Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
The use of company valuations in corporate finance, focusing on the importance of recognizing value drivers and selecting appropriate peer groups. the process of deriving multiples and value drivers, as well as the significance of historical and futuristic perspectives in valuation. It also discusses the challenges of selecting comparable companies and the role of simple linear regression in establishing value estimations.
Typology: Schemes and Mind Maps
1 / 49
This page cannot be seen from the preview
Don't miss anything!
DEGREE PROJECT IN FINANCE REAL ESTATE AND FINANCE TRACK: FINANCE BACHELOR OF SCIENCE, 15 CREDITS, FIRST LEVEL STOCKHOLM , SWEDEN 2016
KTH ROYAL INSTITUTE OF TECHNOLOGY DEPARTMENT OF REAL ESTATE AND CONSTRUCTION MANAGEMENT
Bachelor of Science Thesis
Title Evaluating comparable company valuation
Company valuation is entering a new era; with increasing demands, more awareness and internal resistance. As the companies who request the valuation, together with third parties, begin to show more interest in the value statements - the analyst must be able to validate his course of action with reliable reasoning based on substantiated data.
In this thesis, two approaches to the Comparable Company Valuation method will be evaluated and analyzed with the use of a Case Study. Initially, the two approaches will be applied on a Target Company, Company X, which will result in two value estimations. In order to draw conclusions of how to derive a correct valuation and what approach that is to be preferred in the given scenario, similar valuations were performed on six additional companies, in the same manner as the Case Study, and compared with their respective real market value. The valuation is based on financial data and all companies used in the study are listed on Nasdaq Stockholm Stock Exchange.
Findings – First and foremost, results showed that a Comparable Company Valuation is very dependent on its composed peer group. Results from the study indicated increasingly favorable outcomes, when the peer group was similar to the Target Company. The prime conclusions are that, with a perfectly composed peer group, in a mature industry, one of the approaches was to be preferred. However, in an immature industry, where the requirements of the companies used in the composed peer group have to be broadened, the latter approach indicated favorable outcome.
Originality - This study is one of the first to compare two different approaches to the Comparable Company Valuation method and analyze in what scenarios one approach is to be preferred to the other.
Examensarbete
Titel
Författare
Institution
En analys av jämförande företagsvärdering
Institutionen för Fastigheter och Byggande Examensarbete Kandidat nummer TRITA-FOB-BoF-KANDIDAT-2016: Arkivnummer 383 Handledare Björn Berggren Nicolaus Lundahl Nyckelord Företagsvärdering, multipelvärdering, värdedrivare
Företagsvärdering går mot en ny era; med ökade krav, högre medvetenhet och internt motstånd hos värderingsfirmorna. Företag som begär en värdering samt tredjeparter visar allt mer intresse och förståelse för hur värderingen har gått till - vilket leder till att analytikern måste redogöra för sitt tillvägagångssätt med korrekta resonemang baserade på pålitlig data.
I denna uppsats analyserar och utvärderar vi två olika approacher till Comparable Company Valuation med hjälp av en fallstudie. Inledningsvis kommer de två approacherna utföras på Målföretaget, Företag X , vilket leder till två olika värderingar. Vidare, för att kunna dra slutsatser kring vilken approach som bör användas vid vilket tillfälle, gjordes liknande värderingar på ytterligare sex företag, på samma sätt som fallstudien, dessa värderingar jämfördes med marknadsvärdet för respektive företag. Samtliga värderingar baseras på finansiell data och alla företag som är med i studien är listade på Nasdaq Stockholm Stock Exchange.
Resultat – Först och främst visade resultaten att Comparable Company Valuation är väldigt beroende av hur sammansättningen av jämförelseföretag har gått till. Resultat indikerade vidare att värderingen gav bättre, det vill säga mer precist, resultat – om jämförelseföretagen var lika Målföretaget. De viktigaste slutsatserna som drogs var att, när en värdering görs med en perfekt grupp jämförelseföretag, i en mogen industri, var den ena approachen att föredra. Vidare, på en nyare marknad, där kraven för jämförelseföretagen måste sänkas – gav den andra approachen en mer precis värdering.
Originalitet – Denna studie är en av de första som jämför två olika approacher till Comparable Company Valuation samt analyserar när vilken av dessa bör användas för att få en så bra värdering som möjligt.
There is much literature concerning the history of valuation and its different methodologies that have been used overtime (Rutterford, 2004). Company valuation was initially a tool used to assess whether it was profitable, or not, to invest in a company. It was later also used to derive a credit rating for a company so that banks could estimate the risk of lending money to a company (Bergling, 2014). Company valuations developed into a significant tool for corporate finance professionals when conducting mergers and acquisitions, management buyouts, leveraged buyouts, initial public offerings, raising capital through bonds and restructuring of businesses (Koller, et al., 2016). It is also highly used within asset management when allocating money for clients (Barker & Richard, 1999). Corporate valuation is therefore frequently used on a day-to-day basis by both professionals and retail investors. There are several methodologies used when estimating the value of a company, which in a broader context consists of intrinsic valuation and comparable company valuation (Barker & Richard, 1999).
Intrinsic valuation consists of the Discounted Cash Flow (DCF) analysis, which dates back to the early works of Miller, Modigliani, Gordon and Shaprio (Capinski & Patena, 2009). The DCF analysis converts future net cash flows to the present-day values where an investor prefers the company that generates the largest net present value (Hussey, 1999).
The comparable company valuation is sometimes referred to as “peer comparison method” or “the multiple approach”, where a Target Company is valued in comparison to other companies of the same type. This approach assumes that the market is efficient which makes it possible to measure a company’s value in reference to another company’s value.
There are several approaches to the comparable company valuation method where the one that is most practiced by professionals is described by Matthias Meitner. The Target Company’s value is measured by deriving multiples from a peer group. The peer group is selected by the analyst and consists of closely comparable companies in relation to The Target Company. The multiple is derived by extracting a mean or median multiple from the peer group, which could later be adjusted by the analysts’ rule of thumb and personal experience (Capinski & Patena, 2009).
There is an alternative approach presented in the book Valuation: the market approach, which is slightly different (Bernstrom, 2014). The selection process of the peer group is made in a similar manner as in the method described by Matthias Meitner. One crucial difference is that the analysts are to consider the multiples value drivers, both historical and forward-looking value drivers. Studies show that valuation accuracy is improved when recognizing the value drivers when selecting a peer group (Liu, et al., 2002). The peer groups multiples are plotted in a scatter plot chart, versus the respective multiples primary value driver, which is derived from the value drivers compounded estimated future growth (Suozzo, et al., 2001). A linear regression line is drawn to capture the relationship between the multiple and its primary value driver. The Target Company’s multiple is then derived by inserting The Target Company’s
value driver, the coefficient, into the equation that the linear regression line provides (Suozzo, et al., 2001).
The comparable company valuation and the intrinsic valuation methods are widely used by both analysts and retail investors (Capinski & Patena, 2009). The intrinsic valuation method has been continually evaluated and developed, over time, by both practitioners and academics whilst the comparable company valuation has been continually neglected and overlooked by academics and academic literature (Bernstrom, 2014). Such a commonly used valuation method deserves to be analyzed and assessed by academics.
1.1 Background Valuating a company by conducting a comparable company valuation is one of the most used valuation methods. Deriving a value using comparable company valuation is often considered unreliable, and therefore often ignored in research, leaving one of the most practiced valuation methods underutilized (Bernstrom, 2014). However, one of the most common valuation methods deserves to be scrutinized and improved, both scientifically and by practitioners.
Standard practice for company valuation is for an analyst to calculate the average or median value multiple from a listed peer group and apply it to the base metric of The Target Company, hence, using the result to derive value estimations for respective multiple, resulting in three different value estimations. Illustrating a general outcome of a traditional valuation:
Figure 1. A fictional example of how a traditional valuation could look
The key question is whether the arithmetic mean represents The Target Company’s value? One of the problems is that the value is not substantiated by any value driver from the multiples used, solely it cannot explain how the conclusion of this value was derived.
This thesis aims to describe, assess and evaluate the comparable company valuation, which is most commonly used, and present an alternative approach on how to derive at the right multiple which can be substantiated by clear explanations and data.
This chapter initially explains the theory, real-life-practice and previous research regarding comparable company valuation, in addition to this, all values, multiples and value drivers used will be derived and explained.
The market approach is used to derive the valuation of a company based on how comparable companies, listed on the stock exchange, are priced. Firstly, one must find comparable companies, preferably within the same industry and with similar operations, capital structure, risk-level and other value drivers. The value is then based on “rule of thumb” multiples based on personal experiences and multiples derived from the comparable companies (Meitner, 2006).
The market approach can also derive the valuation of a company based on multiples derived from company transactions. The process is similar to deriving multiples from listed companies, however, it is more difficult to get access to relevant data, besides, company transactions may include synergies, which are not representable to the company that is being valued (Bernstrom, 2014).
Value is a defining measurement in a market economy. Investors invest in different types of assets with an expectation that the asset will increase a sufficient amount of value to compensate the investor for the risk taken when purchasing the asset. For this reason, knowledge of how companies create value and how to measure value is vital intellectual equipment. Companies can create financial value by investing capital raised from investors in order to generate future cash flows at rates of return that exceeds the rate that investors require to be paid for usage of their capital. A company that can increase revenues and deploy more capital, meeting or exceeding the rates of return, the more value they create. Therefore, a combination of growth and return on invested capital relative to the cost of capital is what drives value. A company with well-defined competitive advantages can sustain significant growth and high returns on invested capital (Koller, et al., 2016).
The enterprise value is often referred to as EV , defined as interest-bearing debt plus the market value of equity minus excess cash (the market value of the operating/invested capital) (Koller, et al., 2016).
The market capitalization or value of equity is often represented by the letter P, and is defined as the market value of all outstanding shares for a company that is listed on the stock exchange (Koller, et al., 2016).
2.3 Multiples This chapter describes the value-multiples that have been used in the study. The three multiples chosen are the most commonly used multiples by analysts in real life practice (Fernandez, 2001). We define a multiple as a ratio of a market price variable, such as a stock price, the whole enterprise value or the market capitalization to a specific value drive such as earnings or revenues of a firm (Schreiner & Spremann, 2007).
A proper analysis requires that one finds valid multiples for the specific industry. When selecting peers one should consider both Equity and Entity multiples, since they descend from different capital structure aspects.
The share price of a company, by itself, is an absolute value; hence, it is not of interest for the valuation, instead, looking at multiples, in other words, ratios, one can compare a company with another and further use this multiple to perform a valuation (Schmidlin, 2014).
According to Péter Harbula, below, are the most relevant valuation multiples, depending on the industry of which the company being valued is operating in (Harbula, 2009).
Real estate: Price-to-book, Price-to-earnings Building materials: Enterprise-to-EBITDA Banking and insurance : Price-to-book, Price-to-earnings Food and beverages : Enterprise-to-EBITDA, Price-to-earnings Services : Enterprise-to-EBIT, Price-to-earnings Energy : Enterprise-to-EBITDA, Enterprise-to-IC^1 Technology: Enterprise-to-EBITDA, Enterprise-to-EBIT Telecommunications : Enterprise-to-EBITDA, Price-to-earnings Distribution : Enterprise-to-EBITDA, Enterprise-to-EBIT Manufacturing : Enterprise-to-EBITDA, Price-to-FCF^2 Construction : Enterprise-to-EBITDA, Price-to-earnings Life sciences / healthcare : Enterprise-to-sales, Enterprise-to-EBITDA Capital goods: Enterprise-to-EBITDA, Enterprise-to-EBIT Media : Enterprise-to-EBITDA, Enterprise-to-EBIT (Harbula, 2009)
(^1) IC, short for Invested Capital, the total amount of that was put into the company shareholders and other parties. (^2) FCF, short for Free Cash Flow, operating cash flow subtracted capital expenses
To compare performance indicators investors can use entity multiples that represent all the capital providers that are entitled to the enterprise value. The enterprise value is defined as the market value of equity plus financial debt less cash (Koller, et al., 2016). The general question of the entity method is: ‘How much does it cost to purchase the entire business?’ However, any cash belonging to the company purchased belongs to the buyer, hence, reducing the purchase price significantly (Schmidlin, 2014).
Entity multiples usually have the following structure:
𝐸𝑛𝑡𝑒𝑟𝑝𝑟𝑖𝑠𝑒 𝑣𝑎𝑙𝑢𝑒 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 𝑖𝑛𝑑𝑖𝑐𝑎𝑡𝑜𝑟 (𝑏𝑒𝑓𝑜𝑟𝑒 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡)
Formula 1-3. A general structure of entity multiples
Earnings before interest, taxes, depreciation and amortization, EBITDA , express the operational income adjusted for depreciation and amortization, which are non-cash expenses.
As Schmidlin explains, “The EBITDA corresponds roughly to the gross cash flow, therefore, EV/EBITDA shows an approximation of the proportion of the total value of the enterprise in relation to the means that capital providers received” (Schmidlin, 2014).
When looking at businesses within an industry this ratio is sufficient, however, if the companies are operating in different industries then differences can arise, since different companies have different capital expenditures, which directly affect depreciation and amortization expenses (Schmidlin, 2014). As Schmidlin explains further, “Companies with high growth rates or high capital intensity display relatively high levels of depreciation, whereas businesses in asset-light industries, for example wholesalers or internet companies, usually report lower levels of depreciation”. These have an impact on EBITDA and therefore on the resulting valuation…) (Schmidlin, 2014). Furthermore, the EV/EBITDA multiple gives the investor a good insight on the businesses operative performance (Koller, et al., 2016).
EBITDA is defined as follows:
𝐸𝐵𝐼𝑇𝐷𝐴 = 𝐸𝐵𝐼𝑇 + 𝐷𝑒𝑝𝑟𝑒𝑐𝑖𝑎𝑡𝑖𝑜𝑛 𝑎𝑛𝑑 𝑎𝑚𝑜𝑟𝑡𝑖𝑧𝑎𝑡𝑖𝑜𝑛
Formula 1-4. EBITDA defined
𝐸𝑉/𝐸𝐵𝐼𝑇𝐷𝐴 = (𝐸𝑛𝑡𝑒𝑟𝑝𝑟𝑖𝑠𝑒 𝑣𝑎𝑙𝑢𝑒)/𝐸𝐵𝐼𝑇𝐷𝐴
Formula 1-5. The EV/EBITDA multiple
According to the S&P 500, at the fiscal year, the average EV/EBITDA ratio was about 20 (Bloomberg, 2015). Approximately 65% of the companies had an EV/EBITDA ratio between 8 and 18 (Schmidlin, 2014).
The EV/EBIT multiple describes the enterprise value in relation to the operating earnings of a company.
𝐸𝑉/𝐸𝐵𝐼𝑇 = (𝐸𝑛𝑡𝑒𝑟𝑝𝑟𝑖𝑠𝑒 𝑣𝑎𝑙𝑢𝑒)/𝐸𝐵𝐼𝑇
Formula 1-6. The EV/EBIT multiple
EBIT is defined as the earnings before interest and taxes. Thus, compared to EBITDA, depreciation and amortization is excluded. Schmidlin explains: “…The ratio is particularly suitable for comparisons of businesses across industries and serves here as a central valuation multiple together with the price-to-earnings ratio. The EV/EBIT multiple considers the capital structure and includes the financial stability of the firm directly in the valuation." (Schmidlin, 2014).
According to the S&P 500, at the fiscal year, the average EV/EBIT ratio was about 15 (Bloomberg, 2015), approximately 80% of the companies had an EV/EBIT ratio between 8 and 24 (Schmidlin, 2014).
2.4 Multiple Value Drivers Multiples, as those explained above, are stimulated by their respective primary value driver, affecting their outcome over time, in addition to risk (as will be explained later in the thesis). The value drivers are unique for different multiples. In general, a higher value driver would result in a higher value multiple. Looking at the price-to-earnings multiple, the value driver is the expected percentage growth of the company’s earnings after tax, derived from the expectations of the futuristic 3 years. Similarly, the enterprise-to-EBITDA multiples value driver is the expected percentage growth of the company’s earnings before interest, taxes, depreciation and amortization and the enterprise-to-EBIT multiples value driver is therefore the expected percentage growth of the company’s EBIT (Liu, et al., 2002). Note that all value drivers are expressed in percentage.
Conclusions regarding the value drivers above can be estimated by historical data as well as from forward-looking data provided by analysts following the listed companies (Liu, et al., 2002).
In the process of finding a suitable peer group, it is essential to consider geographic circumstances that may have effect on company growth. It is undisputed that macro-economic trends such as GDP and monetary policy play a crucial part in company growth and therefore also affects the multiples that can be derived from the peer group (Meitner, 2006). To derive value multiples from a peer group one must find suitable peers in the same country, or at least in counties where macro-economic trends are reasonably alike (Bernstrom, 2014). It is also known that different regions tend to have different patterns of evolution, for example, companies operating in Asia tend to have strong projections, not being too affected by slowdowns, whilst Europe has shown modest, but now increasing growth (Martins, 2011).
The selection process also highly depends on the business model, which for the peer group should be as similar as possible to the Target Company. A simple approach to the problem of selecting similar comparable companies is to find companies within the same industry, furthermore compare business models and financial rations between The Target Company and the potential comparable companies to arrive at the adequate peer group (Henschke, et al., 2009).
According to a study, where the authors analyzed companies in the same industry and their historical growth, valuation errors were smaller when comparable companies are matched on historical growth (Sehgal & Pandey, 1981). Another study showed similar results, looking at forecasted growth (Zarowin, 1990). The purpose of analyzing historical financials in combination with the specific company strategy aims to explain historical performance, both operating and financial performance, furthermore helps one identify business risks and key profit drivers. It is then possible to make correct estimations of future performance with relevant historical data as a basis (Healy & Palpu, 2000). The time period of historical data should in general cover a time period about 3-5 years if representative and relevant data is available. The time period can be shortened or increased depending on the information that the historical data provides, however, the time period should represent the company’s or industries future growth and earnings potential (Bernstrom, 2014).
2.6 Risk Financial risk is an important factor when valuing a company. Financial risk can be thought of as the variability in cash flows and market values that are caused by unpredictable events and changes that are both macro-economic or company specific (Holton, 2004).
It has been beneficial to invest in small companies, rather than large, and this has been documented in numerous studies (Bis, 2007). Small Cap companies annual rate of return from 1925 to 1997 was 12,7 % while large cap companies reached an annual return of11 %, according to Ibbotson Associates (Kathman, 1998). In 1981, Rolf Banz was able to show that “the common stock of small firms had, on average, higher risk adjusted returns than the common stock of larger firms”. He concluded that the size was not the likely value driver of the over performance, rather a hidden risk (Banz & W, 1981). However, in 1986 Amihud and Mendelson provided evidence that the illiquidity is a primary driver behind the small stock premium (Amihud & Mendelson, 1986). Investors require higher returns on small stocks since they in general lack liquidity, hence making it difficult to get in and out of positions quickly in the event of a market downturn (Bis, 2007).
A company can be exposed to numerous company specific risks compared to other large traded counterparts (James, et al., 2005). These risks are, in general, priced in to the stock and can be caused by factors such as; inexperienced management, a high dependency on one customer or supplier, key personal or lack of customer loyalty. Companies exposed to such risks must offer a higher rate of return to attract investors (Israel, 2011). However, analysts do not have a general procedure for measuring company-specific risks, which means that analysts interpret these risks differently (Meinhart, 2008).
The alternative comparable multiple-based valuation is conducted by deriving multiples from a peer group which have similar value drivers and operate in the same, or in some cases similar, industries and countries meaning that they are exposed to similar macro-economic conditions. The peer group consists of listed companies (Meitner, 2006). The amount of companies in a peer group varies depending on how many similar listed companies one can find with suitable financial data, however, the amount of companies varies amongst 5 to 10 companies (Cooper & Cordeiro, 2008).
Specific industry multiples, from the peer group, are plotted as Y-variables, in a scatter chart, versus its primary value driver, the X-variable, which is derived from the value drivers compounded estimated future annual growth. A linear regression line is drawn to capture the relationship between the multiple and its primary value driver. The Target Company’s multiple is then derived by drawing a vertical line from its x-axis; from its compounded estimated future annual growth in its primary value driver, until it intersects the peer groups’ linear regression line. An additional line is drawn horizontally towards the y-axis; from the section in where the peer groups’ linear regression line was intersected, to derive the multiple in relation to The Target Company’s compounded estimated future annual growth from its value driver. The multiple can also be derived by inserting the X-variable into the simple linear regression equation.
3.3 Data All historical and forecasted financial data is extracted from Bloomberg Terminal. All data has been entered and processed in Microsoft Excel by the authors themselves. All companies used in the thesis are listed on the Nasdaq Stockholm stock exchange.
3.4 Interviews Two interviews were conducted at an early stage of the project. Both interviews were recorded with an audio recorder and transcribed to its full extent. Both interviews were semi- structured and consisted of several key questions in order to define which areas to be explored. The questions were designed in such a manner that both the respondent and the interviewer could diverge in order to pursue interesting responses or ideas in detail. This method was chosen because it allows one to pursue elaboration of information that is of significance but not previously thought of as pertinent. Both authors in this bachelor thesis were present during both interviews and both of the authors asked questions.
The first interview was conducted 24-04-2016 with an analyst at IK investment Partners named Farhad Tatar with approximately 2 years of experience in the finance industry. Most questions and answers were related to the comparable company valuation method and company valuation in general. This interview lasted approximately one hour.
The second interview was conducted 11-05-2016 and the person interviewed prefers to remain anonymous. This person has extensive experience with company valuation and has worked in the finance industry since 2000. This interview was more focused on how to select a peer group and how to derive at the right multiple, also clear explanations of different approaches to the comparable company valuation method, but also, defining the differences
between the traditional and alternative comparable company valuation methods. This interview lasted two hours.
The semi-structured interviews were favorable since it provided an in debt knowledge of how comparable company valuation is practiced. The key questions and follow-up questions provided sufficient information and many insights which helped to answer the thesis framed question and in addition also provided great insight of how the comparable company valuation is conducted in practice. The answers provided from the professionals also included helpful insights in selecting academic literature, financial data and selecting the companies used in the case study. The interviews also resulted in insights of what missteps most practitioners make.
3.5 Simple linear regression Interpreting the data received from the alternative valuation method is rather straightforward, however, one would like to estimate the precision of the value estimated. The perks of using a simple linear regression are that it can be made with few observations (Simkiss, et al., u.d.).
To arrive at a valuation, using the alternative valuation method, one must derive the multiple from a composed peer group (Bernstrom, 2014). This is possible if x and y show a relationship with each other, one can predict y from x by establishing their relationship. The relationship, in its simplest model, is a straight line called a simple linear regression line where one is regressing y on x. Simple indicates that the regression line is only dependent on one independent variable whilst linear indicates that the model used is a straight line (Dowdy, et al., 2004). The simple linear regression line is established by plotting the pairs, x and y , as points in a graph called scatter plot (Dowdy, et al., 2004). The points in the graph, when using the alternative comparable company valuation method, will in general appear in a linear upward trend since an investor is willing to pay a higher multiple for a higher estimated value driver (Bernstrom, 2014). A simple linear regression line, is used to establish a straight line, to fit such data so that the line can be used to predict the variable y (multiple) given the provided x variable (the value driver, in this case the expected growth in the multiple’s performance indicator) (Dowdy, et al., 2004). Since the slope has a linear upward trend, it measures the change in the value of y corresponding to a unit change in the value of x (Dowdy, et al., 2004).
The linear mean, known as the regression equation, is mathematically represented by the formula:
𝒀 = 𝜶 + 𝜷𝚾
Formula 1-6 , the simple linear regression equation
Where 𝜶 and 𝜷 are regression coefficients. The closer the regression line comes to all the points on the scatter plot, the better it is (Simkiss, et al., u.d.). The regression equation and the linear relationship are either calculated with a graphing calculator or with the excel add-on ‘Data Analysis’
The additional data received is as follows: df, p, s, r, r-square, adjusted r-square, standard error, ss and ms
