Part

Introduction
a)
i. The Payback Period
Initial Investment −Resale Value
Depreciation = Cash flow = Profit + Depreciation
Useful Life
180000−40,000
Depreciation of Project X = =35,000
4
160000−10,000
Depreciation of Project Y =37,500
4
The table below includes the result of cash flow of each project:
Year Cash flow of Project Xi Cumulative Cash flow Y Cumulative
of Project X of Project Y
0 -180,000 -160,000
1 50,000 + 35,000 = 85,000 -95,000 10,000 + 37,500 = -112,500
47.500
2 40,000 + 35,000 = 75,000 -20,000 25,000 + 37,500 = -50,000
62.500
3 20,000 + 35,000 = 55,000 35,000 45,000 + 37,500 = 32,500
82.500
4 10,000 + 35,000 +40,000 = 120,000 60,000 + 37,500 + 140,000
85,000 10,000 = 107,500

20,000
Payback of Project X will be in 2 + = 2.36 years
55,000
32,500
Payback of Project Y will be in 2 + = 2.61 years
82,500
 According to the above calculation method, we can see that the payback period of project X
is profitable earlier than the other project, so we will see that the favor for project X is more
than project Y.
ii. The Return on Capital Employed (ROCE)
Average Annual Accouting Profit
ROCE = × 100 %
( Initial investment + ResaleValue)÷ 2
 (50,000+ 40,000+20,000+10 , 000)÷ 4
ROCE of Project X = x 100 %=27 , 27 %
(180,000+40,000) ÷ 2

(10,000+25,000+ 45,000+60,000)÷ 4
ROCE of Project Y = x 100 %=41.17 %
(160,000+10,000)÷ 2
 According to ROCE theory, we see that the rate of return of project Y is higher than that of
X. Therefore, the potential level of project Y to generate much more profit than the initial
investment is higher than the other project.
iii. The Net Present Value (NPV)
C1 C2 Cn
NPV = -C 0+ + 2
+..+ n
1+r (1+r ) (1+ r)
85,000 75,000 55,000 85,000
NPV of Project X = −180,000+ 1+10 % + + + =58 , 63 %
( 1+ 10 % ) ( 1+10 % ) ( 1+10 % )4
2 3

47,500 62,500 82,500 107,500

NPV of Project Y = −160,000+ 1+10 % + + + =70 , 24 %
( 1+ 10 % ) ( 1+10 % ) ( 1+10 % )4
2 3

According to the theory of NPV, projects X and y both satisfy the condition greater than 0. This
proves that both projects generate returns greater than their initial investment. It is easy to see
that choosing project Y will be preferred because it has a higher NPV than project X.
In summary, Project Y has a higher potential than Project X because project X has a faster
repayment period but loses much more in other areas such as ROCE or NPV. Moreover, the
Payback Period method is usually only used for small projects, while the other two methods are
preferred in large projects.
B,
* The Payback Period
According to the CFI (2023), the payback period method determines how long it takes for
a project to turn a profit in units of years. Small-time projects with the shortest payback will be
used this method.
Since the cash flows after repayment are not calculated using the payback period method,
the value of the project cannot be determined. The payback period method, as described by CFI
(2023), is an approximation of a project's cash flows. This method works well because the return
calculation is easy and efficient and shows how quickly a refund can be made. Payback period is
the easiest approach to understanding an investment project for a business. The payback method
will have more credibility for temporary strategies than long-term strategies (G. Reniers, 2016).
The payback period approach has advantages but it also has limitations (Louise, 2020).

The table below shows the benefits and harms of the Payback period method:
Pros Cons
 Aim directly at the financial source -  It is not possible to calculate future
money that every company must care financial events
about  Don't care about project specificity
 Simple and effective calculation method  Doesn’t a big influence on investment
 Can directly compare projects with each choice
other
 Know the payback period to be able to
anticipate the impact of the market

* The Return on Capital Employee

According to Dheeraj Vaidya (2023), return on capital employed (ROCE) is a statistic
used to evaluate the efficiency and return of an organization's investments. This concept is
sometimes referred to by the acronym ROCE, which stands for return on capital employed. This
reach ratio represents how effectively a company is at recovering capital from its capital
investments and indicates how successful the company has been in doing so. A high return on
capital employed (ROCE), also known as return on investment, is a sign of competitive
advantage. When two institutions have similar income levels but different rates of return on
capital employed, potential investors should put their money in the business with the higher ratio.
Therefore, the importance of profitable and financial growth should not be underestimated.
Businesses struggling to make ends meet are often wary of each other, as there is a high
probability that they will suffer monetary losses in the event of a market crash. Although it has
many applications, return on capital employed (ROCE) is still limited in some contexts
(Madhuri, 2021). The following table provides an overview of the benefits and limitations
associated with this rate:
Pros Cons
  As a tool for investors to compare  ROCE can be faked by project
projects and companies with each accountants resulting in overstated
other profits
 The ROCE is considered an important  ROCE is based solely on the books
criterion to evaluate a project, so which may result in a difference from
investors are very fond of it the market.
* The Net Present Value (NPV)
According to Baron (2021), NPV's intended purpose is to investigate the financial
strategy used to evaluate a project's viability for funding. Tettey (2020) argues that the net
present value (NPV) is a useful tool for assessing investments because it accurately reflects the
value of money over time. When companies begin working on projects, they incur expenses,
making it simple to see the link behind NPV. Because these funds often come from investors
expecting a return, the corporation shouldn't choose to invest unless the future cash flow is
expected to be worth more than the cost of the project at the current time. The net present value
(NPV) approach is used by investors when evaluating a stream of cash flows that occur at
different dates. One further reason why the NPV tool is so popular is because it accounts for how
much time is worth to the user. NPV is a useful tool, and it has numerous benefits, but it also has
certain limitations (Mendell, 2020). Below is a table outlining the benefits and drawbacks of this
approach:
Pros Cons
 The NPV takes into consideration the  Have to choose discount rate. NPV
amount of the investment. It may be also assume that the discount rate will
used to compare small-scale forestry not change throughout the project life.
investments to multibillion-dollar  NPV relied on the presumption that
projects or acquisitions. you could analyze and predict cash
 NPV is not difficult to calculate. flows in the future.
 The temporal value of money is  It is a little bit difficult to understand
recognized by NPV. with unexperienced.
* The Internal Rate of Return (IRR)
According to Marko and Domagoj (2021), IRR is defined as a key factor for making
decision about financial, which offers news to the investors about their profits in its relative
form. The IRR is a rebate ratio that reduces the project’s net cash flows during its life to the
value ofi its investment costs. It known as a ratio of ROI which takes into account the time value
of cash flow throughout the course of the project’s existence (Orsag, 2002). However, besides
the benefits it brings, IRR method still has limitations in its use (Marko and Domagoj, 2021).
The following table presents about the pros and cons of this method:
Pros Cons
 It examines the issue of time value of  There might be several IRRs.
money.  Since a actual-valued IRR may not
 This method is not difficult to utilize. unreal so it’s cannot compare with
 This method eliminates the need for cost of capital.
the discount rate to be determined  Cannot used this method in case cost
subjectively. of capital change over the time.
 This method cannot demonstrate the
investment’s loss.
 It is not pay attention to projecti size;
that is, this method is only a relative
measure, it’s not an absolute metric
because it provides information about
the annual average
 It will take a lot of time because this
method uses trial approach.
Part B
The value of Z’ (Z’ is Z after taking over Y) excluding the operating savings
= The Value of Y + The Value of Z – Cash paid to Y
= 3 mil x £3.8 + 10 mil x £5 – 3 mil x £5 = £46.4 (million)
The value of one share of Z’ excluding the operating savings = 46.4 / 10 (mil) = £4.64 (million)
The value of Z’ including the operating savings = 46.4 + 10 = £56.4 (million)
The value of one share of Z’ including the operating savings = 56.4 / 10 = £5.64 (million)

Semi-strong from Strong form

Y’s price Z’s price Y’s price Z’s price
 Dayi 2 £3.8i £5i Dayi 2 £5i £5.64
Dayi 4 £5i £4.64 Dayi 4 £5i £5.64
Dayi 12 £5i £5.64 Dayi 12 £5i £5.64
ii.
The value of Z’ excluding the operating savings = 3 mil x £3.8 + 10 mil x £5 – 0 = 61.4 (million)
The value of one share of Z’ excluding the operating savings = 61.4 / (10+3) = £4.39 (million)
The value of Z’ including the operating savings = 61.4 + 10 = £71.4 (million)
The value of one share of Z’ including the operating savings = 71.4 / (10++3) = £5.49 (million)
Semi-strong from Strong form
Y’s price Z’s price Y’s price Z’s price
Dayi 2 £3.8 £5i Dayi 2 £5.49i £5.49
Dayi 4 £4.39 £4.39 Dayi 4 £5.49i £5.49
Dayi 12 £5.49i £5.49i Dayi 12 £5.49i £5.49
* Weak form:
Because of this structure, stock prices are affected by all of the information that is readily
accessible to the public on the financial markets; nevertheless, stock prices do not represent
recent information or information that is not readily available to the public. According to this
particular iteration of the EMH, this suggests that none of the information, including price,
volume, and profit, will have any influence on the price of the asset in the future. Furthermore,
future price action based on fresh information cannot be easily expected based on existing price
information; as a result, technically greater profit will not come from using technical transaction
approaches. To add salt to injury, this iteration of EMH devalues technical analysis, but
fundamental research has the potential to generate a return that is far higher than the average of
the market.
Using statistical methods such as the two-test, run, and serial correlation, for example, Paiboon
(1986) establishes in his journal that the Thai financial market is in a weak-form by exhibiting its
behavior. In addition, in 2017, Komain, in the same vein as Pa boon, carried out research on the
Thai market. In his research, Komain came to the conclusion that the SET index follows a
pattern of movement known as a random walk. Furthermore, the variance-ratio method was used
to show that Thailand is a market with a weak-form structure. In addition, based on the findings
of his research (2015), Colin suggested that Thailand is an inefficient market by using testing
strategies such as runs, autocorrelation function, and other similar methods. By applying testing
methodologies such as unit root, variance ratio, spectral shape, and average exponential, Muneer
and Maheswaran (2017) came to the conclusion that Thailand's financial sector is inefficient.
These findings are comparable to those that were discovered by Colin in his research into the
Thai financial industry. According to Kim and Abul (2017), the variance-ratio test reaches the
conclusion that Thailand is a market with weak form. This finding supports the authors'
conclusion. This research also explains why the Thai market eventually became competitive in
the years after the Asian financial crisis that occurred in 1997.
Komain's research focuses on examining the behavior of stock prices on the Thai stock market
via the use of variance-ratio approaches. This research was conducted in Thailand. The GARCH
process is used by Komain to examine the volatility of stock returns in terms of gains and losses,
while the variance-ratio approach determines whether or not the stock price is following a
random walk. It is possible to simulate the volatility of stock return using the GARCH process.
The first method is used to determine whether or not stock prices follow a completely random
path, while the second method may be used to determine the degree to which price variations are
responsible for erratic stock market returns. It's possible that the findings of this research will
provide some insight into the subject of whether or not the Thai stock market is efficient. In
addition, Colin (2015) has shown via the use of analytic tools such as runs and autocorrelation
that Thailand is a market with a weak-form structure. In this investigation, we make use of a
non-parametric run-test and an autocorrelation test to search for consistent statistical aspects of
the price and return profile. We do this so that we are not too dependent on any one asset pricing
model. There would be no possibility for arbitrage if the Stock Exchange of Thailand (SET) was
effective since stock prices would accurately and totally represent all significant information. A
conclusion that may be drawn from this kind of test is that the Thai stock market is inefficient if
the outcome is negative. In the most general sense, efficiency refers to the fact that one can rely
on stock prices to correctly represent the worth of the company's underlying assets.
* Semi-Strong form:
If you apply this framework instead of fundamental or technical analysis, both methods will be
completely ineffective. In the context of the financial markets, it might be defined as any piece of
information that could cause a change in the value of an asset. Its significance may be ascribed to
any recently acquired knowledge. Therefore, fundamental analysis will be rendered useless in
predicting future price fluctuations.
For instance, Gupta (2013) has shown that the Indian financial industry is in moderate health
using event research. Gupta claims that this is the case. Iqbal and Mallikarjunappa (2017) have
also written a report after researching the Indian market. The results are on par with those found
in Gupta's study. The authors of the research concluded, using both parametric and non-
parametric tests, that the Indian financial market is of a semi-strong kind. Moreover, according to
Pilchard, the Indian market is somewhat powerful in terms of efficiency as measured by tests like
statistical analysis and case study. This claim is supported by findings from an analysis
conducted by Pilchard (2019). In addition, Mihaley investigated the Indian market for a report on
this sector that was published in 2012. Mihaley concluded from this research that the strong form
is not true in the Indian market, but that the semi-strong version is effective. Mishra's (2015)
study, which follows a similar methodology, concludes that the Indian market is a semi-strong
form market. The event-study approach was used to get this result.
Gupta (2013) used event research to look at the Indian stock market's lukewarm efficiency
between 1995i and 2000. The study examined the impact of bonus issues on the price of equity
share transactions in India using a sample size of 145 bonus issues. This meant that Gupta's
analysis indicated that the Indian stock market was inefficient to some degree. The market
reaction to quarterly results announcements for 149 businesses listed on the Bombay Stock
Exchange in September 2011 was also studied by Iqbal and Mallikarjiunappa (2017). They did
this using a mix of parametric and nonparametric techniques. It has been determined that
abnormal returns occur at random during the event window since running tests are not significant
at the 5% level. However, the t-test refutes the existence of daily abnormal returns, allowing
investors to beat the market and generate their own abnormal returns. Based on their research,
Iqbal and Mallikarjiunappa concluded that the Indian stock market exhibited features of a semi-
efficient market.
* Strong form: This specific version of EMH applies to both publicly available and non-public
data on the financial markets. This means that any insider knowledge that has been leaked will
be included into the current share price of a business or organization. since of this, investors
won't be able to earn more than the market average since they can't make use of the specialist
information that is accessible to them to predict changes in the prices of assets. For example,
Oladapo and Ayowole's (2013) study tests the assumption that professionally managed funds
provide better returns than the market index. An experiment is performed to check this idea. We
analyzed the average monthly returns from 2007 through 2011 across five different financial
institutions. The efficiency of the Nigerian Stock Exchange (NSE) was analyzed using the
"market model" for calculating residuals. The anomalous return on a well-managed portfolio has
been demonstrated to be statistically indistinguishable from zero. However, Oladapo and Ayowle
have not yet shown irrefutable proof that the strong-form Nigerian idea is correct. Similarly, Ojo
and Azeez (2012) examined the Nigerian stock market from 1986 to 2010 to see whether it
supported the strong-form efficient market theory. Both the ARCH and GARCH models were
used over the course of the empirical study. According to the results of this study, the weak-form
is the one that best fits the Nigerian language.
https://corporatefinanceinstitute.com/resources/financial-modeling/payback-period/ - CFI,2023

https://www.sciencedirect.com/book/9780128037652/dynamic-risk-analysis-in-the-chemical-and-petroleum-

industry - G. Reniers-2016
https://www.wallstreetmojo.com/return-on-capital-employed-roce/