimation
regarding the fluctuations of financial market might improve for the data with high
frequencies (Malik and Shah 2017).
2.4 Summary
A detailed elaboration on the model used for measuring the risk by investors has
provided the researcher with enough information on the suitability and effectiveness of the
model. The mixed views presented from the findings of different studies conducted would
assist research in deducing the fact from the current study that has to be analyzed.
Chapter 3: Research methodology
3.1 Introduction
This particular chapter outlines the research approach, research design, tools and
methods of collecting the data along with the manner in which the data has been analyzed.

14
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
The methodology of research is an important area in the whole research paper as the main
objective of conducting the research and the method is addressed.
3.2 Research approach
The research is conducted for determining the suitability of the risk management
technique used by the investors at DBS bank. In this research paper, researcher has employed
an empirical study approach to research. It is so because the use of one particular risk
management technique that is CAPM has been identified and the validity and implications of
the model is checked with the help of data collected (Fernandez 2015).
3.3 Justification of research approach
The empirical study and deductive approach has been selected because the findings
have to be related with the analysis of views from literature.
3.4 Research design
Under the present study, the research has implemented a descriptive and quantitative
research design. Since, the main interest of researcher is solely analyzing the topic of interest,
it is considered suitable to adopt descriptive approach.
3.5 Justification of research design
The researcher has adopted a theory-based approach that is created by gathering,
collecting and presenting the collected data. In addition to this, the adoption of quantitative
research design has helped researcher to have statistical conclusions for collecting the
actionable insights (Linnenluecke et al. 2017).

15
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
3.6 Sampling strategy:
The researcher has adopted the technique of non-probabilistic sampling for selecting
the sample for conducting research. Under this sampling, the judgmental sampling method
has been adopted where the sample is selected based on the credibility and knowledge of
researcher. Therefore, only such organizations have been selected which the researcher feel to
have the right fit. However, the results of research can be influenced by the ore conceived
nation of researcher, which is regarded as the downside to this method of sampling (Mensah
and Premaratne 2017). The study incorporates two other companies as a sample other than
the stock of DBS bank, Singapore. Sample banks include OCBC bank and UBOH bank and
the return of the respective stocks have been compared against the return of the index.
3.8 Instruments of collecting data
The researcher has collected secondary data for the purpose of analysis. Secondary
data are the data, which has already been published and have sourced for analyzing it to test
the validity of the model chosen. Therefore, the research conducted for analyzing the topic
under consideration is basically the secondary research.
3.9 Procedure of collecting data
This section takes into account the procedure for collecting the secondary data
pertaining to the topic of interest. Such information is sourced from the annual reports of the
companies under analysis that is published from the respective websites. In addition to this,
data has also been sourced from some other financial websites such as Bloomberg and
yahoofinance.com.
3.10 Gantt chart
Main activity 1st week 2nd week and 4th week 5th week and 7th week

16
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
3rd week 6th week
Selection of the
topic
Determining the
objectives of
research using
the specific
model
Conducting the
review of
literature
Selection of
appropriate
research
technique
Collecting the
data and
analysis
Findings and
recommendation
3.11 Ethical considerations
Researcher has attempted to perform the research under the strict guidance of ethics
and no such actions have been taken that intends to disrupt the legal proceedings while
carrying out research work. While collecting the data and information about the organization,
it was ensured that the ownership of the original data is acknowledged. Any data in the form
of hard copy collected by researchers have kept in the locked cabinets and soft copies being
kept as encrypted files. The secondary analysis has been conducted in a way to ensure that
the further analysis of the data that is conducted is appropriate.

17
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
3.12 Data analysis
The proposed method of analyzing the data is that the return generated from each of
the sample stocks is compared with that of the market index. In addition to this, the relevance
of the CAPM model is tested by evaluating the return by incorporating the value of beta. The
quantitative technique is employed for interpreting the collected data and the stability of beta
testing is done under the model of CAPM. The model assumptions have been detected as
frontier for capitalizing the risk as per the return in accordance with the risk level.
Chapter 4: Discussion, Evidence and analysis
4.1 Introduction
In this chapter, the data collected has been presented and the analysis of the collected
data has been performed by using the appropriate risk management technique. The closing
price of three stocks and the price of index are presented for a time of four years and until
date. Returns generated by each of the stock have been computed and based on the closing
price, the expected returns of the stocks was computed according to the CAPM. In addition to
this, computation of market premium is done as the difference between risk free rate and
expected return of the market index that is STI index multiplied by beta of respective stocks.
4.2 Presentation of data
The table presented below depicts the computation of value of beta of three different
stocks that is beta of DBS bank, OCBC and UOBH bank. Researcher has taken the help of
Excel to compute the value of beta by using CAPM beta formula.
Coeffici
ents
Standard
Error
t Stat P-value Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept - 0.001214 - 0.68913 - 0.00195 - 0.00195

18
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
0.00048
8787
168 0.40256
9052
0039 0.00293
2781
5207 0.00293
2781
5207
X Variable
1
0.10704
3697
0.033327
448
3.21187
8017
0.00240
8629
0.03995
9024
0.17412
8369
0.03995
9024
0.17412
8369
Coeffici
ents
Standard
Error
t Stat P-value Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept 0.00296
9218
0.003252
919
0.91278
5643
0.36611
4642
-
0.00357
8568
0.00951
7004
-
0.00357
8568
0.00951
7004
X Variable
1
1.08409
9645
0.089288
679
12.1415
1292
6.00457
E-16
0.90437
0856
1.26382
8433
0.90437
0856
1.26382
8433
Coeffici
ents
Standard
Error
t Stat P-value Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept -
0.00012
9641
0.007049
434
-
0.01839
0296
0.98540
7031
-
0.01431
9416
0.01406
0134
-
0.01431
9416
0.01406
0134
X Variable
1
-
0.02626
7849
0.193498
412
-
0.13575
2271
0.89260
9462
-
0.41575
9952
0.36322
4254
-
0.41575
9952
0.36322
4254
It can be observed from the table that the value of beta for the stock of DBS bank is
0.1 and that of OCBC and UOBH bank is 1.08 and -0.03 (Bloomberg.com 2019). The
negative value of beta coefficient implies that the return generated by stock is opposite to the
market return.

19
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Particulars
DBS
BANK
OCBC
BANK
UOBH
BANK
Market
Return 6.88% 6.88% 6.88%
Beta 0.11 1.08 (0.03)
Risk free rate 2.04% 2.04% 2.04%
CAPM 2.56% 7.29% 1.91%
4.3 Analysis of data
The underlying principle of CAPM is that there is a linear relationship between the
beta and return of stocks and the return generated by stocks is explained by the reliability of
beta coefficient. From the table presented above, it can be observed that the stock of OCBC
bank has higher beta value that is the beta coefficient of stock is more than the market with
beta coefficient of 1. On other hand, the beta coefficient of UOBH bank is negative indicating
lower return generated by stocks compared to market. The expected return of stock of OCBC
bank is higher than the market return. The expected return generated by the stocks of DBS
bank is lower than the market return because the value of beta coefficient is less than the
market beta value (French 2018). When looking at the expected return of the stocks of UOBH
bank having negative beta coefficient. This implies that if the market return were moving
upwards, then the return generated by the stock would move downward. Therefore, from the
analysis of the presented data, it can be inferred that the expected return of stock of DBS
bank is lower than OCBC bank.
4.4 Limitations of proposed study
One of the main limitations of this research paper is that the research work is confined
to few of the banks of Singapore. That is the focus of research is on the technique used by
investors of banking sector and hence this would create difficulty in generalizing the results

20
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
to some other sector. Most of the limitations are limited to the approach of empirical study in
general and particularly to the set of data and methodology implemented. It is recommended
by the CAPM that the market portfolio in the test should combine all the assets; however, it is
not possible to bring all the worldwide assets in one portfolio. In order to arrive at results that
are more accurate conducted using the CAPM should be obtained based on investigation of
many stocks that is grouped into portfolios. Since the sample of the study under consideration
was small, instead of using portfolio beta, individual stock beta has been used. Furthermore,
there might be some measurement errors because of short observation period and small
sample size.
4.5 Dissemination
The findings generated from the research paper would be disseminated through public
media such as media coverage. In addition to this, for dissemination of information to broad
audiences, a visually appealing and concise is through research briefs and brochures. A
regular newsletter summarizing the findings of research can also be considered as an ideal
way for dissemination.
Chapter 5: Conclusion and Recommendation
5.1 Conclusion and Findings
The paper intended to study the expected return of the stocks of DBS bank to
investors in the light of CAPM. It is indicated by the literature review that for explaining the
risk return trade off, the original version of CAPM is not adequate. The validity of CAPM has
been examined in the application of the stocks of banks of Singapore and verification of the
theory that higher risk is associated with higher value of return has been examined. The study
tested the effectiveness of beta in determining the return generated by stocks and was

21
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
ascertained that for all the stocks, beta was a significant factor. However, the value of beta
was not fully capable of explaining the return on stocks.
Some of the findings resulted from the analysis of empirical results are listed below:
 The variation in value of beta coefficient causes variation in the value of expected
returns of stocks. A higher value of beta generates higher expected returns and vice
versa.
 The magnitude of beta is significantly affected by coefficient of correlation between
the market return and stock.
 In the entire scenario, the market premium was positive.
 The returns of stock are determined by factors other than the systematic risk and beta
cannot be regarded as the only source for determining return generated to stocks.
5.2 Scope for future study
The research topic is considered very crucial in the field of financial management and
investment. It has been found that beta is not the only factor determining the expected on the
stock and there is little support for the basic hypothesis of theory that higher return is
associated with higher value of beta that is higher risk. Therefore, for determining the return
generated by the stocks, there is a need to conduct further research using different model and
risk management techniques.
Reference list:
Abdoh, H. and Varela, O., 2018. Competition and exposure of returns to the C-
CAPM. Studies in Economics and Finance, 35(4), pp.525-541.

22
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Ajibola, A., Kunle, O.A. and Prince, N.C., 2015. Empirical proof of the CAPM with higher
order co-moments in Nigerian stock market: the conditional and unconditional based
tests. Journal of Applied Finance and Banking, 5(1), p.145.
Alqisie, A. and Alqurran, T., 2016. Validity of Capital Assets Pricing Model (CAPM)
(Empirical Evidences from Amman Stock Exchange). Journal of Management
Research, 8(1), pp.207-223.
Alshomaly, I., Masa’deh, R.E. and AqabaBranch, J., 2018. The Capital Assets Pricing Model
& Arbitrage Pricing Theory: Properties and Applications in Jordan. Modern Applied
Science, 12(11).
Beltrame, F., Caselli, S. and Previtali, D., 2018. Leverage, Cost of capital and Bank
valuation. Journal of Financial Management, Markets and Institutions, 6(01), p.1850004.
Bloomberg.com., 2019. Bloomberg - Are you a robot?. [online] Available at:
https://www.bloomberg.com/markets/rates-bonds [Accessed 3 Apr. 2019].
Cornell, B., Hsu, J. and Nanigian, D., 2017. Does Past Performance Matter in Investment
Manager Selection?. Journal of Portfolio Management, 43(4), p.33.
Dbs.com., 2019. [online] Available at:
https://www.dbs.com/annualreports/2017/pdfs/governance-and-risk-management/DBS-AR17-
71-91.pdf [Accessed 3 Apr. 2019].
Faisal, S.M., Khan, A.K. and Al Aboud, O.A., 2018. Estimating Beta (β) Values of Stocks in
the Creation of Diversified Portfolio-A Detailed Study. Applied Economics and
Finance, 5(3), pp.89-99.
Fernandez, P., 2015. CAPM: an absurd model. Business Valuation Review, 34(1), pp.4-23.

23
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
French, J., 2016. Estimating Time-Varying Beta Coefficients: An Empirical Study of US and
ASEAN Portfolios. In The Spread of Financial Sophistication through Emerging Markets
Worldwide (pp. 19-34). Emerald Group Publishing Limited.
French, J., 2017. The one: A simulation of CAPM market returns. The Journal of Wealth
Management, 20(1), pp.126-147.
French, J., 2018. Market moods: an investor sentiment event study. foresight, 20(5), pp.488-
Gao, Y. and Yang, X., 2018, June. A Study on the Relationship Between CAPM and China
Stock Market. In 2018 2nd International Conference on Management, Education and Social
Science (ICMESS 2018). Atlantis Press.
Grace, M.F., Leverty, J.T., Phillips, R.D. and Shimpi, P., 2015. The value of investing in
enterprise risk management. Journal of Risk and Insurance, 82(2), pp.289-316.
Iosrjournals.org., 2019. [online] Available at: http://iosrjournals.org/iosr-jbm/papers/Vol17-
issue4/Version-2/B017421022.pdf [Accessed 3 Apr. 2019].
Joshi, H., 2017. Constructing international equity portfolio for BRIC nations using modified
global CAPM returns. Abhigyan, 35(1), pp.25-35.
KHAN, A., TARIQ, Y.B. and KHAN, M.K., 2016. MODERN PORTFOLIO THEORY: A
REVIEW OF LITERATURE. Journal of Global Economics, Management and Business
Research, pp.45-52.
Kim, K.S. and Su, Y., 2018. Reexamination of estimating beta coefficient as a risk measure
in CAPM. The Journal of Asian Finance, Economics and Business, 5(1), pp.11-16.
Lane, K. and Rosewall, T., 2015. Firms’ investment decisions and interest rates. Reserve
Bank of Australia Bulletin. June quarter, pp.1-7.

24
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Linnenluecke, M.K., Chen, X., Ling, X., Smith, T. and Zhu, Y., 2017. Research in finance: A
review of influential publications and a research agenda. Pacific-Basin Finance Journal, 43,
pp.188-199.
Mackaya, W. and Haque, T., 2016. A study of industry cost of equity in Australia using the
Fama and French 5 Factor model and the Capital Asset Pricing Model (CAPM): A
pitch. Accounting and Management Information Systems, 15(3), p.618.
Magnani, G. and Zucchella, A., 2018. Uncertainty in entrepreneurship and management
studies: a systematic literature review. International Journal of Business and
Management, 13(3), pp.98-133.
Malik, I. and Shah, A., 2018. Single stock futures and their impact on risk characteristics of
the underlying stocks: A dynamic CAPM approach. South Asian Journal of Management
Sciences, 12(1), pp.46-68.
Malik, I.R. and Shah, A., 2017. The impact of single stock futures on market efficiency and
volatility: A dynamic CAPM approach. Emerging Markets Finance and Trade, 53(2),
pp.339-356.
McNeil, A.J., Frey, R. and Embrechts, P., 2015. Quantitative Risk Management: Concepts,
Techniques and Tools-revised edition. Princeton university press.
Mensah, J.O. and Premaratne, G., 2017. Dependence patterns among Asian banking sector
stocks: A copula approach. Research in International Business and Finance, 41, pp.516-546.
Miffre, J., 2016. Long-short commodity investing: A review of the literature. Journal of
Commodity Markets, 1(1), pp.3-13.
Negrea, B. and Toma, M., 2017. Dynamic CAPM under ambiguity—An experimental
approach. Journal of Behavioral and Experimental Finance, 16, pp.22-32.

25
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Neslihanoglu, S., Sogiakas, V., McColl, J.H. and Lee, D., 2017. Nonlinearities in the CAPM:
Evidence from developed and emerging markets. Journal of Forecasting, 36(8), pp.867-897.
Pätäri, E. and Leivo, T., 2017. A closer look at value premium: Literature review and
synthesis. Journal of Economic Surveys, 31(1), pp.79-168.
Ramiah, V., Xu, X. and Moosa, I.A., 2015. Neoclassical finance, behavioral finance and
noise traders: A review and assessment of the literature. International Review of Financial
Analysis, 41, pp.89-100.
Ruhani, F., Islam, M.A.I. and Ahmad, T.S.T., 2018. Theories Explaining Stock Price
Behavior: A Review of the Literature. International Journal of Islamic Banking and Finance
Research, 2(2), pp.51-64.
Sutrisno, B. and Nasri, R., 2018, October. Is More Always Better? An Empirical
Investigation of the CAPM and the Fama-French Three-factor Model in Indonesia. In n
International Conference on Economics, Business and Economic Education (pp. 454-468).
Syarif, D.H., Wahyudi, S. and Muharam, H., 2017. Applying an international CAPM to
herding behaviour model for integrated stock markets. Journal of International
Studies, 10(4), pp.47-62.
Syarif, D.H., Wahyudi, S. and Muharam, H., 2017. Applying an international CAPM to
herding behaviour model for integrated stock markets. Journal of International
Studies, 10(4), pp.47-62.
Westbom, E., Seteánszki, E., and Harish, S. 2018. Performance analysis of the Swedish
Pension Fund Market using CAPM.

26
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Xiao, Y., Faff, R., Gharghori, P. and Min, B.K., 2017. The Financial Performance of Socially
Responsible Investments: Insights from the Intertemporal CAPM. Journal of Business
Ethics, 146(2), pp.353-364.
Zhang, L., 2017. The investment CAPM. European Financial Management, 23(4), pp.545-
603.

27
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Appendix:

28
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK
Date Close Return Date Close Return
19-Apr 11.35 2.71% 19-Apr 24.25 5.85%
19-Mar 11.05 -0.09% 19-Mar 22.91 0.31%
19-Feb 11.06 -3.91% 19-Feb 22.84 3.91%
19-Jan 11.51 2.22% 19-Jan 21.98 14.54%
18-Dec 11.26 0.00% 18-Dec 19.19 4.46%
18-Nov 11.26 4.84% 18-Nov 18.37 -8.74%
18-Oct 10.74 -6.12% 18-Oct 20.13 3.82%
18-Sep 11.44 1.24% 18-Sep 19.39 -1.12%
18-Aug 11.30 -2.33% 18-Aug 19.61 8.40%
18-Jul 11.57 -0.60% 18-Jul 18.09 5.48%
18-Jun 11.64 -7.18% 18-Jun 17.15 -9.11%
18-May 12.54 -9.13% 18-May 18.87 1.45%
18-Apr 13.80 7.64% 18-Apr 18.60 2.09%
18-Mar 12.82 -1.84% 18-Mar 18.22 -1.09%
18-Feb 13.06 1.01% 18-Feb 18.42 1.21%
18-Jan 12.93 4.36% 18-Jan 18.20 1.05%
17-Dec 12.39 -0.48% 17-Dec 18.01 -4.35%
17-Nov 12.45 4.62% 17-Nov 18.83 0.27%
17-Oct 11.90 6.63% 17-Oct 18.78 -7.99%
17-Sep 11.16 -0.09% 17-Sep 20.41 0.05%
17-Aug 11.17 -1.67% 17-Aug 20.40 -2.49%
17-Jul 11.36 5.28% 17-Jul 20.92 -2.70%
17-Jun 10.79 2.86% 17-Jun 21.50 -2.76%
17-May 10.49 7.04% 17-May 22.11 1.42%
17-Apr 9.80 0.82% 17-Apr 21.80 -5.13%
17-Mar 9.72 2.75% 17-Mar 22.98 -0.61%
17-Feb 9.46 0.75% 17-Feb 23.12 -3.63%
17-Jan 9.39 5.27% 17-Jan 23.99 -0.17%
16-Dec 8.92 -1.76% 16-Dec 24.03 2.26%
16-Nov 9.08 7.08% 16-Nov 23.50 -4.55%
16-Oct 8.48 -1.97% 16-Oct 24.62 -6.03%
16-Sep 8.65 0.70% 16-Sep 26.20 -0.95%
16-Aug 8.59 -0.12% 16-Aug 26.45 -3.57%
16-Jul 8.60 -1.04% 16-Jul 27.43 -1.65%
16-Jun 8.69 0.81% 16-Jun 27.89 1.42%
16-May 8.62 -1.71% 16-May 27.50 -8.76%
16-Apr 8.77 -0.79% 16-Apr 30.14 7.11%
16-Mar 8.84 9.54% 16-Mar 28.14 5.16%
16-Feb 8.07 1.89% 16-Feb 26.76 -0.96%
16-Jan 7.92 -10.00% 16-Jan 27.02 -0.15%
15-Dec 8.80 1.50% 15-Dec 27.06 -0.07%
15-Nov 8.67 -3.99% 15-Nov 27.08 11.07%
15-Oct 9.03 2.73% 15-Oct 24.38 -3.06%
15-Sep 8.79 -1.57% 15-Sep 25.15 2.36%
15-Aug
15-Jul
15-Jun
15-May
OCBC BANK UOBH BANK

29
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK

30
RISK MANAGEMENT TECHNIQUE FOR INVESTORS AT DBS BANK