IMPLEMENTATION OF A VALUATION MODEL. CASE STUDY: NEXT PLC

IMPLEMENTATION OF A VALUATION
MODEL. CASE STUDY: NEXT PLC
Word count: 23035

Nikolas Wuylens
Student number : 000140831569

Promotor: Prof. Dr. Els De Wielemaker

Master’s Dissertation submitted to obtain the degree of:

Master in Business Engineering: Finance

Academic year: 2018-2019

PERMISSION

I declare that the content of this Master’s Dissertation may be consulted and/or reproduced, provided
that the source is referenced.

Signature

Nikolas Wuylens, June 2019

Foreword
This master’s dissertation has been written to fulfil the graduation requirements of the ‘Master of
Science in Business Engineering: main subject Finance’. The goal of this assignment is to test whether
I’m capable to independently conduct research.

My decision to conduct a study on valuation practices was made fairly quick. It is an area in which I
intend to specialize by enrolling for a postgraduate in Finance. After a constructive meeting with Prof.
Dr. Els De Wielemaker, we decided that I was going to develop a valuation model, which incorporates
multiple existing valuation approaches.

This thesis would not have been possible without the assistance of several people.

First and foremost, I thank Prof. Dr. Els De Wielemaker for providing me with the possibility to write
about this topic, and guiding me towards the desired result. Additionally, I like to thank Erik Gjymshana
for the close monitoring.

I also want to thank friends and family, more specifically my mother, for providing the ideal conditions
for me to complete this thesis.

 I

Table of contents

Inhoud
Foreword ....................................................................................................................................................... I

List of used abbreviations ........................................................................................................................... III

List of tables ................................................................................................................................................. V

List of figures ............................................................................................................................................... VI

1. Introduction.......................................................................................................................................... 1

2. Literature review .................................................................................................................................. 3

 2.1. Introduction.................................................................................................................................. 3

 2.2. Practical use of valuation approaches.......................................................................................... 3

 2.3. Key valuation methods ................................................................................................................. 5

 2.4. Relative valuation ......................................................................................................................... 5

 2.4.1. Introduction .......................................................................................................................... 5

 2.4.2. Multiples ............................................................................................................................... 6

 2.5. Intrinsic valuation ....................................................................................................................... 10

 2.5.1. Introduction ........................................................................................................................ 10

 2.5.2. Building blocks of intrinsic valuation .................................................................................. 11

 2.5.3. Dividend Discount Model ................................................................................................... 22

 2.5.4. The equity DCF method ...................................................................................................... 24

 2.5.5. The entity DCF method....................................................................................................... 24

 2.5.6. Practical applicability of the intrinsic methods .................................................................. 27

 2.6. Options ....................................................................................................................................... 28

 2.6.1. Option basics ...................................................................................................................... 28

 2.6.2. Variables influencing option value ..................................................................................... 29

 2.6.3. Option pricing models ........................................................................................................ 29

2.7. Recap of the intrinsic methods .................................................................................................. 31

3. Research ............................................................................................................................................. 33

 3.1. Aim of the research .................................................................................................................... 33

 3.2. Research methodology............................................................................................................... 33

 3.2.1. Conceptual model .............................................................................................................. 33

 3.2.2. Data research ..................................................................................................................... 43

4. Case Study: NEXT Plc .......................................................................................................................... 44

 4.1. The financials .............................................................................................................................. 44

 4.1.1. Industry & regional breakdown.......................................................................................... 44

 4.1.2. The cost parameters........................................................................................................... 45

 4.1.3. The financial input .............................................................................................................. 46

 4.1.4. Conversion of operating leases .......................................................................................... 47

 4.1.5. Market value of interest-bearing debt ............................................................................... 48

 4.2. Valuation methods ..................................................................................................................... 48

 4.2.1. Choice of intrinsic method ................................................................................................. 49

 4.2.2. The entity DCF method....................................................................................................... 50

 4.2.3. Relative valuation ............................................................................................................... 52

 4.2.4. Valuation summarized........................................................................................................ 55

5. Conclusion and directions for further research ................................................................................. 57

6. Reference list ...................................................................................................................................... VII

7. Attachments ....................................................................................................................................... XII

List of used abbreviations
B-S = Black-Scholes

BV(E) = Book value of equity

BV(D) = Book value of debt

CDS = Credit Default Swap

CF = Cashflow

COD = Cost of Debt

COE = Cost of Equity

CRP = Country Risk Premium

DDM = Dividend Discount Model

DCF = Discounted Cash Flow

D/E = Debt-to-Equity ratio

EBIT = Earnings Before Interest and Taxes

EBITDA = Earnings Before Interest, Taxes, Depreciation and Amortization

EPS = Earnings Per Share

ERP = Equity Risk Premium

EVA = Economic Value Added

EV/EBITDA = Enterprise Value-to-Earnings Before Interest, Taxes, Depreciation and Amortization

FCFF = Free Cash flow to the Firm

FCFE = Free Cash flow to Equity

IPO = Initial Public Offering

M&A = Merger & Acquisition

PBV = Price-to-Book value
 III

P/E = Price-to-Earnings

ROI = Return On Investment

R&D = Research & Development

TTM = Trailing Twelve Months

WACC = Weighted Average Cost of Capital

WC = Working Capital

 IV

List of tables
Table 1: Use of valuation approaches .......................................................................................................... 3
Table 2: Key valuation methods ................................................................................................................... 5
Table 3: Most used multiples ....................................................................................................................... 7
Table 4: Comparable characteristics ............................................................................................................ 8
Table 5: NEXT industry & regional breakdown .......................................................................................... 45
Table 6: NEXT Cost parameters .................................................................................................................. 46
Table 7: NEXT financials ............................................................................................................................. 46
Table 8: NEXT operating lease commitments ............................................................................................ 47
Table 9: Adjustments after conversion of operating leases....................................................................... 48
Table 10: NEXT market value of interest-bearing debt .............................................................................. 48
Table 11: NEXT fundamentals .................................................................................................................... 49
Table 12: NEXT fundamentals (after normalisation) .................................................................................. 50
Table 13: NEXT fundamentals in lower and upper bound scenario ........................................................... 51
Table 14: NEXT entity DCF share prices ..................................................................................................... 52
Table 15: ABF financial characteristics ....................................................................................................... 53
Table 16: H&M financial characteristics..................................................................................................... 53
Table 17: B&M financial characteristics ..................................................................................................... 53
Table 18: Williams-Sonoma financial characteristics ................................................................................. 54
Table 19: Multiples used ............................................................................................................................ 54
Table 20: NEXT share prices from multiples .............................................................................................. 54
Table 21: FCFF computation best estimate ................................................................................................ XII
Table 22:FCFF computation upper bound ................................................................................................. XIII
Table 23: FCFF computation lower bound ................................................................................................ XIII

 V

List of figures
Figure 1: Sensitivity risk-free rate .............................................................................................................. 52
Figure 2: Valuation summarized................................................................................................................. 55

 VI

1. Introduction
There are two opposing views on how a firm should be valued. One group argues that due to the
extensive amount of assumptions that have to be made, valuation approaches rarely yield precise
results. Therefore, this group states that valuation is more a story than a mathematical phenom. The
other group states that a good valuation is based on solid numbers. This group recognizes the fact that
plenty of assumptions have to be made. Nevertheless, by analysing the impact of changes in these
assumptions, a viable range of values is obtained. In this dissertation, the focus is put on the number
side of valuation.

There are four main approaches to value a firm and by extension assets in general: asset-based
valuation, intrinsic valuation, relative valuation and contingent claim valuation. Extensive research has
been on conducted on each approach, which led to clear theoretical definitions of these approaches.
Asset-based valuation assumes that assets are easily separable and that an active market exists for each
asset. A valuation of the firm is then obtained by summing up the value of its assets. All intrinsic value
methods are based on the idea that an asset generates cashflows in the future. Discounting these future
cashflows back to the present, leads to the current value of an asset. It is the soundest approach from a
technical point of view. Nevertheless, intrinsic methods require an extensive amount of assumptions.
Relative valuation is based on the notion that for every firm, other firms with similar assets can be found
on the market. Multiples are used to compare the assets among firms. A multiple is a ratio which has
the price of an asset in its numerator and the cashflows resulting from an asset in its denominator.
Practitioners find relative valuation attractive due to its simplistic character. Nevertheless, multiples
have the same buildings blocks as intrinsic methods and are, therefore, based on the same assumptions.
Certain theorists criticize the methods above on the fact that these methods do not account for certain
options embedded in assets (e.g., option to delay). Contingent claim valuation deals with this criticism.
Nevertheless, this approach is more of a theoretical paradigm.

Relative and intrinsic valuation are the two dominant approaches to value a firm in practice. However,
these methods require numerous assumptions. People who are unfamiliar with valuation practices tend
to forget about all these assumptions. However, misinterpreting assumptions can cause extremely
skewed valuation outcomes. The goal of this dissertation is to bridge the ‘complexity’ gap for non-
valuation experts. To achieve this goal, I will try to create a model that is as user-friendly. Additionally, I
will try to incorporate as few financials in the model. For the model to be user-friendly, it should require

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only standard input that can be obtained without specific knowledge of valuation practices. Additionally,
to limit the number of financials on which the valuation is based, the ones that drive the valuation
outcome the most, have to be isolated.

The remainder of this thesis is structured as follows. In section 2, a review of the current literature is
given. This literature review is split into two parts. First of all, information is gathered on the popularity
of each approach. The goal of this part is to identify the approaches that should be present in the self-
created model. Secondly, the most popular approaches are split up and discussed. In section 3, the
conceptual model and data present in the conceptual model are outlined. After, a case study is
presented which uses the model to value a company, more specific NEXT Plc. Finally, conclusions and
suggestions for further research are presented in section 5.

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2. Literature review
 2.1. Introduction
The goal of the literature review is to outline the framework for the model I will create. The literature
review is organised as followed. First of all, an elaboration on the use of valuation approaches in
practice is given. Secondly, a summary of the different types of valuation approaches is shown in section
2.3. These types are then be split up and each discussed separately. In section 2.4. relative valuation is
handled, section 2.5 elaborates on intrinsic valuation and section 2.6 gives a brief overview on option
pricing models. Finally, the intrinsic methods are summarized in section 2.7, since these methods are
the most important building block of the valuation model created in association with this dissertation.

 2.2. Practical use of valuation approaches
Pinto, Robinson & Stowe (2015) surveyed 13.478 CFA professionals concerning their daily use of
valuation approaches. 2.378 professionals filled in the survey. After elimination of invalid responses,
1.980 valid responses remained. The findings are summarized in the table below.

 Approaches used Percentage of respondents Conditional use
 Market multiples 92.80% 68.80%
 Discounted value 78.80% 59.50%
 Asset based 61.40% 36.80%
 (real) Options 5.00% 20.70%
 other 12.40% 58.10%

 Table 1: Use of valuation approaches

The ‘Percentage of respondents’ column gives an overview on how many analysts use a certain
approach on a frequent basis. A staggering 92,8 % of the respondents uses a market multiples approach.
Discounted value approaches (e.g., Discounted Cash Flow model (DCF)) and asset based approaches
(e.g., Liquidation value model) are used respectively by 78,8% and 61,4% of the respondents. real option
approaches are merely used, despite its increasing popularity as an alternative to traditional valuation
approaches, especially in today’s highly uncertain environment (Wooster, Blanco, &Sawyer, 2016; Xiong
& Zhang, 2016; Collan, Haahtela, &Kyläheiko, 2016). Earlier studies like the one by Block (2007) confirm
this low use of real option approaches. MacMillan and van Putten (2004) state that no matter how
sophisticated a method, valuation is wrong. Therefore, all time spent on complex valuation approaches
is time wasted. This might be a reason why real option approaches aren’t used frequently in practice.

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Finally, under ‘Other approaches’ respondents mentioned other techniques than the ones mentioned
above. (e.g., Leveraged buyout (LBO) analysis, multifactor models, etc.)

The ‘Conditional use’ column represents information on the conditional use of valuation approaches.
Conditional use is the amount of times a certain approach is used, considering an analyst uses the
approach. Therefore, it provides insight on whether analysts see the approach as generally applicable or
as more case-specific. A broadly applicable approach has a conditional use of more than 50 % (50% is
the in benchmark in the study). As a result, market multiples and discounted value approaches are
considered general methods. Whereas, the other tools are more specific in use. Note that the
conditional use of other approaches is also above 50%. Nevertheless, very few analysts use these other
approaches. Therefore, these approaches are not considered general methods.

Bancel and Mittoo (2014) obtain similar results. They surveyed 365 CFA professionals regarding their use
of relative valuation (multiples) and intrinsic valuation (discounted value) approaches. Their conclusion
is similar to the one of Pinto et al. (2015), market multiples are the most frequently used in practice.
Approximately 81% of the respondents uses market multiples. Whereas, 78% of the respondents uses a
Free Cash Flow to the Firm (FCFF) model for valuation. Other DCF alternatives like Free Cash Flow to
Equity (FCFE) models and Dividend Discount Models (DDM) are less popular. Bancel and Mittoo (2014)
also questioned the professionals how much different models they use to complete one valuation
assignment. The majority (81%) uses either one, two or three different techniques. Brown, Call, Clement
and Sharp (2015) questioned sell-side analysts on their use of valuation approaches. Sell-side analysts
are analysts who advise companies at the sell side of either a merger or acquisition deal. They report
that 61% of all respondents (N = 181) very frequently use a Price-to-Earnings multiple (P/E). DCF models
are utilized very frequently by 60% of the respondents.

These different studies clearly prove the dominance of relative and intrinsic valuation. Therefore, this
dissertation focuses on these techniques. Accordingly, the valuation model accompanying this
dissertation contains both relative and intrinsic valuation methods.

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2.3. Key valuation methods
Asset-based valuation Relative valuation Intrinsic valuation Contingent claim valuation
 Liquidation value Market multiples Entity DCF Black-Scholes (B-S)
 Sum of parts value Recent transactions Adjusted Present Value (APV) Decision Trees
 Economic Value Added
 Equity DCF
 Dividend Discount Model

 Table 2: Key valuation methods

As outlined in the introduction (Cf. supra), there are four main areas in which valuation methods can be
categorized. In the following sections only intrinsic and relative valuation are discussed, due to their
relevance for the framework of the valuation model.

 2.4. Relative valuation
 2.4.1. Introduction
Relative valuation is based on the principle that firms/assets have identical characteristics. The more
similar these characteristics, the more equal the value of the assets should be. Multiples are at the basis
of relative valuation. A multiple is a ratio with in the numerator the amount you pay for an asset and in
the denominator what you get out of the asset in the future. For example, the P/E multiple has the price
of a share in its numerator and the earnings associated with this share in the denominator.

Pearl and Rosenbaum (2013) call multiples the go-to valuation tool for every banker. Multiples provide a
simple way to value companies/assets in Merger & Acquisition (M&A) deals, Initial Public Offerings
(IPO), investment decisions and restructurings. Pearl and Rosenbaum (2013) also highlight the fact that
market multiples reflect current market conditions, making them more relevant than intrinsic valuation
methods. Pandit and Srivastava (2016) claim that relative valuation is getting increasingly important due
to the mounting political and economic uncertainty. They also emphasize the fact that valuation tends
to be as much art as science. Therefore, the “more simple” multiple approach should be preferred over
other techniques. However, Fernandez (2001) finds that multiples have a broad dispersion. Therefore,
he states that multiples only are insufficient to obtain an acceptable value of an asset. However, another
study showed that the dispersion in multiples is highly dependent on company profitability, size and the
extent of its intangibles. (Lie & Lie, 2001)

The introduction of this section and the section on the practical use of valuation techniques clearly
highlights the importance of relative valuation (Cf. supra). Therefore, an extensive breakdown of this

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approach is necessary. In section 2.4.2.1 the dis- and advantages of multiples are explained. In section
2.4.2.2 an overview is given of the most used multiples. After this, price multiples are explained in
section 2.4.2.3. Enterprise Value multiples are discussed in section 2.4.2.4. Finally, in section 2.4.2.5 the
process of selecting comparable companies is described.

 2.4.2. Multiples
 2.4.2.1. Disadvantages and advantages
There are several points of criticism on multiples (Suozzo, Cooper, Sutherland, &Deng, 2001). These
points can be categorized into three main disadvantages. First of all, it’s hard to draw conclusions when
comparing multiples. There are a huge amount of reasons why multiples can differ. However, not all of
these reasons imply true value differences. For example, similar assets are valued differently if different
accounting principles are used to value them. Secondly, in contrary to popular belief, multiples are
based on the same value drivers as DCF methods. A combination of all these drivers into a point
estimate can lead to erroneous value interpretations. Finally, multiples represent the status of a
company at a certain point in time. Its static nature fails to capture the time-effects of a company.

Nevertheless, some clear advantages validate the extensive use of multiples (Suozzo et al., 2001). The
statistics used in the numerator and denominator of multiples are the ones most used by investors.
Investors influence markets and, as a result, so do the multiples they use. Secondly, as highlighted
previously, valuation is as much art as a science. Therefore, multiples provide solid guidance if based on
viable assumptions. Finally, its ease of calculation makes it very attractive for users.

Interpretation of the dis- and advantages leads to the conclusion that multiples should be present in
every valuation process. The model accompanying this dissertation incorporates multiples, however,
more as a cross-check for DCF methods.

 2.4.2.2. Different multiples used in practice
Pinto et al. (2015) provided further analysis into the use of market multiples. Their findings are
summarized in the table below.

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Multiples used (N = 1,765) Percentage of respondents Conditional use
 P/E (price-to-earnings) 88.10% 67.20%
 PBV (price-to-book value) 59.00% 54.60%
 P/CF (price-to-some measure of CF) 57.20% 44.80%
 P/S (price-to-sales) 40.30% 45.70%
 P/D (price-to-dividend) 35.50% 44.30%
 Enterprise value (EV) multiples 76.70% 61.10%
 Other multiples 11.60% 58.50%

 Table 3: Most used multiples

Both price multiples and enterprise multiples are commonly used. The P/E multiple is used by 88,1% of
the respondents. EV multiples have the second highest usage rate (76,7%). Bancel and Mittoo (2014)
obtain slightly different results. According to their study the EV/EBITDA multiple is the most frequently
used (83%). The P/E multiple follows in second with place with a usage rate of 68%. O'Shaughnessy
(2011) states that the use of enterprise multiples has grown more extensively in previous years than the
P/E multiple. As stated earlier in section 2.2. (Cf. supra), Brown et al. (2015) report that 61% of the
interviewed sell-side analysts uses a P/E multiple very frequently. Liu, Nissim & Thomas (2007) find that
the P/E multiple is more popular than other multiples and DCF methods. Yee (2004) states that the DCF
method is extremely noisy and ,therefore, the P/E multiple should be used instead.

 2.4.2.3. Price multiples
Price multiples have a firm’s share price in its numerator. The share price is presented relative to a
statistic (e.g., earnings per share (EPS)) that relates only to the shareholders of a firm. The most popular
price multiple is the P/E multiple, it was the first method used for stock valuation (Graham & Dodd,
1940). The price earnings multiple represents how much investors are willing to pay for 1 EUR (or
another currency) earnings. The fundamentals underlying the PE ratio can be derived from a simple
equity discount model, such as the dividend discount model (DDM). This model is explained in section
2.5.3 (Cf. infra). A clear distinction has to be made between the historical and estimated P/E ratio. The
historical P/E ratio is defined as a company’s current stock price over its earnings in the previous year.
Whereas, the estimated P/E is a company’s current stock price over its forecasted earnings for the
following year(s). Lie & Lie (2001) proved that using forecasted earnings give more precise value
estimates than historical earnings. However, forecasted earnings are not always available.

 2.4.2.4. Enterprise multiples
Enterprise multiples take all claimholders of the firm into account, not just the shareholders. The capital
invested by these claimholders is represented relative to a statistic (e.g., sales) that relates to the entire
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enterprise. (Suozzo et al., 2001). The most important advantage of enterprise value (EV) multiples is that
companies with different capital structures can be compared. As a result, the amount of debt doesn’t
influence the valuation process. Companies active in similar industries and of similar maturity tend to
have the same capital structures. However, this is most certainly not always the case.

 2.4.2.5. Comparable companies
The importance of choosing an appropriate set of comparable companies was stressed by De Franco,
Hope and Larocque (2015). They also state that there is little theory on how to appropriately select
peers. However, Pearl and Rosenbaum (2013) provide a solid framework for doing this. Therefore, this
section is mainly based on their work. Where necessary, additional insights by others are added.

First and foremost, it is important to study the company whose value you wish to determine. A
valuation practitioner has multiple sources for finding a complete overview of a company. The main
sources of information are quarterly reports, investor presentations, press releases, expert opinions,
etc.

 Business profile Financial profile
 Industry Company size
 Products (services) Profitability
 Customer base Growth pattern
 Distribution means ROI
 Geographic activity Credit risk

 Table 4: Comparable characteristics

The table above lists the characteristics that form the basis for finding comparable companies. It is
important to realize as a practitioner that it is impossible for a peers to be conform on every aspect.

Business Profile

Industry

Industry refers to the markets a company operates in. Industries or sectors can be further divided into
sub-sectors. Sub-sectors can be further decomposed into segments. Determining the industry and
further sub-divisions of a company is essential, due to the fact that companies in similar industries share
common risk patterns and growth opportunities. For example, highly fragmented sectors provide large
growth opportunities compared to mature markets.

Products (services)

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Companies providing similar products (services) are often good peers. This is of course due to the fact
that products (services) are at the basis of a company’s business model. For example, Ontex and Essity
AB both sell healthcare products. The dominant product for both is baby diapers. Their resemblance in
product portfolio makes them comparable.

Customer base

Companies sharing a similar customer base are usually subject to the same risks and opportunities. For
example, Ferrari and Lamborghini each serve customers who like fast cars and take pride in the vehicle
they drive.

Distribution means

The distribution channel is a key determinant of a company’s operating strategy, its performance and as
a result its value. For example, companies selling to wholesalers are characterized by entirely different
cost structures than companies directly selling to customers or retailers.

Geographic activity

Differences in business drivers can be caused by different operational bases. For example, risk-free rates
in the Eurozone are different than in Asia. Therefore, region similarity is important when choosing
appropriate peers.

Financial profile

Company size

Size is based on a company’s market capitalization. Companies active in the same sector who are similar
in size are frequently subject to the same factors (e.g., purchasing power, potential growth, liquidity of
the shares and customers, etc.). As a result, peers are frequently categorized based on size. For
example, companies with a market capitalization lower than €2 billion are one group and with a market
capitalization higher than €2 bn another one.

Profitability

Shortly stated, profitability is the ability to generate revenues. Generally, higher profit margins lead to
higher valuations, all else being equal. Therefore, benchmarking a company’s profitability to its peers is
essential.

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Growth pattern

A firm’s growth pattern is derived from its historical and estimated future financial performance. All else
equal, investors are willing to pay more for shares of companies who are expected to grow a lot.
Consequently, the share price of these companies is higher. For more mature companies, growth in
earnings per share (EPS) is the most important growth measure. However, younger companies often
have no earnings. In those cases, the growth pattern of sales or EBITDA is more meaningful. A more
detailed explanation of growth patterns is given later on (Cf. infra).

Return on investment

The return on investment (ROI) is a ratio measuring the ability of a company to provide earnings to its
financers. The ROI consists of a profitability measure in its numerator (e.g., EBIT, Net Operational Profit
Less Adjusted Taxes (NOPLAT) or net income) and a measure of capital invested in its denominator (e.g.,
total assets, shareholder’s equity or invested capital). Return on investment measures are discussed
more extensively later on (Cf. infra).

Credit risk

Credit risk measures a company’s ability to meet its payment obligations. Credit rating agencies such as
Moody’s Investors Service (Moody’s), Standard & Poor’s (S&P) and Fitch Ratings (Fitch) assess a (public)
company’s credit profile. Ratings given by these agencies serve as good indicators of credit risk.
Nevertheless, these agencies have been frequently accused of being biased (Mathis, McAndrews,
&Rochet, 2009). For non-rated companies the interest coverage ratio is an example of a credit risk
measure. The interest coverage ratio compares a firm’s operating earnings to its interest expenses.

 2.5. Intrinsic valuation
 2.5.1. Introduction
Intrinsic valuation focusses on a firm’s assets and the cash flows these assets generate in the future. The
model created in association with this thesis mainly focuses on intrinsic valuation. Therefore, an
extensive elaboration of this approach is necessary.

 10

 
 
 = ∑ + (1)
 (1 + ) (1 + ) 
 =1

All intrinsic methods value are based on formula (1). However, the underlying building blocks differ per
method, depending on what is valued. The model created in association with this dissertation
incorporates three intrinsic value methods, namely the DDM, the equity DCF model and the entity DCF
model. In Section 2.5.2 the differences in building blocks among these 3 methods is explained. After, in
section 2.5.3 the different variants of the DDM are outlined. In section 2.5.4, the alternatives of the
equity DCF method are presented. Next, in section 2.5.5 the different entity DCF approaches are
explained. Additionally, some extra concerns regarding the entity DCF are discussed. Finally, the
practical applicability of each method is discussed in section 2.5.6.

 2.5.2. Building blocks of intrinsic valuation
Three building blocks can be identified from formula (1). First of all, an asset generates cash flows. The
three methods use different cash flows measures, because they value different outcomes. The DDM and
equity DCF directly value the share price of a firm. The entity DCF, on the other hand, values the
operating assets of a firm. A ‘bridge’ has to be created to go from the value of these operating assets to
the share price of a firm. The different types of cash flows and how they are computed are explained in
section 2.5.2.1. The second building block is risk and more specifically the influence of risk on cost. The
way risk and cost differ among the methods is described in section 2.5.2.2. The final building block is the
growth pattern of an asset, more on this in section 2.5.2.3.

 2.5.2.1. Cashflows
The DDM assumes that dividends are the only cashflows that equity investors get. However, this view is
quite conservative. Investors also have a residual claim on the cash balances that are not paid out in
dividends. The equity DCF, on the other hand, uses the FCFE as a cashflow measure. The FCFE is the
remaining cash in a firm after fulfilling reinvestment needs and obligatory debt payments. To draw the
link with dividends, the FCFE can be interpreted as the amount of potential dividends. Finally, the
cashflow measure used in the entity DCF method is the FCFF. The FCFF is the cash that is left over after
fulfilling reinvestment needs but before making obligatory debt payments. It is the amount of cash left
over for a firm to distribute among its investors. Note the difference between the first two models
(DDM and equity DCF), which use a measure of cash that is at the disposal of shareholders. Whereas,
the entity DCF uses a measure of cash before any debt commitments are honoured. The following
formulas present the relation between the different cashflow measures.
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 = ℎ − (2)

 ℎ = × (1 − ) + ℎ noncash (3)

 = − & (4)

 ℎ = − (5)

 = + − + ℎ (6)

 = − (7)

 = × (8)

 = (9)
 
The FCFF is obtained by subtracting the net capital expenditure from the cashflow from operations. The
cashflow from operations is equal to the sum of the firm’s after-tax operating income and the change in
non-cash working capital (WC). The firm’s net capital expenditure is the difference between its capital
expenditures and its depreciation & amortization costs. All tangible assets depreciate or amortize over
time. Therefore, the firm has to make investments to sustain the quality of its assets or to replace its
assets. The non-cash WC is the difference between a firm’s non-cash current assets and non-debt
current liabilities . Current assets are assets that are short-term of nature (e.g., inventory).
Consequently, current liabilities are liabilities that are short-term of nature (e.g., accounts payable).
Cash is not incorporated into the current assets. This is because cash is invested in risk-free assets (e.g.,
commercial paper). As a result, the firm earns returns on cash, whereas, on other current assets no
returns are earned. Short-term debt is not included in the current liabilities. The FCFE is obtained by
subtracting net debt issued and interest expenses from the FCFF. The net debt issued is the difference
between the debt a firm issued and the debt it repaid during a year. Interest expenses are the costs
associated with debt. Interest payments are taxed, resulting tax benefits are, therefore, added back to
the FCFE. Dividends are the amount of FCFE that is paid out by the firm. The rest of the FCFE is held
back. (Damodaran, 2007)

 2.5.2.2. Risk and cost
A company’s risk can be split into market risk and idiosyncratic risk. Market risk relates to the risk
associated with overall market movements. These movements influence all firms in a market. For
example, the quantitative easing project by the European Central Bank influences all firms active in the
European market. Idiosyncratic risk is risk specific to a company. For example, a certain firm might be
 12

sued for environmental malpractices. This only influences the company in question and not the market
as a whole. (Damodaran, 1999). Risk influences the cost of a firm. The riskier a firm, the higher the
compensation asked by both equity and debt investors. Formula (1) shows that the cashflows have to be
discounted using an appropriate rate. This discount rate is the cost of attracting a certain type of
investors. The discount rate per method has to be conform with the nature of the cash flows. The DDM
and equity DCF both use cashflows measures at the disposal of shareholders. Therefore, the appropriate
cost factor associated with these methods is the cost of equity (COE). On the other hand, the entity DCF
uses a cashflow measure before financial expenses. Therefore, the appropriate cost factor associated
with the entity DCF takes both the COE and cost of debt (COD) into account. This cost factor is called the
weighted average cost of capital (WACC).

In section 2.5.2.2.1 the cost of equity (COE) is explained. After, the cost of debt (COD) is dissected in
section 2.5.2.2.2. The COD is lower than the COE because debtholders have limited liability. This means
that they are repaid before shareholders and are protected by a collateral. Finally, the weighted average
cost of capital (WACC) is explained in section 2.5.2.2.3.

 2.5.2.2.1. Cost of equity
The COE can be determined by the following formula.

 = + × ( − ) (10)

Formula (6) is derived from the Capital Asset Pricing Model (CAPM). Rf is the risk-free rate, β is the beta
of the stock and Rm is the return on the market portfolio. The CAPM of William Sharpe (1964) and
Lintner (1965) was one of the first methods within the asset pricing theory framework. It stems from the
model on portfolio choice by Henry Markowitz (1959). At time t – 1, an investor selects a certain
portfolio which produces a stochastic return at time t. Markowitz’ theory assumes that investors are risk
averse. This means that when investors choose a portfolio they only care about the mean and variance
of their investment’s return. As a result, Markowitz’ model is called a ‘mean-variance model’. In the
following subsections the parameters of formula (6) are explained separately, because of their
importance in valuation.

Risk-free rate

This part is based on Damodaran’s extensive research on the use of risk-free rates in valuation practices.
(Damodaran, 1999)

 13

The risk-free rate is the return on a risk-free asset. For an asset to be risk free, the actual return on the
asset must equal the expected return. The risk-free rate is mostly derived from zero-coupon
government securities. The risk-free rate is then a combination a country’s real interest rate and the
country’s expected inflation. However, not all governments are risk-free. Solutions for this problem are
described at the end of this subsection (Cf. infra). In practice, it is common to use one, long-term risk-
free rate for all cashflows, regardless of their maturity. It is a time waste to compute a risk-free rate for
every cashflow duration. The risk-free rate has to be denominated in the same currency as the
cashflows. For example, if the cashflows are in Euro, then the risk-free rate within the Eurozone is used.
The rate on the 10 year German government bond is mostly used as a risk-free rate for the Eurozone.
This is due to the fact that the German government has the lowest default risk in the Eurozone.

Risk-free rates vary across regions and currencies. However, not all countries have long-term
government bonds denominated in their local currency. As a result, it is not possible to directly derive a
risk-free rate for these countries. There are two ways to deal with this problem. Firstly, the financials of
companies located in these countries can be denominated in a mature market currency instead of in the
less mature currency. As a result, the mature market’s risk-free rate and other parameters can be used
for valuation. For example, if the Indian government does not have a government bond denominated in
Indian Rupee valuation can be done in US dollars. The second solution keeps the financials in the local,
less mature currency. However, the roadblock of not having a risk-free in these currencies still has to be
overcome. Damodaran (1999) proposes three solutions. The first option assumes that real rates are the
same in every country. The US government offers Treasury Inflation-Protected Securities. The rate on
these securities can be used as a proxy for the real rate. Adding the (expected) inflation numbers of a
country to that real rate leads to the nominal risk-free rate for that country. Expected inflation can be
determined by extrapolating inflation from the previous years. The second solution uses interest rate
parity between the forward and the spot exchange rate. A respective risk-free rate can be derived if all
other input factors are known. Thirdly, the discount rate of a mature currency can be computed and
adjusted for inflation, to obtain an estimation of the discount rate in the local currency.

Another problem is that not all governments are default free, as mentioned above (Cf. supra). History
has proven that especially emerging markets are not default free (Cruces, Buscaglia, &Alonso, 2002).
Therefore, using the interest rate on long-term bonds isn’t a good proxy for the risk-free rate, since it
includes a default spread. The solution is to compute the sovereign default spread and subtract it from
the interest rate on the long-term bond. Several studies discuss how sovereign default spreads can be

 14

computed. (Du, &Schreger, 2016; Annaert, De Ceuster, Van Roy, &Vespro, 2013). Three ways reoccur in
most studies. Firstly, it is possible for emerging governments to have a bond denominated in a mature
currency (e.g., Euro, US dollar). In this case, the sovereign default spread is obtained by taking the
difference in interest rate on the emerging and mature government bond. For example, assume there is
a 10 year Indian government bond denominated in US dollars. The sovereign default spread of the
Indian government results from the difference in interest rate on that bond and the interest rate on the
10 year US treasury bond. Secondly, the sovereign default spread can be approximated by sovereign
credit default swaps (CDS). However, there is not a CDS for every emerging government. Finally, if there
are no bonds denominated in a mature currency, nor credit default swaps. Then the average of
sovereign default spreads for countries with the same sovereign rating is used. Rating agencies provide
ratings per country.

The risk-free rate also changes over time (DeJong, &Collins, 1985). Especially emerging markets have
been characterized by volatile risk-free rates. Analysts tend to use a normalized risk-free rate, if they
expect the risk-free rate to be volatile. However, idiosyncratic views on risk-free rates tend to lead to
over- or undervaluation of companies. The appropriate solution is to look at the forward or futures
market for treasury bonds. This provides us with what the market expects interest rates to be in the
future and are ,therefore, the best approximations of risk-free rates further down the line.

Beta

The underlying structure for this part is again based on Damodaran’s work. Additions are made where
necessary. (Damodaran, 1999)

The beta coefficient is a measure of a company’s systematic risk, it measures how strongly a firm reacts
to overall market movements. The following formula determines the beta (Black, 1992).

 ( , )
 = (11)
 ( )

With Re being the return on an individual stock, Rm the return on the market portfolio. The covariance
entails the effect of market movements on a stock’s return. The variance is the dispersion of market
returns from their average.

There is a difference between a levered and an unlevered beta (Fernandez, 2006). The unlevered beta,
also called the firm beta, doesn’t take the firm’s capital structure into account. Whereas, the levered
beta, also called the equity beta, is obtained by levering the firm beta. Levering means taking debt into
 15

account. A more leveraged capital structure leads to a higher equity beta, all other things equal. The
overall market beta is equal to one, which makes sense based on formula (11). Therefore, a beta higher
than one means that a firm is more risky than the overall market. The opposite is true for firms with a
beta lower than one.

The unlevered beta is mainly determined by the nature of a firm’s products or services and by its
operating leverage. Some general principles on the influence of a firm’s product portfolio can be stated.
First of all, firms that produce luxury goods are characterized by higher betas. This is due to the fact that
these products are the first to be dropped out of a consumer’s product portfolio during hard economic
times. Maslow (1970) was one of the first to observe this. Secondly, growth firms have higher betas than
mature firms. This is logically considering that growth firms have less stable cashflows. Finally, cyclical
companies have higher betas than non-cyclical ones. This results from the fact that sales of these firms
depend largely on specific conditions. For example, an umbrella company sells more if weather
conditions are bad. A company with a higher operating leverage uses a lot of fixed costs compared to
variable costs. All other things equal, a higher operating leverage leads to a higher beta (Mandelker,
&Rhee, 1984).

There are two ways to lever up the firm beta. Firstly, it is possible to assume that debt doesn’t carry any
market risk. This approach is mostly chosen in practice. In this case, the equity beta is derived using the
following formula.

 = × {1 + (1 − ) × } (12)
 
βL is the levered beta. βU is the unlevered beta or the asset beta, tr is the marginal tax rate, D the level of
debt and E the level of equity. Secondly, it is sometimes possible to compute the market risk associated
with debt. In this case the levered beta is determined as follows.

 = × {1 + (1 − ) × } − × (1 − ) × (13)
 
In valuation practices, the beta of a certain stock is determined using either a bottom-up or top-down
approach. The bottom-up approach requires taking several steps. First of all, the businesses in which a
company operates have to be determined. Secondly, regression (top-down) betas for firms present in
these businesses have to be found. From all these individual regression betas a simple average per

 16

industry has to be computed. This average beta is then unlevered using the industries’ average debt-to-
equity ratio. Thirdly, the value the firm creates in each industry has to be determined. In practice a
statistic such as sales or operating income is mostly used to define the relative weight of an industry.
Next, a weighted unlevered beta for the firm is computed using the weights and unlevered betas of each
business. If you expect the firm to change its business mix than the weights should be adjusted on a
yearly basis. Finally, you lever up the firm beta using the capital structure of your firm. This levering
process has to be done every time you expect the firm’s capital structure to change.

The top-down approach is done by regressing company returns against market returns. The slope of the
regression is the beta. The r-squared (R2 ) of the regression tells how much of the firm’s risk can be
attributed to market risk. Consequently, (1 – R2) is the portion of idiosyncratic risk. The top-down
approach rests on several assumptions. First of all, the estimation period has to be decided, most of the
time a period from 2 to have 5 years is used. Secondly, a return interval has to be chosen, for example
intraday returns. Thirdly, a market index has to be determined to regress the stock returns against, for
example the S&P 500 Index.

Equity risk premium

In accordance with the previous parts the outlined framework is based on a paper from Damodaran.
(Damodaran, 2013).

The equity risk premium (ERP) is the premium investors require for investing in an average risk
investment compared to a risk-free investment. The premium should fulfil certain conditions. First of all,
the premium has to be greater than zero. Secondly, it has to increase if the average risk aversion of
investors increases. Finally, the premium has to increase with the riskiness of the average risk
investment. Several studies have claimed that the ERP is currently too high. These studies highlight that
the ERP is more than just a premium for investing in a risky instead of risk-free investment (Mehra,
&Prescott, 1985; Siegel, &Thaler, 1997). However, further elaboration on this matter surpasses this
study’s scope. The ERP horizon should match with the horizon of the risk-free rate. Therefore, in
practice the 10 year ERP is used. Graham and Harvey (2001) find that the 1 year ERP tends to be highly
volatile, whereas, the 10 year expected ERP is way more stable.

The three most popular ways to determine the ERP are the survey approach, the historical data
approach and the implied approach. Firstly, the survey approach is based on analyst consensus.
Interviewing several professionals gives an estimation of the ERP they use. Secondly, the ERP can be
 17

based on historical data. However, this approach poses two main problems. Firstly, expectations of
future ERPs based on historical data are mostly too high (Dimson, Marsh, &Staunton, 2003). Secondly,
there is insufficient data on historical premia, especially for non-prominent markets. To obtain an ERP
based on historical data for these non-prominent markets a country risk premium (CRP) has to be added
to the ERP of a mature market. This additional premium can be incorporated in three ways. Firstly, the
sovereign default spread can be used as a proxy for the CRP. The ways this default spread can be
computed was previously discussed in the subsection on risk-free rates (Cf. supra). Secondly, the
standard deviation on the equity market of the emerging and prominent country can be compared. The
higher the difference in standard deviation between the two markets, the higher the ERP for the
emerging country is. Finally, the default spread on a bond of the emerging country can be multiplied
with the relative volatility of stocks and bond prices. For firms operating in these non-prominent
markets there are three ways to incorporate the CRP in their risk number. Firstly, it can be assumed that
every company in a country is equally exposed to country risk. In this case, the following formula
determines the company’s overall risk.

 = + × ( ) (14)

Secondly, the CRP can be treated the same as other market risk. The overall risk is then determined in
the following way.

 = × ( + ) (15)

Finally, the CRP can be treated as firm-specific risk. This is done by weighing how much percent of
business is located in the country in question. The company’s risk is then equal to the following.

 = × + × ( ) (16)

Finally, the ERP can be based on the current value of a stock. Under the assumption that shares are
correctly priced, the ERP can be derived by finding the discount rate that makes the present value of the
stock equal to zero. Subtracting the risk-free rate from this discount rate results in the implied ERP. This
method is the most accurate one, considering it is forward looking.

The ERP for a certain company as a whole should be based on its operations. A statistic, such as sales,
should be used to determine the countries where a firm is active and its respective presence in each
country. The ERP for a firm is then most precisely obtained by multiplying the implied ERP for each
country with the respective country weights.

 18

2.5.2.2.2. Cost of debt
Debt has several specific characteristics. First of all, debt entails a commitment to make fixed payments
in the future. Failure to honour these commitments leads to default or loss of control. Hence, debt
includes all interest-bearing liabilities and leases, both operating and capital.

The process of estimating the COD depends on whether a firm is rated or not. Rating agencies give
ratings to companies based on their default risk. The three most famous rating agencies are Standard &
Poor’s, Moody’s and Fitch. In this dissertation the process of how ratings are determined is not
discussed. When the firm is rated, the pre-tax COD is obtained by combining the risk-free rate with a
default spread based on a firm’s rating, as the following formula shows.

 − = + (17)

If the firm is not rated there are two possibilities. Either the interest rate on the most recent, long-term
loan is used as a proxy for the COD or a synthetic rating can be created to determine the firm’s default
spread. A synthetic rating is created using the interest coverage ratio and size of a firm. Based on these
two characteristics a default spread is obtained.

 2.5.2.2.3. The weighted average cost of capital
The weighted average cost of capital (WACC) is the weighted sum of a firm’s COD and COE. The WACC
can be computed using the following formula:

 = × + × × (1 − ) (18)
 + + 

E is the level of equity and D consequently the level of debt, tr is the marginal tax rate. It is common
practice to use the market value of equity but the book value of debt as a proxy. However, using the
following formula, the market value of debt can be computed which leads to more precise results.

 1
 1− ( )
 (1 + ) 
 ( ) = × + (19)
 (1 + ) 

I is the interest expense for the current year, BV (D) is the book value of debt, r the pre-tax COD and Tw
is the average maturity of the outstanding debt.

 2.5.2.3. Growth pattern
The measure of growth differs per method used, because it is based on different fundamentals. How the
growth rate is computed per method is outlined in section 2.5.2.3.1. The growth pattern of a firm
 19