Applying markovitz’s portfolio theory to company’s products portfolio analysis and porter’s five forces model industry’s profitability analysis

Applying Markovitz’s portfolio theory to
company’s products portfolio analysis and
Porter’s Five Forces Model industry’s
profitability analysis
David M. Atencia
November 29, 2016

1
Table of figures
Figure 1. Example of companies’ portfolio management analyses (not exhaustive)....... 3
Figure 2. Graphical representation of Porter's five forces model........................................ 4
Figure 3. Potential risk-return relationship (risk-return profile) for the portfolio of the
company. ..................................................................................................................................... 8
Figure 4. Potential risk-return relationship for the portfolio of the company
for different correlation coefficients (ρ =-1, 0, +1). ................................................................ 9
Figure 5. Impacts in the portfolio’s risk-return relationship when changing the risk-return
characteristics............................................................................................................................. 9
Figure 6. The WACC level and the in the portfolio’s risk-return relationship. ................. 10
Figure 7. Evolution of the current company’s products portfolio with increase in sales.11
Figure 8. Impact on the company’s products portfolio risk-return profile with the
introduction of a new product (Product D)............................................................................ 12
Figure 9. Graphical representation of Porter's five forces analysis. ................................. 14
Figure 10. Potential risk-return relationship for the industry.............................................. 15
Figure 11. Potential risk-return relationship for a industry with two competitors. ........... 16
Figure 12. Impact on expected industry’s WACC with changes in competitor expected
return. ......................................................................................................................................... 17
Figure 13. Changes in risk-return relationship for the industry with a new entrant........ 18
Figure 14. Changes in risk-return relationship for the industry with strengthening power
of suppliers................................................................................................................................ 19
Figure 15. Changes in risk-return relationship for the industry with strengthening power
of buyers. ................................................................................................................................... 20

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1. Executive summary
This study provides a first analysis and evaluation of applying Markovitz’s Modern
Portfolio Theory (MPT) to companies’ products portfolio performance. The same
approach is used to assess industries’ profitability and risk based on Porter’s Five
Forces Model (FFM). The analyses are based on mean-variance calculations to
establish the risk-return profile and evaluate different scenarios. Results show that a
company’s product portfolio can be characterized in terms of risk-return metrics,
increasing the financial metrics and framework to assess performance that companies
use for their portfolios. Additionally, the Modern Portfolio Theory equations showed to
be a useful frame to establish an industry’s profitability-risk profile considering the
shaping forces according to Porter’s model.
As a result, the company’s products portfolio analysis shows that MPT allows to
compare the company’s Weighted Average Cost of Capital (WACC) to the expected
return and establish a risk level for the WACC accordingly to the company’s products
portfolio risk-return relationship; analyze the impact in risk-return terms of the current
company’s product portfolio with an increase/decrease in sales of one or several
products; study the impact of the introduction/disinvestment in one or several products
in the company’s products portfolio; segregate the products’ risk-return profile by
categories and/or geographies; and test the sensibility of the risk-return relationship of
the company’s products portfolio to changes in one or several variables in the expected
return of one or several products. In the Porter’s Five Forces Model analysis,
Markovitz’s framework allows to assess an industry’s profitability and associated risk
and the impact of each of the forces (supplier power, buyer power, competitive rivalry,
the threat of substitution, the threat of new entry).
The study is developed using basic formulations and not applying real/detailed data to
the equations. So, further analyses could be elaborated using real market data and
compared with the results obtained here.
2. Introduction
Company’s products portfolio analysis
In any industry is easy to see company’s presentations in investors’ seminary showing
analyses about the company’s brands/products’ portfolio and their category/geography
mix. Normally, statements such as “very diversified and balanced portfolio” are
commonly used, and sales contribution graphics per product and geography are
shown. Also, categories’ analysis is done considering the position of the company,
product in each different category of the market and growth/sales/profit breakdowns
are developed. Additionally, companies also develop a holistic framework of key
metrics, such as growth, margin, capital efficiency, capital allocation, etc, to assess
performance, and these indicators are used to analyze growth strategies, identify
market drivers, establish in which products/category/geography mixes to spend on
marketing or in which products/categories to allocate capital expenditure resources
(see Figure 1).

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Figure 1. Example of companies’ portfolio management analyses (not exhaustive).
Are these analyses flaw? No, quite the contrary. Undoubtedly, all these analyses are
right and must be developed and managed. To put it simple, a company’s value
depends on its portfolio of products. So, one of the biggest challenges faced by
companies is to decide how to invest and in which categories/products to invest to
have a “very diversified and balanced portfolio”. But what do “diversified” and
“balanced” mean. According to the Cambridge Dictionary “balanced” means:
considering all sides or opinions equally, or, another definition, containing an equal
amount or number of similar things or people. And “diversified” means: including a
range of different types of products, investments, etc. in order to reduce risk or
increase the chances of success.
One important question to answer by managers is to decide whether to invest in a few
existing individual or new products, evaluating each in isolation, or take a portfolio
approach. A “portfolio approach” means evaluating individual products in relation to
their contribution to the returns characteristics of the whole portfolio of products.
"Portfolio diversification” helps to avoid disastrous investment outcomes. This benefit is
most convincingly illustrated by examining what may happen when companies relay all
their value in one product, this is they are not diversified.
So, the same way that financial assets are generally defined by their risk and return
characteristics, products in any company’s portfolio should be characterized in the
same way. Comparison along these two dimensions simplifies the process of
managing existing products or creating new ones among different options. The
expression “risk–return trade-off” refers to the positive relationship between expected
risk and return. In other words, a higher return is not possible to attain in efficient
markets/sectors/industries and over long periods of time without accepting higher risk.
Expected returns should be greater for products with greater risk. Thus, by taking a
diversified portfolio approach, managers can spread away some of the risk and be
concerned about the risk–return trade-off of their portfolio. The portfolio approach

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provides a way to reduce the risk associated with companies’ investment decisions
without necessarily decreasing their expected rate of return.
The concept of diversification has been around for a long time and has a great deal of
intuitive appeal. However, the actual theory underlying this basic concept and its
application to investments only emerged in 1952 with the publication of Harry
Markowitz’s classic article on portfolio selection. It’s with this risk–return trade-off and
diversification approach that the analyses will be developed.
Porter’s Five Forces Model industry’s profitability analysis
Porter’s Five Forces Analysis (see Figure 2) is an important tool for assessing the
potential for profitability in an industry. This tool was created by Harvard Business
School professor, Michael Porter, to analyze the attractiveness and likely-profitability of
an industry. Since publication, it has become one of the most important business
strategy tools.
Industry’s profitability framework
Figure 2. Graphical representation of Porter's five forces model
The forces that shape competition in any industry, and its profitability, can be
summarized in five components:
 Supplier Power: The power of suppliers to drive up the prices of inputs;
 Buyer Power: The power of your customers to drive down prices;
 Competitive Rivalry: The strength of competition in the industry;
 The Threat of Substitution: The extent to which different products and
services can be used in place of existing ones;
 The Threat of New Entry: The ease with which new competitors can enter the
market if they see that good profits are made in the industry.
The goal of this methodology is to analyze the attractiveness and sustainable likely-
profitability of an industry in the long term. However, the main “hurdle” of this
methodology is the lack of specific formulation to assess profitability and risk values
associated with the analysis framework. As stated above, a company’s value depends
on its portfolio of products and it is possible to establish risk-return pair of values to the
company. So, the same way that financial assets are generally defined by their risk and
return characteristics, companies competing in a specific industry should be
characterized in the same way. This approach allows to assess the industry’s risk-

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return profile taking into account the impact of the five forces that shape
competitiveness.
3. Modern Portfolio Theory: Basic formulation
A major reason that portfolios can effectively reduce risk is that combining securities
whose returns do not move together provides diversification. Although portfolio
diversification generally does reduce risk, it does not necessarily provide the same
level of risk reduction during times of severe market turmoil as it does when the
economy and markets are operating ‘normally’. In fact, if the economy or markets fail
totally (which has happened numerous times around the world), then diversification is a
false promise. In the face of a worldwide contagion, diversification was ineffective, as
illustrated at the end of 2008.
The concept of diversification has been around for a long time and has a great deal of
intuitive appeal. However, the actual theory underlying this basic concept and its
application to investments only emerged in 1952 with the publication of Harry
Markowitz’s classic article on portfolio selection. The article provided the foundation for
what is now known as modern portfolio theory (MPT). The main conclusion of MPT is
that investors should not only hold portfolios but should also focus on how individual
securities in the portfolios are related to one another. In addition to the diversification
benefits of portfolios to investors, the work of William Sharpe (1964), John Lintner
(1965), and Jack Treynor (1961) demonstrated the role that portfolios play in
determining the appropriate individual asset risk premium (i.e., the return in excess of
the risk-free return expected by investors as compensation for the asset’s risk). In
addition to avoiding a potential disaster associated with over investing in a single
product, portfolios also generally offer equivalent expected returns with lower over-all
volatility of returns—as represented by a measure such as standard deviation.
The aim of this analysis is not to demonstrate the Modern Portfolio Theory formulation,
but its potential application to company’s portfolio products analysis/management. It is
considered that the reader is familiar with this theory, so the formulas that underlie the
theory will be presented quite straight forward. It is also consider that the reader has
got knowledge of basic statistical concepts such as expected return (E(·)), variance
(Var(·)), risk (represented by ), correlation coefficient (ρ), covariance (Cov(·,·)) and
basic relationships among these variables.
Consider a company’s portfolio of N products and Ii designating each of the
investments associated with the different products in the company’s portfolio, with
i=1,2,3,…,N. So, every product in the portfolio has associated a weight (wi) calculated
as Ii/IT, with IT = ΣIi for i=1,2,3,…,N. Likewise, for every product it is defined an
expected return ( ). Every expected return can be defined as a function of its sales
level (ni) price (Pi), Costs (Ci), exchange rates (FXi), taxes (Ti), interests rates (ri) and
any other variables necessary to establish the expected return. When several individual
products are combined into the portfolio, we can compute the portfolio return as a
weighted average of the returns in the portfolio. The portfolio return ( ) is simply a
weighted average of the returns of the individual products,
(1)
(2)
(3)

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(4)
(5)
(6)
with defined by
) (7)
Additionally, to fully characterize a product, it is necessary to associate a measure of
risk. Variance is a measure of the volatility or the dispersion of returns. Higher variance
suggests less predictable returns and therefore a more risky product. Variance is
measured as the average squared deviation from the mean,
(8)
was defined as a function of different variables in (7). So, the variance will be also a
function depending on these variables,
(9)
These means that the volatility associated to each product will depend on the volatility
(variances) of the different variables that define and impact on the products’ expected
return. This simple observation will be useful for later analyses when analyzing the
performance of the portfolio.
Then, the risk associated to the product will be established using the standard
deviation,
(10)
Jointly with other key metrics such as growth, margin, capital efficiency, capital
allocation, etc, defining the risk associated with each product gives a better
understanding of the product’s performance. It is necessary to remember that for each
product, and for the portfolio of products as we will see later, there is “risk–return trade-
off”. In other words, a higher return is not possible to attain in efficient markets and over
long periods of time without accepting higher risk. For example, any company
launching a new product (not existing previously in the market) that turns out to be
successful (profitable in terms defined by the company) will probably be copied by
other companies, impacting in the launching company’s expected return (in relative and
absolute terms) of the product.
Like the portfolio’s return, we can calculate the portfolio’s variance. When computing
the variance of the portfolio’s return, standard statistical methodology can be used by
finding the variance of the full expression of portfolio return. Although the return of a
portfolio is simply a weighted average of the returns of each product, this is not the
case with the standard deviation of a portfolio (unless all products’ expected returns are
perfectly correlated, that is, correlation equals one). Then, considering that the share of
each product in the company’s portfolio (i.e its weight in the portfolio’s expected return)
doesn’t changes and it is perfectly known, the variance can be expressed more
generally as,

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(11)
(12)
(13)
(14)
The same way that was considered for an individual product of the portfolio, the risk
associated to the portfolio of products of the company will be established using the
standard deviation,
(15)
With a risk-return perspective it is possible to analyze the impact of each product in the
company’s risk-return profile and also whether the products have a diversification
effect. To examine how a portfolio with many products works and the ways in which we
can reduce the risk of the portfolio, assume that the portfolio has equal weights (1/N)
for all N products. In addition, assume that and are the average variance and
average covariance. Given equal weights and average variance/covariance, we can
rewrite the portfolio variance as,
(16)
(17)
(17) shows that as N becomes large, the first term on the right side with the
denominator of N becomes smaller and smaller, implying that the contribution of one
asset’s variance to portfolio variance gradually becomes negligible. The second term,
however, approaches the average covariance as N increases. It is reasonable to say
that for portfolios with a large number of products, covariance among the assets
accounts for almost all of the risk for the portfolio of products. The analysis becomes
more instructive and interesting if we assume that all assets in the portfolio have the
same variance and the same correlation among assets. In that case, the portfolio risk
can then be rewritten as,
(18)
The first term in (18) under the root sign becomes negligible as the number of assets in
the portfolio increases leaving the second term (correlation) as the main determining
factor for portfolio risk. If the assets are unrelated to one another, the portfolio can have
close to zero risk. In the next section, we review these concepts to learn how portfolios
can be diversified.
4. Company’s products portfolio risk-return analysis
To continue the analysis, and for simplicity to handle the results, we will consider a
company initially with only 2 products (product A and product B), with defined risk-
return variables. The previous expressions for the portfolio of products simplify to the
following ones,

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(19)
(20)
(21)
Considering the different options for the products’ weight in the company’s portfolio,
this is from a portfolio containing only one of the products to all the possible
combinations of the weights (relative investment) of the products, the risk-return
relationship (risk-return profile) for the portfolio can be represented graphically (see
Figure 3).
Figure 3. Potential risk-return relationship (risk-return profile) for the portfolio of the company.
As can be seen in Figure 3, the extreme points of the curve are represented
considering a portfolio with only one of the products of the company (Point A and Point
B). Between these two points, there all the hypothetical portfolio of products depending
on the weight of each product. Point C represents a theoretical current portfolio of the
company defined by its products’ expected returns and risks. So, what we can see is
that the combination of products in the company’s portfolio results in a higher expected
return than a 100% product B portfolio but in less return when compared to a 100%
Product A portfolio. However, because of the risk diversification effect, the current’s
product portfolio risk is less than that of a 100% Product A portfolio.
In the risk-return relationship, an important factor is the correlation coefficient, defined
for two random variables (x,y) as,
(22)
with,
(23)
Depending on the value of correlation coefficent (from -1 to 1), the relative position for
Point C among the options (risk-return profile) and the potential risk-return scenarios
change (see Figure 4). Depending on the value of correlation coefficient, the risk
ProductsPortfolioReturn
Products Portfolio risk
100% Product A
100% Product B
Current company’s
products portfolio
A
B
C
100% Product A

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associated to the current company’s products portfolio (Point C) reduces to a minimum
(ρ = -1), keeping the expected return. The more negatively correlated the two products
of the company are, the more the risk associated reduces.
Figure 4. Potential risk-return relationship for the portfolio of the company
for different correlation coefficients (ρ =-1, 0, +1).
For two given products, accepting that the expected return and risk sources and values
don’t change, the portfolio’s risk-return relationship doesn’t change. Consequently, this
means that different portfolio scenarios (risk-returns associated) can be analyzed.
However, changes in the risk-return values in any of the products of the company’s
portfolio will change also the portfolio’s risk-return relationship. As an example, Figure
5 shows how the portfolio’s risk-return relationship modifies (without changing the
correlation coefficient) when for Product A changes: 1) the expected return and 2) the
risk associated. But remember, in practice changes in return should trigger changes in
risk and vice versa. So, a combination of changes in both variables should happen at
the same time.
Figure 5. Impacts in the portfolio’s risk-return relationship when changing the risk-return characteristics.
100% Product A
100% Product B
Current company’s
products portfolio
A
B
C
ρ = 1ρ = 0ρ = -1
100% Product B
A
C
B
100% Product A
Current company’s
products portfolio
Increase in
expected return
Increase in risk

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As shown in Figure 5, changing Product A’s expected return changes the current
company’s products portfolio expected return proportionally to its weight in the portfolio.
An increase in Product A’s expected return will increase the current company’s
products portfolio expected return and, consequently, a decrease in Product A’s
expected return will decrease the current company’s products portfolio expected return.
On the other hand, changing Product A’s risk also changes the current company’s
products portfolio risk. An increase in Product A’s risk will increase the current
company’s products portfolio risk and, consequently, a decrease in Product A’s risk will
decrease the current company’s products portfolio risk. However, this time the changes
are not only proportionally to its weight in the portfolio (see proportion factor in (24)),
(24)
Once we have characterized the risk-return profiles of the company’s products and
established the potential risk-return relationship of the company’s products portfolio, we
can develop different applications/analysis:
 Compare the company’s expected Weighted Average Cost of Capital (WACC) to the
expected return of the company’s portfolio and establish a risk level for the WACC
accordingly to the company’s products portfolio risk-return relationship;
 Analyze the impact in risk-return terms of the current company’s product portfolio
with an increase/decrease in sales of one or several products;
 Study the impact of the introduction/disinvestment in one or several products in the
company’s products portfolio;
 Segregate the products’ risk-return profile by categories and/or geographies;
 Test the sensibility of the risk-return relationship of the company’s products portfolio
to changes in one or several variables in the expected return.
Weighted Average Cost of Capital (WACC) analysis
A risk-return approach in the company’s products portfolio allows to analyze and to
compare the portfolios’ expected return-risk profile with the expected Weighted
Average Cost of Capital (WACC) of the company. Additionally, it is possible to
associate a level of risk when targeting a specific WACC given the company’s current
risk-return relationship (see Figure 6).
Figure 6. The WACC level and the in the portfolio’s risk-return relationship.
100% Product B
Current company’s
products portfolio
A
B
100% Product A
C
σWACC
Current company’s
products portfolio Expected company’s
WACC

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As shown in Figure 6, introducing the company’s expected WACC level as an expected
return allows comparing the performance of our products portfolio and the expected
WACC. In this example, the current company’s products portfolio expected return
(Point C) would be above the expected WACC, so the company is creating value
through its products portfolio performance. At the same time, it can be seen that the
responsible for creating that excess of value is Product A and that Product B is
underperforming. Moreover, using the risk-return relationship of the company’s
products portfolio it is also possible to settle a risk for the companies expected WACC
(σWACC) accordingly with the company’s products profile and characteristics (in risk-
return terms).
Figure 7. Evolution of the current company’s products portfolio with increase in sales.
Increase/decrease in sales
Consider that for example Product A has an unexpected increase in sales (nA). As
established in (7), besides sales, the expected return depends on other variables such
as price, costs, etc. However, considering that the other variables remain the same,
with no changes, the impact on the expected return of Product A will be an increase
and, consequently, an increase in the expected return of the company’s products
portfolio (see Figure 7) . The same reasoning can be done for a decrease in sales for
any of the products.
Introduction/disinvestment of products
One of the most interesting analyses that can be done with the risk-return portfolio
approach is assessing impact of the introduction/disinvestment of a product. In the
case of disinvestment, considering that we have only two products in our portfolio, the
result is very simple: the new risk-return values for the company’s products portfolio will
be that of the remaining product. In our example, let’s consider that the company
disinvest in Product B (the less profitable one, however the less risky). So, the new
current company’s products portfolio risk-return values (Product C) will be the same as
that of Product A.
Let’s consider now that the company wants to invest and introduce a new product
(Product D). Let’s consider too that the existing products (Product A and Product B)
represent each 50% of the company’s investments and that the company wants to
invest an equal amount of money in Product D. So, as a result, each of the products
A 100% Product A
100% Product B
Current company’s
products portfolio
B
C
Increase in sales for
Product A

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will have approximately a 33% weight in the new company’s portfolio. Product A and
Product B correlation coefficient equals -0,5 and Product D isn’t correlated with any of
them (ρAD=0 and ρBD=0). This is, Product D doesn’t modifies risk through the
covariance with Product A or Product B. Finally, consider that return and risk for the
new product (Product D) are the average values of Product A`s and Product B’s
expected return and risk, respectively. This last premise is to facilitate the
understanding of the impacts. Product D’s could take any values for expected return
and risk.
Figure 8. Impact on the company’s products portfolio risk-return profile with the introduction of a new
product (Product D).
The results are presented in Figure 8. Small points in the figure represent all potential
risk-return scenarios considering Product A, Product B and Product D. The dashed line
represents the new company’s products portfolio risk-return relationship (minimum-
variance frontier in Markowitz’s Modern Portfolio Theory) including Point D. Because
we decided to establish Product D’s expected return as the average expected return of
Point A and Point B’s expected return, the new company’s products portfolio keeps the
same expected return. However, because Product D’s risk value is the average risk
between Product A and Product B and because the correlation coefficient between
Product D and both Product A and Product B, the new company’s products portfolio
risk reduces (moves to the left).
As presented, these results will vary depending on Product D’s characteristics (risk-
return profile). However, this methodology permits to analyze the impact of
introducing/disinvesting in any product of the company.
Categories and/or geographies analyses
Another application of this methodology is to segregate the risk-return company’s
products portfolio profile by categories and/or geographies. Let’s remember how the
total expected return for the company’s products portfolio is calculated,
(25)
(26)
A 100% Product A
B 100% Product B
D 100% Product DCurrent company’s
products portfolioC
New company’s
products portfolio
C’

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(27)
(28)
These expressions can be rearranged considering products by geography, for
instance. If we group products by geographies, expected return for the category can be
calculated as the average expected return for all the products in that region,
(29)
with NA being the total number of products in geography A. So the expected return for
products in geography A can be represented as
(30)
If the company operates in M geographies, then the company’s products portfolio
expected return in terms of geography can be represented as
(31)
(32)
(33)
(33) expresses the company’s products portfolio expected return in terms of
geography. Analogously, the risk can also be expressed in terms of geography. Let’s
consider the following expression for the portfolio’s variance,
(34)
As the expected return can be grouped by geographies, the corresponding variances
can also be grouped,
(35)
(35) can be interpreted as follows: the total variance of the company’s products
portfolio is a weighted average of the variances of the geographies ( ) plus a
“cross-border” variance between each of the geographies and the other geographies
(sum of the covariance terms in each category ). So, the risk for the
company’s products portfolio will be,
(36)
This kind of analysis can be useful to establish risk-return profiles by geographies for
the company’s products. The same analysis, with an analog reasoning, can be
developed for a category analysis.
Sensibility analysis of variables
A particular case for this analysis was presented in the Increase/decrease in sales
section.

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) (37)
(38)
Sensibility analyses can be carried out for any of the variables that impact on the
expected return and risk. These analyses can be performed considering one variable at
a time or taking into account several variables.
5. Industry’s profitability(return)-risk analysis
Porter’s model works by looking at the strength of five important forces that affect
competition and that effectively impact on the industry’s profitability:
 Supplier Power: The power of suppliers to drive up the prices of inputs;
 Buyer Power: The power of your customers to drive down prices;
 Competitive Rivalry: The strength of competition in the industry;
 The Threat of Substitution: The extent to which different products and services
can be used in place of existing ones;
 The Threat of New Entry: The ease with which new competitors can enter the
market if they see that good profits are made in the industry.
A summary of different drivers/causes that can be considered when analyzing each of
the forces in the industry’s analysis is presented in Figure 9.
Figure 9. Graphical representation of Porter's five forces analysis.
Understanding the competitive forces, and their underlying causes, reveals the base of
an industry’s current profitability while providing a framework for anticipating and
influencing competition (and profitability) over time.

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But the big question is how to model the industry’s profitability and its associated risk?
The answer is using the Markovitz’s Modern Portfolio Theory. Consider that in an
industry exist N players and each one has got an expected return ( ) and an
associated variance, , defining a certain level of risk defined by
, with i=1,2,3,…,N. As establish before for a company’s products portfolio, an
industry can be modeled as a portfolio that includes all the assets in the industry, in this
case all the companies that play in that specific industry. So, on the one hand, the
expected return (profitability) of that industry can be established as the weighted
average of the returns of the different players. The weight for each company in the
industry will be established considering the company’s invested capital (equity and
debt) relative to the total invested capital in the industry (i.e. the sum of the invested
capital in the companies of the industry). So, every company in the industry has
associated a weight (wi) calculated as Ii/IT, with IT = ΣIi for i=1,2,3,…,N. And, on the
other hand, the risk associated to the expected return of the industry is defined by the
combined variance of the expected returns of all the players in the industry. It’s also
useful to remember at this point, that the expected return and, hence, variance/risk of
the players can be modeled using several variables such as its sales level (ni) price
(Pi), Costs (Ci), exchange rates (FXi), taxes (Ti), interests rates (ri), etc. Putting all
together, an industry’s expected return-risk profile could be defined with the following
equations,
(39)
(40)
(41)
(42)
) (43)
(44)
Figure 10. Potential risk-return relationship for the industry.
IndustryExpectedReturn
Industry risk

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Figure 10 shows the graphical representation for equations (40) and (42). The points
represent all the possible combinations for the industry’s risk-expected return
(profitability) scenarios. The continuous line represents the new company’s products
portfolio risk-return relationship (minimum-variance frontier in Markowitz’s Modern
Portfolio Theory).
As was done before, for simplicity, we will consider that there are only two competitors
in an industry (Company A and Company B). The previous expressions for the
industry’s expected return ( and risk ( ) simplify to the following ones,
(45)
(46)
(47)
(48)
Figure 11 shows the potential risk-return industry’s profile considering two competitors
with given specific characteristics (values) for expected return, risk and correlation
coefficient (Point A and point B). Point C identifies the current industry’s position in
terms of risk and profitability considering competitors’ risk-return profiles and weight
(market share in terms of investments). Considering that the industry’s risk-return
relationship applies, changes in the forces that drive competition can be modeled and
their impact in the industry’s profitability (and risk) established.
Figure 11. Potential risk-return relationship for a industry with two competitors.
The expected return (profitability) associated with the industry’s current position can be
understood as the expected Weighted Average Cost of Capital (WACC) for the industry
as a whole. Because the investment associated with each company considers equity
investments and debt investments, the expected return for the industry can be
associated with a WACC measure. At the same time, the risk associated with the
industry’s current position would be the risk associated with the industry’s profitability
and consequently with the industry’s expected WACC. This doesn’t mean that all
players target that specific expected WACC but it is the average value for that industry
in the current conditions. Changes in any of the players current conditions (expected
Industry risk
Profitability
100% Product A
100% Company B
Current industry’s
position
A
B
C
100% Company A
σIndustry
RIndustry
Risk

17
return, risk or even correlation coefficient with other competitors) will change the
industry’s current position.
Figure 12. Impact on expected industry’s WACC with changes in competitor expected return.
As an example, in Figure 12 is shown how a change in Company A’s expected return
impacts in the expected profitability (WACC) of the industry. Because the change is
only in Company A’s expected return (no changes in terms of risk, weight or correlation
coefficient), the current industry’s position is only affected in terms of return. So, an
increase in Company’s A expected return increases the expected WACC for the
industry keeping the same level of risk for that expected WACC.
But how changes in the shaping forces of the industry can impact in the expected risk-
return profile and its current position? As mentioned before, there are five forces that
shape the industry competitiveness, hence its expected return and risk: the threat of
new entry, the power of suppliers, the power of buyers, the threat of substitutes, rivalry
among existing competitors. Changes in any of the forces can happen independently or
simultaneously. However, for analysis purposes, the effects of each force will be
presented independently.
The threat of new entry
New entrants to an industry introduce new capacity (offer for the market) and target to
gain market share, putting downward pressure on prices and costs. It also increases
the level of investments necessary to compete (investments in marketing, R&D, new
technologies, etc). Therefore, the threat of new entrants tends to lower the potential
profit of an industry.
Let’s consider an industry with only two competitors (see Figure 11). A new entrant in
the industry’s risk-return relationship and its current industry’s position (in terms of risk
and expected return) would have two impacts: firstly, the weight (industry’s share in
terms of investments) of each competitor would be redistributed, so the risk-return
relationship for the industry would be modified. And secondly, the return for the existent
players could be expected to be lower. Changes in risk terms for the existing
competitors in the industry should be expected, but these changes would depend on
how prices and costs are affected. So changes in existing competitors’ risk will not be
represented here, but should also be expected.
Industry risk
C’
100% Company A
100% Company A
position
C
New industry’s
position
A
A’
B
100% Company B
Expected industry’s WACC
σIndustry
New Expected
industry’s WACC

18
A potential modeling for this case is shown in Figure 13. As did in the Company’s
products portfolio risk-return analysis, let’s consider that the existing companies
(Company A and Company B) represent each 50% of the industry’s investments and
that the new entrant wants to invest an equal amount of money to develop its business.
So, as a result, each of the products will have approximately a 33% weight in the
industry. Company A and Company B correlation coefficient equals -0,5 and Company
D isn’t correlated with any of them (ρAD=0 and ρBD=0). This is, company D doesn’t
modifies risk through the covariance with Company A or Company B. Finally, consider
that because of the threat of the new entrant, Company A and Company B reduce their
expected return (trough prices reduction) 10%. Then, for simplicity, we will assume that
expected return and risk for Company D are the average values of Company A`s and
Company B’s expected return and risk, respectively.
Figure 13. Changes in risk-return relationship for the industry with a new entrant.
A potential modeling for this case is shown in Figure 13. As did in the Company’s
products portfolio risk-return analysis, let’s consider that the existing companies
(Company A and Company B) represent each 50% of the industry’s investments and
that the new entrant wants to invest an equal amount of money to develop its business.
So, as a result, each of the products will have approximately a 33% weight in the
industry. Company A and Company B correlation coefficient equals -0,5 and Company
D isn’t correlated with any of them (ρAD=0 and ρBD=0). This is, company D doesn’t
modifies risk through the covariance with Company A or Company B. Finally, consider
that because of the threat of the new entrant, Company A and Company B reduce their
expected return (trough prices reduction) 10%. Then, for simplicity, we will assume that
expected return and risk for Company D are the average values of Company A`s and
Company B’s expected return and risk, respectively.
Small points in Figure 13 represent all potential risk-return scenarios considering
Company A, Company B and Company D. The dashed line represents the new
company’s products portfolio risk-return relationship (minimum-variance frontier in
Markowitz’s Modern Portfolio Theory) including Company D in the industry. Because of
the premises used, the current industry’s position moves to the left and down. This is,
the introduction of averaged-risk Company D in the industry, simultaneously with a
downward pressure on market prices, lowers the expectations for profitability in the
industry with a reduction of risk (diversification effect) because of Company D’s
characteristics. Different results and behaviors in the risk-return profile can be obtained
by changing the premises.
Industry risk
C’
100% Company A
100% Company A
position
C
New industry’s
position
A
A’
B
100% Company B
D
B
100% Company B
σIndustry
RIndustry 100% Company D

19
The power of suppliers
In some cases, powerful suppliers can create more value for themselves by charging
higher prices, limiting quality or services, or shifting costs to industry participants. In
some other cases, suppliers receive strong pressure from customers to continuously
reduce costs and improve service level. In any case, an industry’s supplier power of
bargaining with their customers impacts in the industry’s expected return and risk. At
the same time, suppliers’ costs and negotiating power can be not evenly distributed
among industry’s competitors. This is, market leaders will have better negotiating
conditions (for example, because of sales share in the market) than the other
competitors. So, market leaders could put pressure on costs keeping service levels
agreements to limit risks.
Additionally, industries with very profitable perspectives can trigger strong suppliers to
enter the industry. This case would be the one presented in the previous section.
Figure 14. Changes in risk-return relationship for the industry with strengthening power of suppliers..
Figure 14 shows the example of how the industry’s risk-return relationship modifies
when Company B’s supplier put pressure on the company’s costs. Let’s say that
Company A position (risk-return values) is not affected because its leading position in
the market. Considering that the risks remain the same, an increase in costs from
suppliers in Company B translates in the current industry’s position moving down,
hence reducing the industry’s profitability.
The power of buyers
Customers can force prices down by playing industry participants off against one
another. Besides, demanding better quality or more service can also drive up costs, all
at the expense of industry profitability. Buyers can be powerful if they have negotiating
leverage relative to industry participants, especially if they are price sensitive.
Figure 15 shows an example of the changes in the industry’s risk-return relationship
and in its current position in risk-return terms when buyers can drive prices down.
Putting pressure on prices, without changing costs, lowers expected returns for all
players in the industry. In this case, Company A depicts a smaller sensibility with prices
than Company B, whose expected return suffers the greatest reduction.
Industry risk
100% Company ACurrent industry’s
position
C
A
B
100% Company B
B’
100% Company B
New industry’s
position
C’
σIndustry
RIndustry

20
Figure 15. Changes in risk-return relationship for the industry with strengthening power of buyers.
The above mentioned changes make the industry’s profitability go down and the
industry’s risk-return relationship be modified.
The threat of substitutes
A substitute can produce a great change in the expected return (profitability) for an
industry by a different means. When the threat of substitutes is high, industry
profitability goes down because of diminishing sales or even because of putting a
ceiling on prices. If an industry does not distance itself from substitutes through product
performance, marketing, or other means, it will suffer in terms of profitability. So,
substitutes can have, except for differentiation strategies among participants in the
industry, a general impact on players’ expected return, driving down the expected
profitability for the industry. The changes in the industry’s risk-return relationship would
be similar to those resulting from an increase in the power of suppliers (see Figure 15)
Rivalry among existing competitors
Rivalry among existing competitors takes many familiar forms, including price
discounting, new product introductions, advertising campaigns, and service
improvements. High rivalry limits the profitability of an industry. The degree to which
rivalry drives down an industry’s profit potential depends, first, on the intensity with
which companies compete and, second, on the basis on which they compete. The
strength of rivalry reflects not just the intensity of competition but also the basis of
competition. The dimensions on which competition takes place, and whether rivals
converge to compete on the same dimensions, have a major influence on profitability
and the industry’s risk. Rivalry is especially destructive to profitability if it gravitates
solely to price because price competition transfers profits directly from an industry to its
customers. Price cuts are usually easy for competitors to see and match, making
successive rounds of retaliation likely.
Industry risk
100% Company A
position
C
A
B 100% Company B
B’ 100% Company B
New industry’s
position
C’
σIndustry
RIndustry

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