Corporate Financial Management: FIN200 Assignment Report Analysis

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This report delves into the realm of corporate financial management, examining the application of sensitivity analysis, scenario analysis, break-even analysis, and simulation analysis within the decision-making processes of business organizations. It elucidates how these tools enable managers to assess investment projects, manage uncertainties, and make informed decisions. Furthermore, the report explores the critical relationship between these analytical tools and key capital budgeting components, namely Net Present Value (NPV) and Internal Rate of Return (IRR), demonstrating their significance in determining the viability of investment projects. The report underscores the importance of integrating these tools with capital budgeting methods to enhance the decision-making capabilities of organizational managers, facilitating a comprehensive evaluation of investment opportunities and their associated risks. The analysis highlights the interconnectedness of financial tools and capital budgeting, emphasizing the role of these tools in evaluating the various aspects of investment projects.
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Running head: CORPORATE FINANCIAL MANAGEMENT
Corporate Financial Management
Name of the Student
Name of the University
Author’s Note
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1CORPORATE FINANCIAL MANAGEMENT
Introduction
Corporate decision-making process is considered as a crucial aspect in the business
organizations which involved in making crucial decision for different aspects of the
organizations like investment decisions and others. The managements of the companies have
the option to use different types of financial tools for making corporate decisions; sensitivity
analysis, break-even analysis and others. One crucial aspect is that these tools have certain
connections with the aspects of capital budgeting like Internal Rate of Return (IRR) and Net
Present Value (NPV). This is a crucial aspect that the managements of the companies are
required to consider at the time of corporate decision-making. The main aim of this report is
the analysis and evaluation of four concepts; they are Sensitivity Analysis, Scenario Analysis,
Break-even Analysis and Simulation Analysis. After that, this report undertakes the analysis
of the connection of these concepts with the major components of capital budgeting which
are NPV and IRR. It means that this report discusses about the relation of the capital
budgeting concepts with the selected concepts.
a. Sensitivity Analysis
Sensitivity Analysis is considered as a major tool that is used in financial modelling in
order to analyse how the different values of a set of independent variables create impact on a
specific dependent variable under certain specific conditions. In a more specific sense,
sensitivity analysis is considered as a process that the investors use for understanding what
components of the market condition and environmental variables will change their
perspective investments (Finnerty 2013). For instance, this tool is often used by the investors
for testing what variables change the price of stock of a listed company and to what extent.
Investors study the sensitivity analysis through changing one variable at a time and spotting
the following impact. By segregating the variables through the process to eliminate, investors
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become able in gaining a clear picture of the elements that have effects on the stock prices.
The use of this tool can also be seen in gathering information as well as preparing different
outcome in the presence of incorrect interpretation of data by a special system. It implies that
the sensitivity analysis assists in determining how different values of an independent variable
affect a specific dependent variable in a provided set of assumption. Vast use of this
technique can be seen in the business world as well as in the field of economies (De Grauwe
and Grimaldi 2018).
Now, it needs to be mentioned that sensitivity analysis has a major relation with the
main two components of capital budgeting that are NPV and IRR. The wide use of sensitivity
analysis can be seen in the capital budgeting decisions for assessing how the change in inputs
such as variable costs, sales, fixed costs, cost of capital and marginal tax rate will create an
impact on such outputs as a project’s NPV, IRR and discounted payback period. With the use
of sensitivity analysis, it becomes possible to investigate into the fact that how the projected
performance will differ along with the alterations in the key assumptions on which the
projections of capital projects are grounded (Wu et al. 2014). The NPV of a particular project
is grounded on the series of cash flows along with the discount factor. Both of these
determinants have dependency on large variables like sales, revenue, competition, input cost
and other. In the presence of all of these variable, a series of cash flows will be there along
with the NPV of the proposal. In the presence of the change in any of these variables, there
will be change in the value of NPV. It indicates towards the aspect that sensitivity analysis
helps in measuring the movement in NPV as its value is sensitive to all these variables
(Valickova, Havranek and Horvath 2015).
b. Scenario Analysis
Scenario analysis refers to a process to estimate the a portfolio’s expected value after
a provided period of time while assuming certain changes in the portfolio’s value or the
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occurrence of major factors like interest rate and others. Common use of this tool can be seen
in estimating the changes in the value of a portfolio in reaction to an adverse events and in
determining the worst-case scenario. Scenario analysis involves in the computation of
different reinvestment rates for expected returns that are reinvested within the investment
horizon (Verguet et al. 2013). On the basis of mathematical as well as statistical principles,
scenario analysis gives a process for estimating changes in the portfolio values on the basis of
the occurrence of different circumstances, referred to as scenarios while following the
principles of ‘what if’ analysis. Under this tool, three scenarios are used by the managements
of the companies that are base case scenario, worst case scenario and best case scenario. In a
general note, scenario analysis can be considered as a method to estimate what will happen to
the value of a portfolio in case a specific incident takes place or does not take place. This tool
helps in determining the fact that what will happen in case the incident takes place (Arnold
and Yildiz 2015).
Scenario analysis also has connection with the capital budgeting components of NPV
and IRR because this tool is used for estimating the expected value of an investment in best
case, base case and worst case scenarios. At the time of the calculation of NPV and IRR,
scenario analysis involves in using the most likely value of discount rate, growth of cash
flows, tax rate and others (Damodaran 2016). Most importantly, scenario analysis allows in
assigning probabilities to the base case, best case and worst case scenarios so that the
expected values can be found along with the standard division of the NPV of the project so
that better idea can be obtained about the risks of the project. It implies that scenario analysis
is a major behavioural approach in which several possible alternatives outcome are obtained
for measuring the variability of returns through NPB and IRR. It is possible to gain better
idea about the project’s risk in the presence of expected value and standard deviation of a
project’s NPV by the scenario analysis (Lee and Zhong 2015).
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c. Break-even Analysis
Break-even analysis is considered as a useful tool for studying the relationship
between fixed costs and variable costs and revenue. It is inseparably connected with the
Break Even Point which indicates that at what moment an investment will commence
generating a positive return. The break-even analysis involves in the calculation of the size of
the production at a certain price that is required for covering all the costs incurred. Two major
concepts related to the break-even analysis are fixed cost and variable cost (Morano and
Tajani 2017). Fixed costs are considered as overhead and the occurrence of these costs can be
seen after the commencement of the economic activities. Variable costs are the costs that
change directly with the production volume. Break-even analysis is considered as a handy
tool for deciding in case a company should or should not commence production and selling a
product. For the calculation of break-even point in the break-even analysis, certain data
named fixed costs, selling price of the product and variable cost per product is needed. The
determination of break-even point is done in the point when the fixed costs have been earned
back (Andries, Debackere and Van Looy 2013). This only happens in the presence of the
contribution margin that is the selling price minus the variable costs. Break-even point can be
obtained when fixed costs are divided by the contribution margin.
In this context, it needs to be mentioned that break-even analysis is related to the
components of capital budgeting. It needs to be mentioned that break-even analysis helps in
determining the amount of income a company needs to secure before making profit or before
incurring loss (Burns 2016). The application of the capital budgeting techniques like NPV
and IRR play a crucial role in the determination of profit after that certain level of income
derived from the break-even analysis. This is considered as a major technique in order to
determine the fact that when an investment will be able in generating positive return which is
a crucial information for the investors. This can be determined through graphically or with
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the assistance of simple mathematics. It implies that there is a connection between break-even
analysis and NPV due to the fact that the break-even analysis helps in the determination of
the positive NPV of the investment projects (Svensson 2016). This is majorly helpful for the
investors in undertaking effective investment decisions.
d. Simulation Analysis
Simulation analysis is considered as one of the major techniques that undertakes the
utilization of risk analysis in capital budgeting. The main aim behind the implementation of
simulation analysis is the preparation of a probability profile based on a criterion of merit by
stochastically aggregating the variable values associated with the opted criterion. It needs to
be mentioned that there are certain steps involved in the simulation analysis. Modelling a
project is considered as the first step that shows the relationship of the NPV with the
parameters and exogenous variables (Williams and Dobelman 2017). The next step involves
in the specification of the values of the parameters while assigning probabilities to the
random variables arises from the external factors. After that, it is required to randomly select
any value from the probability distribution of each of the exogenous variables. The next step
involves in the computation of NPV for both the randomly generated values of exogenous
variables and the values of the parameters as specified by the decision maker. The last step
involves in the repetition of the third and fourth stage for obtaining a large number of
simulated values of NPV. It needs to be mentioned that the whole process of the simulation
analysis force the decision maker for considering all the interdependencies as well as
uncertainties that characterize the projects (Arnold and Yildiz 2015). This helps in
determining the project viability based on the number of outcomes as well as the probabilities
realized through a series of performed actions at the time of the simulation analysis.
The above discussion indicates towards the aspect that simulation analysis is
connected with capital budgeting components of NPV and IRR. In the presence of the
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combination of simulation analysis and sensitivity analysis, the sensitivity of NPV as well as
IRR along with different other types of criterion can be determined (Su and Lu 2015). The
project pattern helps in demonstrating the relationship between NPV with different
parameters as well as external variable quantities. These particular parameters are considered
as variable inputs in the decision-making authority. Determination of the NPV of the research
projects matches the stochastically produced values of the external variable quantities (Platon
and Constantinescu 2014). This whole discussion indicates towards the aspect that the
simulation analysis helps in ascertaining the values of the projects while taking into
consideration the capital budgeting concepts of NPV and IRR.
Conclusion
The above discussion indicates towards the importance of sensitivity analysis,
scenario analysis, break-even analysis and simulation analysis in the process of corporate
decision-making of the business organisations. It can be seen from the above discussion that
these particular tools help the managements of the companies in evaluating different parts of
the decision so that they can gain deeper insight in the uncertainties in the investment
projects. The above discussion also indicates towards the crucial aspect that these tools or
concepts have major relation with the capital budgeting components of NPV and IRR
because they play crucial role in the determination of the viability of the investment projects.
This whole analysis explains the crucial fact that the combination of capital budgeting with
the above-mentioned tools help the organizational managers in better decision making
processes through taking into consideration the necessary aspects required for the decision-
making process. At the same time, these capital budgeting components also play a crucial
role in ascertaining the extent of risk of the investment projects. These are the crucial aspects
that the organizational managers are required to take into consideration.
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References
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learning strategy: Business model development under uncertainty. Strategic entrepreneurship
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Arnold, U. and Yildiz, Ö., 2015. Economic risk analysis of decentralized renewable energy
infrastructures–A Monte Carlo Simulation approach. Renewable Energy, 77, pp.227-239.
Burns, P., 2016. Entrepreneurship and small business. Palgrave Macmillan Limited.
Damodaran, A., 2016. Damodaran on valuation: security analysis for investment and
corporate finance (Vol. 324). John Wiley & Sons.
De Grauwe, P. and Grimaldi, M., 2018. The exchange rate in a behavioral finance
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Finnerty, J.D., 2013. Project financing: Asset-based financial engineering. John Wiley &
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Lee, C.W. and Zhong, J., 2015. Financing and risk management of renewable energy projects
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Morano, P. and Tajani, F., 2017. The break-even analysis applied to urban renewal
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private investors. Habitat International, 59, pp.10-20.
Platon, V. and Constantinescu, A., 2014. Monte Carlo Method in risk analysis for investment
projects. Procedia Economics and Finance, 15, pp.393-400.
Su, Y. and Lu, N., 2015. Simulation of game model for supply chain finance credit risk based
on multi-agent. Open Journal of Social Sciences, 3(01), p.31.
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Svensson, L.E., 2016. Cost-benefit analysis of leaning against the wind (No. w21902).
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