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· Respond to 3 posts listed below. Advance the conversation;
provide a real-world application and experiential examples;
· Conceptually discuss your key [most significant] learning
insight or take-away from the selected forum topic comments.
· Responses should be a minimum of 150-250 words, supported
by at least one reference outside of the textbook (use academic
journals), either supporting or refuting the position of the
author of the forum topic response or peer response.
Topic #1: The Cost of Capital
The cost of capital refers to the “cost” a company must incur in
order to use funds towards a new project or investment. The
funds may come from lenders by borrowing the funds, by
financing equity, or by selling bonds or assets. The cost of
capital is expressed as an annual interest rate that the company
will be charged on the capital funds. Therefore, this is the
minimum return a company must be striving for when
undertaking a new project, making a purchase, or making an
investment. Otherwise, they are simply losing money.
The cost of capital is used as the minimum rate of return that
the project must achieve and is also the rate that is used in a
discounted cash flow analysis. If the return of future net cash
flows on an investment or project are greater than the cost of
capital, then the investment or project is worthwhile to the
business. For example, if a project generates a return of 20%
and the cost of capital was estimated at 15%, then this project
has added value to the business.
In addition, the NPV formula can be used to compare multiple
projects using different costs of capital. For instance, Project A

and Project B compared by using 10%, 15%, and 20% costs of
capital. This can allow businesses to see how investing more or
less capital would affect the outcome of the NPV. Just as you
can compare these different costs of capital, you can also add
the element of risk into your calculations by increasing the cost
of capital to reflect a riskier project or investment. Very simply
put, if investment B is riskier than investment A, then you could
compare them with B having a cost of capital at r = 15% and A
having a cost of capital at r= 10% - therefore adjusting for one
project/investment being riskier than the other.
Interestingly, there has been much discussion and debate over
how companies set their cost of capital rates. In the case of
large Fortune 500 companies, they spend hundreds of billions of
dollars per year. If they miscalculate the cost of capital rate on
an investment or project with a difference of even 1%, this
could mean a gain or loss of billions of dollars depending on
which way the value was incorrectly estimated. For example, if
a company plans to invest $52 million dollars into a new project
that is estimated to bring in $10.5 million per year over the next
seven years, and the company incorrectly estimates the cost of
capital by 1%, then you can see by the table below the affect
this small percentage potentially has on the resulting NPV. If
the company assumes a 9% cost of capital rate incorrectly and it
should have been estimated at 10%, then the company may
proceed with a bad investment or project. If they assume the
cost of capital at 10% and in fact it should have been 9%, then
they potentially miss out on a profitable investment opportunity.
When NPV’s are being calculated with incorrect variables, then
it affects the reliability of this decision-making tool. This is not
to say that one improper or missed investment will significantly
impact a business (although it may), but that repeated errors in
calculating the cost of capital could result in an enormous
cumulative loss in potential investment returns over time.

Project A Yields Cash Flow-In of $73.5 million over 7yrs and
has a cost of $52 million
at 10% the NPV = -880,000
at 9% the NPV = +850,000
Therefore, how do companies accurately determine the cost of
capital? Published surveys reveal varying information as to the
preferred method of computing cost of capital. Some surveys
showed greater than 90% of Fortune 100 companies preferred
using “a weighted-average cost of capital” and others revealed
that over 30% of Fortune 500 companies used the “capital asset
pricing model (CAPM)” (Bruner, 1998). However, one
particular survey differed from the previous paper surveys in
that they were conducted by phone and questions/responses
were focused specifically on how cost of capital was estimated
by each of these firms (Bruner, 1998). This survey concluded
that weighted average cost of capital (WACC) based on market
value (instead of book value that looks at debt vs. equity) was
the most popular method and the capital asset pricing model
(CAPM) was the most used model for estimating cost of equity
(Bruner, 1998).
A WACC is a standardized method for evaluating a company’s
cost of capital. It is a “weighted average of individual sources
of capital” that are used for a project or investment (Bruner,
1998). It is expressed by the formula:
WACC = Wdebt (1-t)Kdebt) + (Wpreferred Kpreferred) +
(WequityKequity) (Bruner, 1998)
K = component cost of capital
W = weight of each component as percent of total capital
t = marginal corporate tax rate

The above formula shows three sources of capital, but more may
be added. The capital costs must be those under current market
conditions; the costs should equal the expected internal rate of
return for each source of capital, and the cost of debt value
should be “after tax” to reflect tax deductible interest
(Luehrman, 1997). However, difficulties still arise when
calculating the cost of equity. As stated, the CAPM was most
commonly used, but there were differing opinions on the
variables used in this formula (risk-free rate of return, equity
beta estimates, and market risk premium). This component of
determining equity had the most debate and therefore affects the
results of the WACC depending on which variables were
selected to calculate the CAPM (Dempsey, 2013). The impact of
using differing rates to calculate the WACC mean that there
could potentially result in an unnecessarily wide range from
minimum WACC to maximum WACC having huge potential
economic impact on decision making.
Given the enormous amount of capital used for projects and
investments each year by corporations, the proper assessment of
cost of capital rates is an extremely important concept for
financial analysts and managers. Where there is fairly standard
use of the WACC, the method and rates used to determine cost
of equity using CAPM varies greatly and can cause large
differences in cost of capital estimates (Bruner, 1998).
Therefore, it seems that there should be better guidelines for
calculating this where, based upon industry, standardized,
current averages may be widely used.
References

Bruner, R. F., Eades, K. M., Harris, R. S., & Higgins, R. C.
(1998). Best practices in estimating the cost of capital: survey
and synthesis. Financial Practice and Education, 8, 13-28.
Dempsey, M. (2013). The Capital Asset Pricing Model (CAPM):
The History of a Failed Revolutionary Idea in Finance?.
Abacus, 49(S1), 7-23.
Luehrman, T. A. (1997). What’s it worth. Harvard Business
Review, 75(4), 132-142.
Topic #2: Risk and Diversification
Top of Form
In the realm of investments and financial management, risk is
an important variable that cannot be neglected. There are many
sources of risk in the financial variables of any corporation and
investments. Risk can be political in nature, where the
investments in a specific country can be threatened by political
turmoil or changes. Risk can be market driven, where the new
product lunch may be unsuccessful due to a current competition
[Microsoft surface tablets for example, never captured any
market share and the company was forced to sell the product
below production costs at a loss] (Arthur, 2014). There is also
a risk involved when a new product is introduced to the market
despite previous risk analysis done.
The risk can also stem from investments. In general there are
ten main types of risk associated with investments (Brown,
2008). They are risks associated with interest rates, business,
credit, taxability, call, inflation, liquidity, market, reinvestment
and currency/exchange rate. Business risk is associated with a
specific security which is also known as the unsystematic risk.
In credit risk, the issue is with the bonds issuer, who may not be
able to make the expected payments. In taxability risk, a
security was issued with a tax-exempt status by a municipal

office, however, it may lose that status prior to its maturity. In
inflation risk, the value of the asset may be lost to inflation,
especially if the currency in which it was issued has lost value
since. In liquidity risk, the investor may not be able to
purchase or sell a specific investment in a timely manner or the
optimum time. Market risk or systematic risk [as opposed to
the business risk] is a risk that cannot be controlled by
diversification of the assets. Currency or exchange risk occurs
when the currency in which the assets are purchased may have
lost value, or the desired final currency has increased in value
since the initial purchase. This risk has been common in the
past year. For example Euro was valued as 1.4885USD in May
of 2011 and today it is 1.1734USD. Although the difference
appears to be small [0.31], but when it is measured in millions
of euros the difference is significant.
As Brigham and Houston (2004) explain, diversification is the
single best weapon against risk. They further explain that
“global diversification offers investors an opportunity to raise
returns and at the same time reduce risk” (Brigham, 2004, p.
231). “The process of spreading an investment across assets
[and thereby forming a portfolio] is called diversification”
(Ross, 2000, p. 413). Therefore, we can conclude that
spreading of the investments across many forms of assets will
reduce some of the risks, but will not eliminate the risk all
together. Unsystematic risk [or business risk] is perhaps the
only risk that can be completely eliminated with diversification
of the assets (Ross, 2000, p. 415). In contrast to the
unsystematic risk, systematic risk cannot be eliminated because
it affects all assets to some degree. The systematic risk which
is also known as non-diversifiable risk. In the financial
management, we calculate the total risk by adding systematic
risk to the nonsystematic risk.
Another aspect diversification is in the supply chain. The
management of the company must ensure sufficient supply of

materials in-order to meet the demands of the market
(Bowersox, Closs & Cooper, 2002). To ensure ample and un-
disturbed supply chain of materials, financial managers and
operations must strike a balance between multiple suppliers
(Bowersox et al, 2002, p. 15). An example of this would a
company like Apple who uses many materials for its devices
and hardwares. If the company uses one supplier for its device
displays [the same as investing in one form of asset] and should
that supplier is unable to meet the demands or the promised
screens for number of reasons [such as political turmoil, fire in
the facility, worker strikes] then company [Apple] is unable to
make its products. The same is true in the case of the
company’s product lines. Apple has secured its market
superiority with multiple safety nets [product lines] that can be
viewed as “diversification”. By having a diverse line of
products within an eco-system, Apple has ensured a steady
stream of income regardless of the market changes. At the same
time, Apple has diversified its suppliers across the globe.
Incidentally in 2009, Apple caused a shortage of flash-storages
in Asia which caused other companies including Samsung itself
to scramble to locate parts (Farrell, 2009).
Risk in the business world is unavoidable. Risk in involved in
multiple aspect of the business from the supply chains to market
and also investments. Risk is so important to businesses that
colleges and universities offer specific degrees in Risk
Management and avoidance. Along with sound investments and
planning, risk can be reduced by diversifying the companies
portfolio, assets, supply chains and product lines to name a
few. Diversification breaks down the risk associated buy
reducing the overall probability of the risk (Su & Tsang, 2014).
Doing so ensures that investments the company has made is
secure from risk, that even should a part of the operation is
affected [from a given risk], the whole operation can still
maintain a steady move forward. A low risk enterprise will
therefore becomes a sound investment which in return will

increase the sources of investment in that enterprise [and
therefore reducing yet another risk].
References:
Arthur, C. (2014, May 1). Microsoft Surface tablet is still losing
money, figures show. Retrieved January 19, 2015, from
http://www.theguardian.com/technology/2014/may/01/microsoft
-surface-pc-tablet-losing-money-figures-show
Brigham, E., & Houston, J. (2004). Risk and Rates of Return. In
Fundamentals of financial management (10th ed., p. 231).
Mason, Ohio: Thomson/South-Western.
Brown, K. (2008, June 2). Types of Investment Risks - Series 6
| Investopedia. Retrieved January 19, 2015, from
http://www.investopedia.com/exam-guide/finra-series-
6/evaluation-customers/types-investment-risks.asp
Bowersox, D. J., Closs, D. J., & Cooper, M. B. (2002). Supply
chain logistics management (Vol. 2). New York: McGraw-Hill.
Farrell, N. (2009, September 15). Apple causes NAND shortage
in Asia. Retrieved January 19, 2015, from
http://www.theinquirer.net/inquirer/news/1533511/apple-causes-
nand-shortage-asia
Ross, S., & Westerfield, R. (2000). RETURN, RISK, AND THE
SECURITY MARKET LINE. In Fundamentals of corporate
finance (9th ed., p. 412). Boston: Irwin/McGraw-Hill.
Su, W., & Tsang, E. (2014). Product Diversification and
Financial Performance: The Moderating Role of Secondary
Stakeholders. Academy of Management Journal, amj-2013.
Topic #3: The Monte Carlo Simulation
The Monte Carlo simulation is a simulation that is used in order
to understand the impact of risk and possible uncertainty in
project, financial and cost management. It is also often referred
to as a probability simulation. Though for the purpose of this
paper I will talk about its applications in business and finance it
also has strong applications in engineering, biology and
physical sciences. By definition the Monte Carlo simulation
encompasses "any technique of statistical sampling employed to

approximate solutions to quantitative problems" (Kwak,2007).
A model or a real-life system or situation is developed, and this
model contains certain variables. These variables have different
possible values, represented by a probability distribution
function of the values for each variable. The first item that
one needs to understand though is that when you use any
forecasting model there is a relative uncertainty. This is due to
the fact you are using a model that is planning ahead for the
future. When doing this the analysis is forced to make
assumptions that can range from a possible investment return on
a portfolio to the possible cost of a project. There are also
factors that have to be assumed in this equation such as time. In
order to decide these values the financial manager must
formulate guesses based on historical data and past experiences
rather than actual hard numbers. This creates an overall
uncertainty in the projection.
The question then becomes how do financial managers
estimate the proper ranges of values that can be used when
projecting a project. These ranges are typically based on
experience in the field of typical cost and time frames of
projects. Once this is established the Monte Carlo simulation
can start to come into play. In the Monte Carlo simulation
values are selected at random for each of the tasks to be
analyzed. Based on then on the range of these estimates a model
is calculated based on the random value. The results that are
found are then recorded and the process is then repeated. The
results are typically demonstrated by a graph that shows various
points in a scatter plot format. They also can be displayed in
tables but the graph is the typical model this is normally
accepted and followed. These graphs can at some points have
over 3000 data points to be taken into consideration. It is
important though to note that there are situations where the
numbers are not completely random but this is not always the
case. It is not atypical for a Monte Carlo simulation to be
repeated hundreds or even thousands of times, each time using a
different set of randomly selected values.

Even though at first appearance the Monte Carlo simulation
appears like a firm simulation there are various problems that a
company must be aware of when using this simulation model.
Nawrocki,2001 addressed that fact that the Monte Carlo
simulation does prove very useful in cases where data and
normal analytic models are not available. Outside of this though
the model is flawed. The model often creates more work for the
financial analyst and the results are not always as accurate as
other techniques. The cost in this situation often outweighs the
benefits of using the model. The major driving problem is that
assumptions are made and very few financial managers have the
operations background to make these assumptions. For example
many times this model is used in building projects. It takes a
person with a strong construction background to place proper
cost and time frames. When the model is projected by someone
lacking this background it often skews the numbers. The Monte
Carlo simulation also makes the implication that a company is
operating under conditions of risk and that the financial
manager knows all of the underlying distributions. This is not
typically the case as normally in uncertinatany the distributions
are unknown. In other words the financial manager might be
able to calculate the obvious risk such as broken equipment and
employee sick days, but may not be able to factor in things such
as natural disasters that cannot be predicted. Another downside
as referenced by Whiteside, 2008 is that analyst often take the
Monte Carlo predictions over the historical data. The problem
with this is that historical data is factual where the Monte Carlo
simulation is a set of assumed numbers. It often presents a
problem that people invest more faith in assumed numbers over
actual historical data with true proven values.
There are though positive points for the Monte Carlo method
or else it would not be used in financial management today. It is
a simulation that has lasted a long time in the financial and
other worlds so it has its’ use and merits. One of them
addressed by Whiteside, 2008 is that even though the process is
time consuming once the equations are entered in the computer

system the analysis then becomes easy to run. It produced fast
results that appeal to a broad audience that are capable of
understanding the entire picture over just the individual
elements that are required under most financial systems. This
speed makes this method very attractive as in today’s business
world time is often money. The system also produces a wide
range of numbers which adds strength to any analysis as the
more data you have the stronger the data. The final positive
aspect is the simulations use in other fields. Even though at first
this may not appear to matter in reality it does. When a
financial manager can explain to a biologist how they are
finding their data and that the data shares the same type of
model it becomes a point of similarity. This can help in creating
a bridge between two very different business worlds which is
always an attractive point.
References
Kwak, Y. H., & Ingall, L. (2007). Exploring monte carlo
simulation applications for project management. Risk
Management, 9(1), 44-57.
doi:http://dx.doi.org/10.1057/palgrave.rm.8250017
Nawrocki, D. (2001). The problems with monte carlo
simulation. Journal of Financial Planning, 14(11), 92-103+.
Retrieved from
http://search.proquest.com.proxy.davenport.edu/docview/21755
9045?accountid=40195
Whiteside, James D,I.I., P.E. (2008). A practical application of
monte carlo simulation in forecasting. AACE International
Transactions, , ES41-ES49,ES410-ES412. Retrieved from
http://search.proquest.com.proxy.davenport.edu/docview/20819
3177?accountid=40195
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