MSc. Finance and International Business Master Thesis Authors: Doreen Nassaka and Zarema Rottenburg Advisor: Baran Siyahhan

Analysis of corporate valuation theories and a valuation of ISS A/S

1st August 2011 Aarhus School of Business and Social Sciences Aarhus University

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AcknowledgementsWe would like to thank our advisor, Baran Siyahhan, for his helpful and constructive guidance. We would also like to thank our friends and family for their support and patience.

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Executive summary In this paper various corporate valuation theories are analysed, and selected corporate valuation theories are applied to the case company International Service Systems, ISS A/S (ISS). ISS is a Danish founded multinational, multibusiness company, which operates within the facility services industry. The company was public until 2005 when it was acquired by two equity funds: Swedish EQT Partners and American Goldman Sachs Capital Partners. In the period 2005-2010, ISS has been acquiring many companies in order to expand geographically. In the future ISS expects to focus on organic growth, and limit their growth through acquisitions to emerging markets. ISS has suffered operating losses in the whole period when it was private and has obtained high amounts of debt. This has lead to high financial expenses for the company and an inability to pay off its debt on time. In order to improve its capital structure ISS decided to go public again on the Copenhagen stock exchange. The initial public offering (IPO) was planned in March 2011, but was postponed due to the instability of the financial markets. The corporate valuation theories analysed in this paper are the discounted cash flow (DCF) model, the dividend discount model (DDM), the residual income model (RIM), real options valuation (ROV) and valuation using multiples. Furthermore, two methods for determining the expected rate of return on a companys stock are evaluated, these are: the capital asset pricing model (CAPM) and the Fama and French three factor model. Based on the analysis, the DCF model is selected as the primary corporate valuation model in this thesis, and the capital asset pricing model (CAPM) is chosen to estimate the cost of equity for the company. Additionally, real options analysis is applied as an extension of the DCF model, in order to capture the value of the managers flexibility in relation to ISS expansion in emerging markets. Lastly, the valuation using multiples is conducted in order to evaluate whether the results obtained from the DCF and real options valuation are reasonable. In the valuation process ISS corporate environment is studied by means of a strategic analysis. Additionally, the company value from the DCF model is calculated based on the forecasted free cash flow in the explicit forecasting period and the estimated continuing value after the explicit forecast period.

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In the real options analysis a five year option to expand in South Korea is valued and added to the value obtained from the DCF model. The value of the real option is estimated by using the binomial model. The valuation using multiples is conducted based on ISS identified peer group of seven similar companies, and two multiples EV/EBITDA and EV/S are used in the analysis. The valuation process is finished off with a discussion of the results and a comparison of these results to equity values of ISS published by professional analysts and to the expected IPO share price published by ISS. ISS firm value from the DCF model is DKK 55,173 million, the equity value is DKK 39,049 million and the share price is DKK 167.59. The enterprise value including the real options is DKK 56,279 million, the equity value is DKK 40,154 million and the share price is DKK 172.34. From the multiples analysis, ISS enterprise value, equity value and share price are estimated within the range DKK 40,641 - 48,959 million, DKK 24,516 - 32,834 million and DKK 105 141, respectively. The equity value obtained from the DCF and the real options analysis is compared to the published equity value estimates from professional analysts that are within the range of DKK 39.4-49 billion. The estimated share price of DKK 172.34 is compared to the IPO share price that is within the range of DKK 100 DKK 135. The difference in the share price may be due to the fact that it is a second-time IPO and that the company has high debt levels. It is concluded that the enterprise value for ISS of DKK 56,279 million is reasonable, and that the share price of DKK 172.34 represents the fair market value of the companys shares.

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Table of contentsExecutive summary .............................................................................................................................. 1 1. Introduction ...................................................................................................................................... 8 2. Description of ISS ............................................................................................................................ 9 3. Problem statement .......................................................................................................................... 10 4. Definitions ...................................................................................................................................... 11 5. Delimitations .................................................................................................................................. 11 6. Data collection and validity ........................................................................................................... 12 7. Analysis of the corporate valuation theories .................................................................................. 12 7.1 The discounted cash flow method ................................................................................................ 13 7.1.1 Step 1: The calculation of free cash flow .............................................................................. 13 7.1.2 Step 2: The weighted average cost of capital ........................................................................ 14 7.1.3 Step 3: Identifying the continuing value ............................................................................... 23 7.1.4 Step 4: Calculating the company value ................................................................................. 24 7.1.5 Evaluation of the DCF method ............................................................................................. 25 7.2 Dividend discount model (DDM) ................................................................................................ 25 7.2.1 Advantages and disadvantages of the DDM ......................................................................... 27 7.2.2 Evaluation of the DDM ......................................................................................................... 28 7.3 Residual income model (RIM) ..................................................................................................... 28 7.3.1 Advantages and disadvantages of the RIM ........................................................................... 29 7.3.2 Evaluation of RIM ................................................................................................................ 32 7.4 Real Options Valuation (ROV) .................................................................................................... 32 Page 5 of 112

7.4.1 Advantages and disadvantages of real options ..................................................................... 33 7.4.2 The binomial model .............................................................................................................. 34 7.4.3 The Black and Scholes model ............................................................................................... 36 7.4.4 Evaluation of real options ..................................................................................................... 37 7.5 Valuation using multiples ............................................................................................................ 37 7.5.1 Advantages and disadvantages of multiples ......................................................................... 40 7.5.2 Evaluation of the multiples method ...................................................................................... 41 8. Valuation of multibusiness companies .......................................................................................... 41 8.1 Challenges of valuing multibusiness companies ..................................................................... 42 8.2 Summary .................................................................................................................................. 43 9. The choice of corporate valuation theories .................................................................................... 43 10. Structure of the valuation process ................................................................................................ 44 11. Strategic analysis of ISS .............................................................................................................. 45 11.1 PESTEL analysis........................................................................................................................ 46 11.2 Porters five forces analysis ....................................................................................................... 49 11.3 Core competencies ..................................................................................................................... 52 11.4 SWOT analysis .......................................................................................................................... 53 12. Valuation of ISS using the DCF model ....................................................................................... 56 12.1 Step 1: Choice between using aggregated or disaggregated numbers ................................... 56 12.2 Step 2: Currency choice ......................................................................................................... 57 12.3 Step 3: Calculation of free cash flow ..................................................................................... 57 12.3.1 The reformulated statement of shareholders equity (SE) .................................................. 58 12.3.2 The reformulated balance sheet .......................................................................................... 58 Page 6 of 112

12.3.3 The reformulated income statement .................................................................................... 60 12.3.4 Trend analysis ..................................................................................................................... 60 12.3.5 Profitability analysis ........................................................................................................... 62 12.3.6 Summary of the financial statement analysis ...................................................................... 68 12.3.7 The amount of free cash flow ............................................................................................. 69 12.3.8 Forecasting free cash flow .................................................................................................. 69 12.4 Step 4: Estimating the weighted average cost of capital ........................................................ 77 12.5 Step 5: Calculating the continuing value ............................................................................... 83 12.6 Step 6: Calculating the company value .................................................................................. 83 12.7 Scenario analysis .................................................................................................................... 84 12.8 Sensitivity analysis ................................................................................................................. 86 13. Valuation of ISS using real options ............................................................................................. 87 13.1 Step 1: The value of ISS without flexibility .......................................................................... 90 13.2 Step 2: Event tree for ISS ....................................................................................................... 90 13.3 Step 3: Decision tree for ISS .................................................................................................. 92 13.4 Step 4: The value of ISS with flexibility................................................................................ 93 14. Valuation of ISS using multiples ................................................................................................. 94 15. Discussion of the results .............................................................................................................. 95 16. Conclusion ................................................................................................................................... 99 References ........................................................................................................................................ 102 List of appendices ............................................................................................................................ 111

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1. Introduction The purpose of this master thesis is to analyse and discuss different theories of corporate valuation, and to apply the most appropriate ones to the case company International Service Systems, ISS A/S (ISS). Corporate valuation has been of great interest to the authors throughout the master course; however, this topic has not been covered in details in the corporate finance classes attended by the authors. It was therefore decided to focus on this topic in the final master dissertation. The intention of this assignment is to apply theoretical knowledge about company valuation to a real life case by using external publically available data such as annual reports and published articles. It is preferred to analyse the company from an external point of view because obtaining internal data from the company often makes the analysis process slower because the authors will have to depend on data provided by the companys employees. ISS has been chosen as the case company due to its interesting financial history, the large media coverage at the time the thesis topic was chosen, and the fact that it is a challenge to value this company with the traditional financial valuation tools. The financial history of ISS is considered to be interesting because it started out as a small private company in Copenhagen in 1901, became a public company in 1977 and was acquired through a leveraged buyout by two private equity funds in 2005. Burdened by huge amounts of debt, ISS was considering another private sale or a second IPO in 2010/2011. Valuation of ISS is challenging because ISS is a very large, private, multinational, multibusiness company, which offers different facility services to private and public customers. However, due to the rumours about a sale or an IPO at the end of 2010 and the beginning of 2011 numerous articles about ISS were published stating factors such as the estimated corporate value of the company, its expected growth rate and the expected share price. Furthermore, due to the size of ISS and its past as a public company, all the annual reports for ISS are published for all the years. So even though performing an external valuation of ISS is a challenge, it is not unachievable with the publically available information, and ISS was therefore chosen as the case company.

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2. Description of ISS ISS was founded in 1901 as a Danish security firm by 20 night watchmen in Copenhagen, Denmark and in 1934 the company began offering cleaning services. In 1977, ISS was listed on the Copenhagen Stock Exchange, and in 2005 the company was bought by FS Invest S. R.L, which is located in Luxembourg, and de-listed from the Copenhagen Stock Exchange (issworld.com). Today, ISS is one of the worlds largest private companies owned by FS Invest S. R.L, a company that is owned by two private equity funds: Swedish EQT Partners and American Goldman Sachs Capital Partners, whereby each fund owns 54% and 44% of the share capital, respectively. The remaining 2% of the shares are owned by some employees at the top management level of the company (ISS Annual report, 2010). ISS operates under a decentralized organizational structure. ISS headquarter is currently located in Copenhagen, where they assist their regional and local management in the different countries (ISS Annual report, 2010). By applying decentralized decision making, ISS focuses on strong local leadership and independent decision making, in order to quickly respond to customers demands and needs (issworld.com). In 2010, ISS had revenues of DKK 74 billion and a net loss of DKK 532 million. This loss is an improvement from the net loss of DKK 1,629 million in 2009 (ISS Annual report, 2010). With its 522,700 employees, ISS provides facility services to over 200,000 public- and privatesector customers in the business to business (B2B) market, that are located in 53 countries in Europe, Asia, North America, South America and Pacific. Facility services includes the following six services (the numbers in the parenthesis represent the percentage of the total revenue in 2010 for the ISS group): cleaning services (52%), property services (20%), catering services (9%), support services (8%), security services (7%) and facility management services (4%) (ISS Annual report 2010). The abovementioned services can be delivered separately or as integrated solutions (issworld.com). The cleaning services include daily cleaning (e.g. dust control and wash room services), periodical cleaning (e.g. carpet and window cleaning), special cleaning (e.g. telephone and computer cleaning, laundry services) and segment cleaning (e.g. office, health care and retail cleaning). To maintain the value of the companys customers buildings and surroundings, ISS offers property services that include building maintenance (e.g. painting services, repairs and replacements), ground maintenance (e.g. road services and landscaping), environment maintenance (e.g. pest control and waste management), energy (e.g. water supply, lighting and power) and damage control (e.g.

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dehumidification). The catering services include contract catering (e.g. hospitality services and staff dining), vending machines, event catering, and confectionery services (e.g. coffee shops and fruit service). Additionally, the support services consist of activities related to the front office (e.g. reception and hostess services), back office (e.g. mail handling, call centers and office supplies), welfare facilities (e.g. sports facilities and fruit services) and labor supply (e.g. temporally workers and recruitment). ISS focuses on keeping its customers employees and properties safe, thus security services contain these activities: physical security (e.g. manned guarding and emergency response), surveillance (e.g. monitoring and alarm response), technical installations (e.g. car park management, fire and gas detection), work place emergency management (e.g. first aid services and emergency evacuation) and consulting services (e.g. security training). Lastly, the company offers its customers Integrated Facility Services, whereby the different services can be combined into one solution in order to reduce overhead costs as well as allocate resources more efficiently (issworld.com). At the end of 2010, ISS owners were considering to change the capital structure of the company once again either by selling ISS to another private owner or to let it go public (Webb and Espana, 2010). Even though several equity funds were preparing bids for ISS, the owners decided to go company public (www.altassets.net). The IPO was planned for March 2011 on the Copenhagen stock exchange, but was postponed due to the instability of the financial markets (www.issworld.com). For the purpose of the calculations in this paper, it is assumed that ISS will go public in 2012.

3. Problem statement The purpose of this master thesis is to analyse and discuss different theories of corporate valuation, determine which theories are relevant for valuing ISS, and apply them to estimate ISS firm value. The theories that will be examined include the discounted cash flow (DCF) model, the dividend discount model (DDM), the residual income model (RIM), real options valuation (ROV) and valuation using multiples. In relation to the DCF model, two methods for determining the expected rate of return on a companys stock will be evaluated, these are: the capital asset pricing model (CAPM) and the Fama and French three factor model. The corporate valuation theories will be analysed based on a literature review that for example includes a discussion of advantages and disadvantages of the different theories.

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In relation to valuing ISS, a strategic and a financial analysis of the company will be performed. In the strategic analysis, ISS corporate environment will be studied using the PESTEL analysis, Porters five forces, and the SWOT analysis. Furthermore, ISS core competences will be identified. In the financial analysis, the relevant corporate valuation theories will be applied to ISS. As part of the analysis, ISS financial statements will be reformulated in order to identify the companys main value drivers. Based on the financial analysis, ISS enterprise value, equity value and share price will be determined. Additionally, the equity value of ISS, estimated based on the strategic and financial analysis will be compared to official equity value estimates published by professional analysts, and the estimated share price will be compared to the expected IPO share price published by ISS. If there is a considerable difference between the results, possible reasons for the difference will be discussed. The structure of this paper is as follows: sections 1 to 2 include an introduction and the description of ISS, in sections 7 to 9 corporate valuation theories are discussed and the relevant theories are identified, in sections 11 to 14 the strategic and financial analysis of ISS are performed, and finally sections 15 and 16 contain a discussion of the results and a conclusion of the study. Appendix O contains an overview of the thesis structure.

4. Definitions Due to the fact that formulas are stated with different notations in the literature, the notations of some formulas are changed when necessary in order to achieve notation consistency in this paper. Furthermore, due to the fact that there are several abbreviations used throughout this paper, a list of abbreviations has been made in appendix P.

5. Delimitations This section states the delimitations relevant for this paper. Only financial theories will be analysed in depth and discussed based on a literature review. Marketing models will not be discussed, but just applied to the case company due to the fact that this paper focuses on a financial valuation of

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the company. Corporate valuation theories will not be derived1 in this thesis, because the main focus is on the possible application of these theories to a real life company.

6. Data collection and validity All the information that is used in this thesis whether it is from news papers, the internet or books is publically available. The main source of financial information about ISS is from ISS annual reports. However, some of the information from ISS is considered to be subjective and providing a more positive picture of ISS and has thus been used with precaution. The data from other sources is considered to have an objective opinion about ISS.

7. Analysis of the corporate valuation theories In general the value of an asset equals the present value of the cash flows that it will generate in the future. This methodology can be used to value single projects, investments and also whole companies. What matters in relation to the present value of the cash flows is the timing of the cash flow and the risk level (Benninga and Sarig, 1997). According to Damodaran (1996), valuation methods can be generally grouped into the following three categories: discounted cash flow valuation, relative valuation and contingent claim valuation. Discounted cash flow methods forecast future cash flows of an asset, and discount them at a given rate in order to get the assets present value. Relative valuation methods determine the value of an asset by comparing variables such as earnings, cash flows, book value or sales, and contingent claim valuations apply option pricing models to measure the value of an asset. These methods can lead to different results depending on the assumptions used in each method. Benninga and Sarig (1997) advise to use more than just one valuation method to estimate the firm value. It is advised to use more than one method because there is a great deal of uncertainty in relation to value estimation as it involves predicting future returns of the company, and if the different methods give similar results it implies that the estimated value is sensible. Due to the advice from Benninga and Sarig (1997) various valuation models will be discussed in this section and the relevant methods will be used to analyse ISS in sections 12-14

1

For example the underlying assumptions of the models will not be discussed

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7.1 The discounted cash flow method In the discounted cash flow (DCF) method, the value of an asset is calculated based on the present value (PV) of future cash flows generated by the asset. These cash flows are discounted by using a rate that represents their risk (Damodaran, 2010 3). According to Miller and Modigliani (1961), the DCF approach can be used to value a whole company, (Cooper and Argyris et al., 1998) whereby the company is considered as a lot of projects combined. To determine the firm value, the PV of future cash flows from all the projects in the firms operations are identified (Penman, 2010). Furthermore, the cash flows in the DCF method can be estimated using different cash flow proxies such as dividends, free cash flow (FCF) or accounting earnings (Koller et. al, 2005). The DCF model using the dividends proxy is discussed in section 7.2, the DCF model using the FCF proxy is discussed in section 7.1 and the DCF model using accounting earnings, i.e. the residual income model is discussed in section 7.3. Given very strict consistent assumptions, valuation using the DCF method with the various cash flow proxies should result in similar firm value estimates. However, empirical evidence shows that the different proxies lead to different firm value estimates (Torrez et al. 2006). There are two approaches to the DCF analysis: one is to value the firm as if it was only equity financed: i.e. the equity valuation and the other is to value the whole firm including all its claimholders: i.e. the firm or enterprise valuation (Damodaran, 1996). Since the focus of this paper is on firm valuation, the latter method is discussed further. The DCF model can be set up by using four steps suggested by Penman (2010). In the first step, a companys free cash flow is estimated to a given year. The second step involves determining the weighted average cost of capital (WACC) and discounting the free cash flows using this discount rate so as to determine their net present values (NPV). Additionally, the continuing value is identified in the third step, and the determination of the company value is explained in step four. Lastly, an evaluation of the DCF method is made. Appendix A includes an overview of the steps in the DCF model. 7.1.1 Step 1: The calculation of free cash flow Free cash flow is the difference between cash flow from operations and cash investment in operations (Penman, 2010 p. 341). It is the cash flow that is available to investors after investments in fixed assets and working capital (Brealey and Myers et al., 2007). FCF is also independent of leverage (Koller et. al, 2005) and it determines a companys capability to pay off its debt and equity claims (Penman, 2010). Additionally, FCF is a good indicator of the companys

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ability to generate cash and therefore also profit. A negative FCF does not mean that the companys operations are unprofitable, but it could be a sign that the company is growing fast and is therefore making large investments. Fast growth is good for the company as long as it is earning more than the cost of capital on its investments (Brealey and Myers et al., 2007). In order to forecast a companys future cash flows, it is necessary to evaluate its past financial performance first. This way the main drivers of a companys value: the return on invested capital (ROIC), the growth rate and free cash flow can be identified. Moreover, it is also possible to conclude whether the company has generated value, if it has grown as well as compare its performance to competitors. However, ROIC and FCF cannot be calculated directly from a companys reported financial statements, thus it is necessary to reformulate these statements so as to identify a companys operating items, non-operating items and financial structure (Koller et. al, 2005). The limitations of free cash flow include its inability to identify value created that does not involve cash flows, the fact that it evaluates investments as loss of value, and the option to increase the FCF by e.g. investing less (Penman, 2010). 7.1.2 Step 2: The weighted average cost of capital The weighted average cost of capital is the rate of return that investors expect from investing in a given company instead of other companies with similar risk (Brealey & Myers et al., 2007). As mentioned earlier, WACC is used to discount the free cash flow. It is one of the most important features of the DCF model, because a small change in WACC can lead to major changes in firm value (Steiger, 2010). To successfully apply WACC, it is important to have uniformity between the inputs of WACC and free cash flow regarding factors such as duration and the risk of financial securities. WACC and FCF must both be calculated on an after-tax basis and in the same currency (Koller et. al, 2005). If a firm is considered as a combination of projects, as mentioned earlier, then WACC is the suitable discount rate representing the riskiness of the cash flows from all the projects (Penman, 2010). WACC can be calculated by determining its three components: the after-tax cost of debt, the cost of equity and the companys target capital structure (Koller et. al, 2005). Thus, the formula for WACC is (Brealey & Myers et al., 2007): WACC = Where D/V = Target level of debt to enterprise value using market values

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E/V = Target level of equity to enterprise value using market values = cost of debt = cost of equity = companys marginal income tax rate The following sections include an explanation of how to determine the after-tax cost of debt and the cost of equity in the WACC formula. The cost of debt The cost of debt is the rate that a company pays to borrow money (Damodaran, 2009). There are three factors needed to calculate the cost of debt: the risk free rate, the default spread and the tax rate (Damodaran, 2010). The risk free rate is discussed below in relation to the CAPM. The second factor, which is the default spread2 can be determined in three ways, which are chosen depending on the company to be evaluated: a) if a company has outstanding bonds, then the cost of debt can be calculated by applying the current market interest rate (yield to maturity, YTM) on the companys long-term bonds, b) if a firm has bond ratings from rating agencies such as Moodys or Standard and Poor (S&P) , the default spread can be determined based on the ratings (Steiger, 2010), and c) if the firm is not rated, an artificial rating can be made based on the firms interest coverage ratio (EBIT/ Interest expense) (Damodaran, 2009)3. The last part for determining the cost of debt is the tax rate. Interest payments on debt are subtracted from income before tax is determined, thus taking on debt can act as a tax shield (Brealey & Myers et al., 2007). The formula for the after tax cost of debt is (Damodaran, 2010): After tax cost of debt = (Risk free rate + Default spread) (1- marginal tax rate) The advantages of debt besides the tax shield include committing managers to operate efficiently in order to fulfill principal and interest payments and encouraging lenders to monitor the firm

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Borrowers of the firm bear the risk of not getting their expected payments (interest and principal). To compensate for this risk, the lenders add a default or credit spread to the risk free rate (Damodaran, 2010). A credit spread is the difference between the risk free rate and the interest rate that a company pays to borrow money (Steiger, 2010).3

In option one, long-term bonds are applied because short term bonds do not match the duration of the companys free cash flow forecasts (Koller et. al, 2005). Option one is suitable if the firm has liquid bonds that represent the overall debt of the firm. In option three, the higher the interest coverage ratio the higher the ratings.

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(Binsbergen et al., 2010). Even though interest expenses are tax deductible, companies do not borrow to the maximum, because of the disadvantages of extreme borrowing such as financial distress (Scholze, 2010). There is also an explicit cost and implicit cost to debt financing; the explicit cost is the interest rate that bond holders require from the company and the implicit cost relates to the fact that when a firm borrows more money, its equity becomes more risky, thus equity holders demand a higher return to compensate for this risk (Brealey & Myers et al., 2007). The cost of equity The cost of equity can be calculated by using asset pricing models that help to determine the expected rate of return on a companys stock. There are three asset pricing models: the capital asset pricing model (CAPM), Fame and French three factor model and the arbitrage pricing theory (APT). The main difference between these models is the way they identify a stocks risk. The CAPM, which is the most widely used model, states that a stocks risk depends on its sensitivity to the stock market, Fame and Frenchs model claims that a stocks risk is based on its sensitivity to three factors: the stock market, a portfolio based on firm size and a portfolio based on book-tomarket ratios, and the APT extends Fame and Frenchs model, by arguing that a securitys rick depends on even more factors (Koller et. al, 2005; Bartholdy and Paula, 2003). However, the APT does not specify these factors, and for this reason it will not be discussed further in this paper. Instead the two main models: the CAPM and Fame and Frenchs model are discussed below. The capital asset pricing model The capital asset pricing model, which was introduced by Sharpe (1964), Linter (1965) and Black (1972) based on Markowitzs (1952) portfolio theory, explains the relationship between risk and expected return and it is stated as (Torrez et al. 2006):

Where:

= expected return on security i = risk free rate = sensitivity of the stocks return to the return on the market portfolio = expected return of the market

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Based on the CAPM model, a stocks expected return is determined by two things: a) the time value of money and b) the risk premium. The time value of money is represented by the risk free rate (rf), i.e. investors are compensated for putting their money in any investment over a period of time. Additionally, the extra return that investors demand for taking on risk is called the risk premium i.e. premium , this return depends on the risk measure (Brealey & Myers et al., 2007). , and the market risk

In addition, risk can be divided into unique risk (unsystematic or firm-specific risk) and market risk (systematic risk). Unique risk is specific to the individual firm and possibly its direct competition and it can be diversified away as the investor increases the number of securities in his portfolio. Market risk, which is caused by macroeconomic factors such as changes in interest rates, oil prices and foreign exchange rates that affect the whole stock market, cannot be diversified away (Brealey & Myers et al., 2007). According to the CAPM, the risk free rate and the market risk premium are the same for all companies; it is only beta that is different for each company (Koller et. al, 2005), thus the main idea of the CAPM is that the variance of a stock by itself is not an important determinant of the stocks expected return, instead it is the covariance of the stocks return with the return on a given market index that is important. Thus, the CAPM is developed as a method to evaluate market risk (Mukherji, 2011; Hillier et al., 2008). The following sections consist of a discussion of the inputs to the CAPM: the risk free rate, beta, and the market risk premium as well as an evaluation of this theory. Determining the risk free rate Risk is determined as the possibility that an investment's actual return will differ from the expected return, (Damodaran, 2008) whilst for a risk free investment, the actual return will always be equal to the expected return (Vukovi, 2010). This will occur only if these two conditions are fulfilled; that there is no default risk and there is no reinvestment risk. No default risk means that there should be no chance that the issuer of the security will not accomplish his contract, and no reinvestment risk implies that there ought to be no possibility that interest earned from an investment may have to be reinvested at a lower interest rate. In conclusion, if the requirements for a financial instrument to be risk free are the nonexistence of default risk and reinvestment risk, then the risk free rate can only vary, depending on the investment period (Damodaran, 2008).

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The risk free rate can be determined by looking at the long-term government default-free bonds4. Government bonds have different maturities ranging from for example one months to 20 years (e.g. for U.S. Treasury issue bonds). Considering the fact that different bonds have different maturities that can lead to different yields to maturity, a companys cash flows must be discounted by using a bond with a similar maturity. For companies in the U.S., the most frequent applied proxy is a 10year government bond. For European firms, the 10 year Germany Eurobond can be used, because it is believed to have a higher liquidity and lower credit risk compared to bonds of other European countries. Moreover, as mentioned earlier, in order to consider inflation consistency, the cash flows and the cost of capital should be stated in the same currency (Koller et al., 2005). Estimating beta As stated earlier, a stocks expected return depends on its beta, which is a measure of how much the stock price fluctuates in relation to the market (the stocks volatility) (Koller et. al., 2005). The beta value for the market is 1.0, stocks with a beta greater than 1.0 are sensitive to market fluctuations whilst stocks with a beta less than 1.0 are less sensitive to market fluctuations (Brealey and Myers et al., 2007). Unfortunately, beta cannot be directly observed, thus it must be estimated. This is often done by using the market model, whereby the returns on a stock are regressed against a markets return over a given time period. The market model can be stated as (Damodaran, 1999):

Where: Ri is the return on stock i, Rm is the return on the market index and beta () is the slope of the regression. While the market model seems good in theory, there are some practical issues related to estimating the beta because this theory does not specify the market index, time period and return interval5 to be used. Therefore, the betas estimated by different analysts for the same firm will be different depending on the time period, return interval and market index applied (Damodaran, 1999). According to the CAPM, investors are risk averse and they demand a higher return for taking on additional risk as stated earlier. The advantage of the beta, which is the mostly used measure of an

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Koller et. Al (2005) defines the risk free rate as a return on a portfolio or security that does not correlate with the market ( i.e. with a CAPM = 0). In theory, a zero-beta portfolio can be calculated; however the process will be expensive and complicated. This is why long-term government default- free bonds are often used. These bonds are not entirely risk-free and have very low betas. 5 Stock returns can be determined daily, weekly, monthly, quarterly or yearly.

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assets riskiness (Shalit and Yitzhaki, 2002) is that it provides a quantifiable way of evaluating the required return on a risky investment as well as helping investors recognize attractive stocks based on their risk preferences. Additionally, beta is a good standard for discussing market efficiency, and for evaluating a stocks performance compared to the market (Liang, 2006). Beta is a very important part in the CAPM model and the usefulness of CAPM mostly depends on the accuracy of beta (Grsoy and Rejepova, 2007). As stated earlier, beta measures market risk by evaluating the volatility of a stock to a given index. One of the disadvantages of beta is the fact that it only considers the risk caused by macroeconomic factors on a companys stocks, and firm-specific risk is not fully evaluated by the beta. Beta is therefore an unreliable measure that does not compute the total risk of a firm, because a given firm may have a high level of firm-specific risk but a low level of market risk (Gunlaugsson, 2007). Another problem with betas from a regression analysis is that they are based on historical data and companies tend to change over time6. Thus historical betas are hardly good representatives of the firms current and future structure (Damodaran, 1999). Moreover, beta estimates are noisy since they are statistical estimates, with standard errors (Damodaran, 2011, p.5). In Fama and French (1992)s paper about the trustworthiness of past betas, they concluded that the CAPM beta does not explains the last 50 years of average stock returns. Damodaran (2011) suggests improving the accuracy of the regression betas by using bottom up betas. This refers to a beta that is estimated by using the average betas of similar firms in the industry. This beta should also be adjusted for variations in financial leverage. Furthermore, unlike public firms, private firms do not have past price information to use in a linear regression. Private firm owners, e.g. private equity funds often choose to invest money in just one or few companies and therefore they do not have very diversified portfolios compared to public firm owners7, thus estimating beta for private firms needs to be done in a different way in order to get a reliable beta. To get a beta for private firms, the analysts can for example 1) regress accounting earnings against changes in earnings for a market index to get accounting betas, 2) regress the betas of a given market index to a private firms ratios such as book debt/equity and6

Firms for example: terminate businesses, invest in new businesses and acquire firms. They also change their financial leverage by issuing or paying off debt as well as pay dividends and buy back shares. Firms also grow over time. All these events will change a firms beta (Damodaran, 1999). 7 One of the assumptions of the CAPM is that investors have well diversified portfolios, in which they diversify all firm-specific risk, thus only market risk is relevant as mentioned earlier. For private firms, beta understates the effect of market risk.

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book value of assets to get fundamental betas or 3) look at average betas for similar public firms to get bottom-up betas (Damodaran, 2009). Calculating the market risk premium The market risk premium (MRP) is a challenging measure to estimate, because the

expected return on the market cannot be directly observed (Bowman, 2001). Therefore, a universally accepted model for estimating the MRP does not exist. It is common practice to determine the market risk premiums by using past risk premiums, this refers to premiums that investors have earned over long periods for example 75 years. An alternative option for determining the MRP involves calculating a forward looking premium from current stock price levels and expected future cash flows (Koller et al., 2005). Assuming that investors make their expectations based on their past experiences, the average of historical returns can be expected to have the main influence on investors future expectations (Officer and Bishop, 2008). If investors who are believed to be risk averse, havent changed their attitude towards risk in the past 75 years, then historical returns are a sensible proxy for future expectations (Koller et. al, 2005). Bowman (2001) claims that historical estimates are not suitable to be used in the CAPM, which is a forward looking model that relies on investors future expectations. However, due to the lack of reliability in forecast methods, historical estimates are often applied in the CAPM (Officer and Bishop, 2008). Evaluation of the CAPM Having introduced the CAPM in the previous sections, this section will include an evaluation of this theory. The main benefit of the CAPM is that, it is helpful in explaining the relationship between risk and return of a given investment (Fame and French, 2004). Unfortunately, empirical evidence shows that the CAPM is not completely valid in explaining stock returns, instead there are other factors besides beta that give better reasons (Gunlaugsson, 2007) such as firm size and book-tomarket ratios (Fame and French, 1992). Moreover, Roll (1977) argued that since a true market portfolio cannot be identified, or replaced by a proxy such as a stock market index, the CAPM can never be truly tested (Grsoy and Rejepova, 2007). There is also the challenge of testing the market model, i.e. the joint hypothesis problem, where there is simultaneous testing of both the model and the market, and this makes the results of the test inconclusive (Hillier et al., 2008). In conclusion, the CAPM is the most applied and criticized model in finance (Damodaran, 2010). Page 20 of 112

Fama-French three-factor model As already mentioned, the CAPM model is useful in explaining portfolios that are related to the market. However, if a portfolio is not closely related to the market, the CAPM is less helpful in explaining its returns. For this reason, Fama and French (1992; 1993) developed the CAPM further by suggesting that besides market risk, a stock portfolios risk also depends on the firm size and the book-to-market ratio (Fama, 2007). In the Fama-French model, the excess returns on a given stock are regressed on: the excess returns on the market (like in the CAPM), the excess returns on small minus big stocks (SMB) and the excess returns on high book-to-market stocks minus low book-tomarket stocks (HML) (Koller et al., 2005). SMB represents the size premium, i.e. the fact that stocks of companies with small market capitalization (cap) tend to result in higher returns than large cap stocks. HML represents the value premium, i.e. the tendency that companies with high book-tomarket ratios (value stocks) generate higher returns than those with low book-to-market ratios (growth stocks) (Womack et al., 2003). When calculating the Fame-French regression analysis, returns for three portfolios: the market portfolio, the SMB portfolio and the HML portfolio are needed (Koller et al., 2005; Bundoo 2008).The regression can be stated as (Koller et al., 2005): Where: is the return on portfolio, + is a constant, is the risk free rate, is the coefficient for

the excess return of the market portfolio over the risk free rate, market,

is the return of the stock

is the coefficient for the excess average return of portfolios with SMB, represents SML, is the coefficient for the excess average return of HML portfolios,

represents HML, and is the error term. The three-factor model implies that investors can target a given level of return by weighting their portfolios as desired on each of the three risk factors (Womack et al., 2003). Furthermore, small cap stocks yield a higher expected return because they are believed to be more risky (Fama, 2007). This is for example due to the fact that they offer fewer opportunities for diversification and they are less capable of dealing with negative financial results (Womack et al., 2003). In their 1995 study, Fama and French (1995) concluded that companies with high book-to-market ratios are often distressed compared to those with low book-to-market ratios. For this reason, investors of firms with high book-to-market ratios achieve greater expected returns for holding less beneficial and more risky stocks (Bundoo 2008).

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Evaluation of the Fama-French three-factor model In conclusion, empirical evidence shows that the Fama-French model has a higher explanatory power than the CAPM with its R2 values of 0.95 and above (Womack et al., 2003). In other words a combination of beta, size, and value explains 95% of a diversified portfolios return. Unfortunately, similar to the CAPM, the Fama-French model also has some practical issues regarding for example the amount of data to be used for estimating the risk premium, the return interval and the time period for the regression. Koller et al. (2005) suggests that these practical issues exist because the Fama-French model is relatively new. Additionally, several studies (Bartholdy and Peare, 2003; Lam, 2005) have compared the results from the one-factor model (CAPM) and the three-factor model, and have concluded that neither model is better than the other. Overview of the WACC formula As stated earlier WACC is the expected rate of return on a firms securities (e.g. equity, debt and preferred stock), whereby each security is weighted proportionally on the firms market value. The WACC formula is generally written as if the company only has two securities: debt and equity in its capital structure. The cost of debt is the current market interest rate that is required by a firms bondholders and the cost of equity is the expected return on a firms stocks. If a firms capital structure changes, the rates of return demanded by bondholders and stockholders will change; for instance if a company issues more debt, this will increase the risk of both its debt- and stockholders, who will require a higher return to compensate for this risk as mentioned earlier. However, this does not automatically indicate that the WACC will increase. Research by Miller and Modigliani, claims that by assuming that the company does not pay taxes, WACC will remain the same regardless of whether the amount of debt and equity changes (Brealey & Myers et al., 2007) Furthermore, in order to determine the appropriate capital structure in the WACC formula, it is important to use target weights instead of the companys current capital structure. This is because a companys capital structure may change in the coming years, as mentioned earlier, and using todays structure may lead to an overestimation (or underestimation) of the value of tax shields for a firm whose debt level may increase (or decrease) (Koller et. al, 2005). Koller et. al, (2005) suggest

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determining a companys target capital structure by first examining its current capital structure and then forming some expectations about the future. In order to calculate the WACC, the after tax cost of debt, the cost of equity, and target value weights are inserted in the WACC formula. This rate is used to discount the free cash flows and the continuing value to the present. Thus, the next section discusses the calculation of the continuing value. 7.1.3 Step 3: Identifying the continuing value A companys value can be determined by dividing the expected cash flows into two periods as stated below (Copeland et al., 2000; Russell, 2007; Jennergren, 2008;): Value = PV of cash flows during the explicit forecast period + PV of cash flows after the explicit forecast period

The explicit forecast period is the period, in which detailed forecasts of a companys cash flows are made for a given period up to a specific year, the horizon year (H). The second part of the formula is the continuing value (terminal value or horizon value), which is the value of the firm after the explicit forecast period. According to Brealey & Myers et al. (2007), a firms continuing value can be stated as:

Where: PVH is the value at horizon, i.e. the value of FCF in periods H+1, H+2 etc. The continuing value can be determined in two ways: one way is to assume that the firm will be liquidated in the horizon year and estimate the value of its assets in that year (Damodaran, 2010 2). The other method is to use the constant-growth formula, by assuming that the firm is going concern, i.e. it will continue to grow up to infinity after the horizon year (Brealey & Myers, 1991; Russell, 2007). Since the analysis of ISS will be based on the assumption that it is a going concern company, the constant-growth formula is discussed below. In a going concern firm, it is not realistic to precisely forecast free cash flow to the year infinity, thus the horizon year, which is the year when the firms business is expected to have a stable growth rate, is often used (Brealey and Myers, 1991; Morris, 1994; Russell, 2007).

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To use the constant-growth formula, the analyst needs the FCF for the first year after the horizon year (year H+1), a long-run growth rate (g) and WACC as the discount rate (r), thus the formula for the PV at horizon is (Brealey and Myers, 1991):

Even though theoretically the computation of the continuing value seems easy, in reality it is challenging to estimate the development of a company between the horizon year and infinity (Financial Times, 2005). Several researches claim that continuing value calculations often account for more than half of the total firm value, and that a small change in the perpetual growth rate leads to major changes in firm value (Morris, 1994; Brealey & Myers et al., 2007; Steiger, 2010). The large impact of the continuing value can be due to the fact that a firms cash outflows in the explicit forecast period are caused by investments that are expected to generate cash inflows after the explicit forecast period (Copeland et al., 2000). 7.1.4 Step 4: Calculating the company value Finally, the value of the firm can be determined as the discounted free cash flow up to a horizon year (H) plus the forecasted value of the firm at the horizon, that is (Brealey & Myers et al., 2007):

Once the company value is estimated, the equity value can be calculated by subtracting net debt and minority interest from the company value (Penman, 2010). As mentioned earlier, the DCF analysis involves predicting free cash flows for the next five to fifteen years. For this reason, it is necessary to make assumptions about a companys future situation (Steiger, 2010). Predicting the future always involves uncertainty and risk (Koller et. al, 2005) but methods such as scenario analysis, sensitivity analysis, decision trees and simulations can help in analyzing the uncertainty related to the valuation results, as well as ensure whether the assumptions used are realistic (Damodaran, 2007). Scenario and sensitivity analysis will be used in this paper in order to analyze the effect of different assumptions about both macroeconomic and asset specific variables.

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7.1.5 Evaluation of the DCF method After looking at the procedure of the discounted cash flow analysis, this section includes an evaluation of the method's strengths and weaknesses. One of the advantages of the DCF method is that it is intuitively easy to understand; the value of a company depends on its future cash flows (Morris, 1994). This method focuses on cash flows, which is a real measure that is simple to explain. The DCF method also works regardless of a companys accounting principles (Penman, 2010). When analyzing a company using this method, the analyst performs a useful exercise by identifying a companys value drivers as well as examining its growth and risk (Damodaran, 2010 3). In general, the DCF method is perceived to be the best method for company valuations, but only if the company is profitable (Russell, 2007). The limitations of the DCF method include its large dependency on WACC and continuing value assumptions, this is because small changes in these values have a considerable impact on firm value as stated earlier ( Steiger, 2010; Copeland et al., 2000). For this reason, the DCF method can be easily manipulated by the analyst in order to achieve a given result. Additionally, it requires a lot of information to determine a companys future cash flows, growth rates and discount rates. Similar to any other analytical tools, the DCF must be used with caution. The results from any model depend on the models inputs: it is garbage in, garbage out(Damodaran, 2010 3 p. 11).

7.2 Dividend discount model (DDM) According to Brealey et al., (2009), DDM is a stock valuation tool that is used to determine stock prices as the present value of future expected dividends discounted back at a certain rate. Michaud and Davis (1982), state that one of the main objectives of the DDM is to improve the process of stock valuation. The simplest DDM model is the DDM with no growth, where the discount rate (r) equals the rate of return demanded by investors investing in other stocks at the same risk level, is the value of the stock and as (Brealey et al., 2009): is next years dividend. The DDM with no growth can be stated

A more advanced DDM is the DDM with constant growth. This model assumes that a companys dividend payouts grow over the years. Because it is too time consuming to forecast dividends for every single year in the future, the calculations are simplified by forecasting dividends for the next

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period, and then forecasting a single growth rate with which the dividends will grow in all the following periods. It is assumed that there is an infinite number of periods in the model and the dividend growth rate (g) has to be less than the discount rate (r) (Brealey et al., 2009). The DDM with constant growth can be written as:

If the growth is not constant the formula above cannot be used. Additionally, for mature industries, growth is fairly stable and constant growth DDM is a good model. According to Penman (1998), it is common in practice to forecast dividends for a limited number of years and then to calculate a terminal value at the horizon; this corresponds to the DDM with non-constant growth. In order to use the DDM with non-constant growth, it is necessary to set the investment horizon (H). Until the investment horizon the dividends should be estimated for each period individually and after the investment horizon the companys growth is expected to settle down. In order to estimate the stock price, the dividends until the investment horizon year are discounted back to present value and at the end the terminal value is added. The terminal value is the estimated present value of the stock price at the horizon (Brealey et al., 2009). The formula for the DDM with non-constant growth is:

Moreover, the DDM can also be used to determine the cost of equity for a company. In the simple models, it is assumed that the only cost of equity a company has is the dividend payout. If the market price of the firm is known, the rate of return can just be isolated and it equals to the companys cost of equity (Mills and Robertson, 2004).

According to Penman (1998), it is often claimed in the literature that the DDM does not perform very well when company value with a finite horizon has to be estimated. The calculation of terminal value is considered to be problematic in the financial literature, and many different formulas for calculating terminal value have been developed over the years. Whilst using alternative valuation models such as discounted cash flow model or residual income model often results in a firm value that is similar to the firm value estimated using the dividend discount model, it is the different ways

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of calculating terminal value that cause the largest variations (Penman, 1998). Terminal value basically consists of an estimate of all future cash flows, or in the case of DDM, all future dividends, and these are discounted back and summed up to a single number. According to Penman (1998), a calculation of terminal value is only needed if the discounted payoffs up to the horizon do not capture the total value of the firm. A more detailed discussion of terminal value is been given in section 7.1.3. 7.2.1 Advantages and disadvantages of the DDM According to Hand and Landsman (2005), there are various issues related to the use of the present value of expected future dividends as an estimate for the company value. In short, Hand and Landsman (2005) argue that dividends are often positively priced even when they should not be due to the financial situation of the company, and when these dividends are used to estimate the firm value the result is often wrong. Hand and Landsman (2005) suggest that dividends are positively priced because they are based on public information that is trying to predict a companys future abnormal earnings. This means that the price of the dividends is correlated with the analytical forecasts in the market, which can often be wrong, and not based on internal measures for a firms ability to achieve abnormal earnings. Hand and Landsman (2005) find in their analysis that investors often misprice the current earnings and the equity value of a firm which leads to positively priced dividends. In contrast to the Hand and Landsman (2005) study, Fama and French (1998) and Akbar and Stark (2003), find a positive relation between firm value and dividends. The results of their analysis show that dividends are based on information about future expected cash flows and can therefore be used to estimate firm value. However, Michaud et al. (1983), argues that the DDM contains little market valuation information and the firm value estimated using the DDM is therefore subject to error. According to Hand and Landsman (2005), a main problem is information asymmetry between the information available to the managers of the company and the information available to the shareholders. The managers can pay out a certain amount of dividends to send a certain signal out to the shareholders and the market. For example managers can pay out high dividends to signal that they are doing a very good job and are expecting high abnormal returns in the future. This is a situation where the principal-agency problem may arise, i.e. managers who act as agents for the principals (the shareholders), will act in their own best interest (Grossman and Hart, 1983). According to Hand and Landsman (2005), under the agency cost hypothesis, it is argued that dividends are a more reliable measure if the current earnings of the company are positive and the

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company has free cash flow. On the other hand, under the profitability signalling hypothesis, it is argued that dividends are more reliable as a measure, if the company is currently suffering from negative earnings, because if the company can afford to pay out dividends in such a state it must be because the managers are almost certain of future positive earnings. Penman (2010) states that dividends are not a good measure to estimate firm value, because the company can obtain loans to finance the dividend payouts, and in this case dividends do not represent the earnings the company generates. According to Miller and Modigliani (1961), the dividends are irrelevant to the calculation of firm value. They show in their article that firm value depends on the firms earnings and level of investment. Miller and Modigliani (1961) specifically point out the irrelevance of the dividends in relation to an acquisition. If an investor is interested in acquiring a firm, the investor is free to determine the level of the dividends in the future and the firm value calculated based on future expected dividends does not make sense in that case. The firm value important to the acquirer is based on the expected earnings of the firm and its investment opportunities, which will provide additional earnings in the future. 7.2.2 Evaluation of the DDM The DDM is a type of discounted cash flow model as mentioned earlier. The essence of the DDM is the fact that it uses dividends as the proxy for cash flows. Using dividends to estimate firm value is widely criticized in the literature mainly because dividends are more often than not determined by the management, so they can be subject to manipulation and are therefore not as reliable as other proxies for cash flows. Additionally, using the DDM to estimate the value of private companies is problematic since private companies do not pay out dividends in the same way as public companies.

7.3 Residual income model (RIM) Ohlson (1991) argues that due to the dividend policy irrelevance concept presented in Miller and Modigliani (1961), the value of a firm should not be calculated based on dividends, but based on a more fundamental variable which does not depend on dividends. Based on the analysis Ohlson (1991) concludes that the variable earnings is a good replacement for dividends because earnings do not depend on dividends and could be used to estimate company value. As a continuation of his research from 1991, Ohlson (1995) defines a valuation model, which is based on residual income. However, according to Xiaoquan and Bon-Soo (2005), the idea of a residual income model can be traced back to Preinreich (1938) and is thereby not a new discovery. Page 28 of 112

According to Ohlson (1995), residual income is the amount by which a companys net income exceeds the required return on the firms equity. The residual income is thereby a measure of the additional value created for the shareholder, which is also known as abnormal earnings or economic value added (EVA). Ohlson (1995) derives the RIM from the DDM using among other things the clean surplus relation to prove his point. The clean surplus relation states that the current book value equals beginning book value with an addition of current earnings and a subtraction of current dividends. Mathematically the clean surplus relation is defined as:

Where, B is the book value for period (t and t-1), E is the earnings for period t and D represents the dividends for period t. Ohlson (1995) derives the formula for the residual income model by isolating the dividends in the clean surplus relation, and replacing the dividend term in the dividend discount model with the obtained equation. After replacing the dividend term, Ohlson (1995) gets a formula for calculating firm value, which does not contain dividends. The residual income model is given by:

The RIM calculates the firm value by adding two parts: the current book value, future periods (RIt = Et rBt-1)8, and re is the required rate of return on equity.

plus the present

value of future residual income. Where Bt is the book value in period t, RIt is the residual income in

The residual income model, unlike other valuation models, puts emphasis on accounting data instead of financial data. All the numbers except for the required rate of return on the firms equity are accounting numbers, which can be obtained from the firms financial statements (Ohlson, 1995). The book value used in the model is a sum of the book value of owners equity and the book value of operating net assets, which can be obtained from the balance sheet. And the residual income is based on operating earnings which can be obtained from the income statement (Skogsvik, 2002). 7.3.1 Advantages and disadvantages of the RIM According to Ohlson (1995), the residual income model moves the focus away from the wellknown dividend discount model and instead the value of the firm is calculated as a sum of current8

RI is equal to net income in period ( Et) minus the cost of equity in currency i.e re * income is net income minus a charge for the use of shareholders capital.

. In other words, residual

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book value and present value of expected future abnormal earnings. The fact that the RIM is based on book value and abnormal earnings is a major advantage according to Xiaoquan and Bon-Soo (2005) because they believe that these variables contain more important information in relation to firm value than dividends alone, which are used in the DDM. Additionally, by estimating earnings instead of dividends, it is necessary for the analysts to investigate the factors explaining the firms performance which leads to a deeper understanding of the companys activities (Bernard, 1995; Penman, 2007). Furthermore, Xiaoquan and Bon-Soo (2005) find the fact that the RIM does not use dividends to calculate the firm value very beneficial because it can easily be applied to companies, which do not pay out dividends on a regular basis. One of the disadvantages of using earnings in firm valuation is that future earnings are affected by external events, which cannot be predicted at the time of estimation. Thus, valuations based on earnings can result in imprecise value calculations (Bernard, 1995). Xiaoquan and Bon-Soo (2005) state that the dividends are present in the RIM, they are just defined broadly as the difference between earnings and changes in book value, and these dividends include both regular dividends and other types of cash payouts (e.g. share repurchases) to the shareholders. According to Penman (2007), the fact that the RIM relies on accounting numbers can both be seen as an advantage and a disadvantage. It is an advantage that the already recognized book values can be used in the valuation model. On the other hand, accounting numbers can be manipulated and this will affect the calculated firm value. For this reason, it is important to evaluate the quality of the numbers in the financial statements before applying them in order to obtain a useful result (Rees ,1997). Even though the RIM is sensitive to accounting manipulation, there are some types of manipulation it is actually protected from. If accrual accounting is used to create earnings by for example recording lower book values at present and recognising higher income in the future, it looks like the company is earning more, but in reality no additional value is created. In the RIM, this type of accounting will not result in a higher firm value because the beginning book value will be used in the calculation (Penman, 2007). An important observation made by Skogvik (2002) in relation to the RIM is the fact that it is not correct to treat the required rate of return on the firms equity as a constant if the firms capital structure is expected to change over time. However, applying different rates of return to the model based on the expected capital structure makes the model much more complicated.

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When applying the RIM, the forecast horizon should also be considered like in the other valuation models. The RIM can be constructed in a way that is similar to the DDM model, where residual earnings for a number of years are forecasted and discounted back and a continuing value is added at the end to capture the added value from residual earnings at the horizon. The formula for the residual income model with a continuing value calculation can be stated as (Penman, 2007):

Where RIt+1 is the residual income for the first the year after the horizon. In case it is forecasted that the company will experience constant growth at horizon, the continuing value term can be modified to:

Where g is the growth rate and g should always be less that re . According to Penman (2007), there is often more weight on the continuing value compared to the value calculated up to horizon in the DDM and the DCF model. But in the RIM when the continuing value term is added, there is more emphasis on the value created up to horizon, which can be estimated with more certainty than the value at horizon. Penman (2007) argues that because of this feature the results from the RIM are more certain compared to the results obtained using the DDM and the DCF. Additionally, previous researches undertaken by various authors have compared the performance of the DDM, RIM and the DCF model and concluded that the RIM gives more accurate value estimates and explains more of the variation in stock prices (Xiaoquan and Bon-Soo, 2005). According to Rees (1997) it can be difficult to apply the RIM in practice because it contains expected abnormal earnings, which can be difficult to estimate. He states, that it is therefore important to use valid forecasts to predict reliable future abnormal earnings. Additionally, Rees (1997) claims that it might not be enough to look at book values and expected abnormal earnings to calculate firm value in practice, additional factors such as financial management of the firm, dividend payouts, debt levels and capital expenditure should also be considered.

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To prove his statements, Rees (1997) performs a statistical analysis on a number of public limited UK companies, excluding financial companies, property companies and investment trusts. He tests whether dividends, amount of debt and capital investments have an impact on firm value. His analysis shows that earnings paid out as dividends have a higher impact on firm value than retained earnings, and that capital investments have a positive impact on firm value in contrast to debt which has a negative impact. Ohlson (2001) states that all other factors that can affect company value should also be investigated in addition to the value calculated using the RIM. Therefore the RIM is not sufficient on its own to capture the actual value of the company. 7.3.2 Evaluation of RIM Based on the analysis performed in this section, it can be seen that the RIM is a relatively new model compared to the other popular valuation models such as the DDM and the DCF model. One of the important features that distinguish the RIM from the other valuation models is the fact that it is based on accounting numbers. Whether the use of accounting numbers is an advantage or a disadvantage is widely discussed in the literature, and there is no final conclusion on the discussion because there are both pros and cons.

7.4 Real Options Valuation (ROV) An option is the right, but not the obligation to buy or sell an underlying asset under the terms that are specified in the contract (Damodaran, 1994). Options can be exercised before the expiration date (American options), at the expiration date (European options), or not at all. Additionally, options are especially valuable in environments that are characterized by uncertainty, because they give the opportunity to make a decision after seeing how the events turned out. Originally options have been used in the financial theory, but have later been extended to cover non-financial assets; these are known as real options (Amram and Kulatilaka, 2000). A real option is the right, but not the obligation to take action at an agreed price within the options life (Copeland and Antikarov, 2003). In general real options are mainly used by managers to evaluate single investments or project decisions in a company (Koller et al., 2005). In order to value options, methods such as the Black-Sholes model and the binomial model can be applied (Damodaran, 2010 3). These two methods are discussed further in sections 7.4.2 and 7.4.3.

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Brovles (2003) claims that methods such as DCF are too simplistic to capture the actual value of the company and a better value estimation is achieved if the future options of the company are considered using a real options framework. Moreover, Damodaran (1994) states that even in cases where the traditional DCF method gives a sensible result; real options give another perspective on valuation which can be useful. According to Koller et al. (2005) the standard DCF method does not consider managerial flexibility, that is, the fact that managers react to changes in the economic environment and thereby adjust the companys plans and strategies. According to Damodaran (2002), real options include for example the options to expand, delay or abandon a project these are all examples of managerial flexibility which creates value. The DCF method often understates the firm value because it only considers future cash flows and not the firms future options to expand or invest and thereby achieve unexpected success. These options can be accounted for when using the real options frame work (Damodaran, 2001). The analysis conducted by Andrs-Alonso et al. (2006) shows that the total market value of a firm consists of two parts, these are: the value of the firms existing assets and the value of the firms real options. In order to apply the real options method to company valuation, it is therefore necessary to first determine the value of the underlying asset using another method such as DCF, if the assets price cannot be directly observed in the market, the actual method of applying ROV is discusses further in section 7.4.2. For this reason the ROV does not replace the traditional DCF method, but is a complementary method (Koller et al., 2005). 7.4.1 Advantages and disadvantages of real options Damodaran (2001), discusses some of the limitations of the real options pricing models, he mentions that the variance of the underlying asset might change over the life of the option which makes the option valuation more complicated. Furthermore, it might not be possible to exercises a real option instantly which affects the options value. According to Koller et al. (2005), the ROV depends on precise estimates of the value and variance of the underlying asset; otherwise it will lead to incorrect estimates of the flexibility value. There are therefore some issues with the application of real options theory in practice. According to Damodaran (2005), another danger is the fact that the required inputs of the ROV can be manipulated which makes the resulting value biased. According to Kemna (1993), when applying ROV to real life cases it is beneficial to limit the number of options to the most important ones, because having too many options makes the model

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more difficult and confusing and is not necessarily adding more value. Furthermore, when there is some sort of political uncertainty in the macroeconomic environment the relevance of ROV increases because more companies choose to postpone their investments in order to wait and see what happens (Copeland and Antikarov, 2003). 7.4.2 The binomial model The binomial option pricing model, which is a discrete model for valuing European and American options, was created by Cox, Ross, and Rubinstein in 1979. This model, separates the time to maturity of an option into discrete intervals, whereby during each interval, the price of an asset for example a stock follows a binomial process moving from its original value, S, either to Su (with probability p) or to Sd (with probability 1-p). Afterwards the value of the option can be determined by working backwards from maturity (Cox et al., 1979). According to Koller et al. (2005), real options valuation can be done in four steps as illustrated in figure 7.1. Figure 7.1 The four step process to estimate value of real options

1.Estimate NPV of the underlying asset without flexibility

2.Model uncertainty in an event tree

3.Model flexibility in a decision tree

4.Estimate the NPV with flexibility

Source: Adapted from Koller et al. (2005, p. 560)

Step 1: The value without flexibility In the first step of the real options valuation, the present value of the underlying asset without flexibility is determined (Koller et al., 2005). If the valued asset is a whole company, then the company is valued first using another method, e.g. DCF model, and this value is then used as the value of the underlying asset.

Step 2: Event tree According to Koller et al. (2005) it is necessary to model the different possible values of the underlying asset in an event tree in the second step. The values can either be modelled in a

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geometric event tree9 or an arithmetic event tree10. Koller et al. (2005) recommend using a geometric event tree rather than an arithmetic event tree due to the fact that a geometric event tree does not produce negative values. The up- and downward movements in the geometric event tree can be determined as (Koller et al., 2005):

Where: is the annualized volatility of the underlying asset, and T is the number of years per upward movement. According to Damodaran (2002), there are three different approaches to estimating annual volatility: 1) use the variance in cash flows from the companys earlier similar investments, 2) use simulation to estimate possible cash flows, find the present values, and then calculate the variance across the present values, or 3) use the variance in values of similar firms in the industry as a proxy. After the up- and downward movements are determined, the probabilities of these movements can be calculated as (Koller et al., 2005):

Where: r is the cost of capital of the underlying asset. According to Koller et al. (2005), the values in the event tree can be verified using the estimated probabilities pu and pd. The values can be calculated as:

Step 3: Decision tree

9

10

Geometric event tree: The asset value at time t+1 is determined by multiplying the asset value at time t with a factor Arithmetic tree: The asset value at time t+1 is determined by adding a value to the asset value at time t

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In order to model flexibility, decision points are added to the event tree from the second step and thereby a decision tree is obtained. The decision points are added by estimating a percentage increase in company value due to the expansion and the costs of expansion. If the value with expansion is higher than the value without expansion the company chooses to expand and this value is thus stated in the decision tree at a given time (Koller et al., 2005). Step 4: The value with flexibility The value of the real option is determined in the fourth step. One of the methods to determine the value is to use risk-neutral valuation. In this method the probabilities are adjusted to risk-neutral probabilities using the formulas (Koller et al., 2005):

Then by working from right to left the values estimated at each point in time in the decision tree can be discounted back at the risk-free rate. This way the total asset value including the value of the option is estimated. The binomial model is helpful in valuing American options, thereby providing the owner with an intermediate decision making tool at a given point in time until expiration. This model is mathematically simple compared to the Black and Scholes model (Cox et al. 1979). The major drawback of the binomial model is its quite slow process, especially when calculating many prices in a short period of time (Subramani, 2009) as well as the large number of required inputs, which are the expected future prices at each node (Damoradan, 2005). 7.4.3 The Black and Scholes model The Black-Scholes model from 1972 is not an alternative to the binomial model; rather, it is one limiting case of the binomial model (Damodaran, 1994). Both models have similar assumptions except that the Black-Scholes model only follows a continuous process, which does not allow for price jumps of the assets prices (Damodaran, 2005). The Black and Scholes model for valuing a call option can be stated as (Damodaran, 1994):

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Where

Additionally, S is the current value of the underlying asset, K is the strike price of the option, t is the time to expiration of the option, rf is the risk free rate for the life of the option, and variance in the ln(value) of the underlying asset. The above stated model was originally created for valuing European options, on securities that do not pay dividends. This means that this model does not consider an early exercise and dividend payments, both of which affect the value of options. Recognizing the limitations of the BlackScholes Model, the binomial model is considered to be more accurate because it includes several factors such as the possibility of early exercise and other factors like dividends (Cox et al. 1979). 7.4.4 Evaluation of real options Based on the literature review, it is found that real options is a useful tool to capture the value of managers flexibility, i.e. their future options, in relation to company valuation. In general, real options analysis is not an independent method, but rather an extension of the DCF model. The two popular models for option valuation, discussed in this section, are the Black-Scholes model and the binomial model. According to the recommendations from the literature, the binomial model is the preferred choice, when valuing real options. is the

7.5 Valuation using multiples Valuation using multiples is a broadly used supplementary method to the well-known discounted cash flow method, when it comes to company valuation (Benninga and Sarig, 1997), according to Yoo (2006), the popularity of this method is mainly caused by its simplicity. In general, multiples are the average price divided with a certain performance measure; therefore many different multiples can be calculated for a firm. The primary ratio which is generally used to estimate value is the price/earnings (P/E) ratio (Benninga and Sarig, 1997) and the two other ratios which are commonly used are the price/book value (P/B) ratio, and the price/sales (P/S) ratio (Damodaran, 1994). According to the analysis performed by Lie and Lie (2002), where they test the accuracy of ten different multiples through an empirical study of 8621 companies, the P/B ratio generates more

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exact and unbiased results than the other multiples including the P/E and P/S ratios. According to Koller et al. (2005) P/E ratio can generate imprecise results because it is systematically affected by the capital structure of the company, and, furthermore, the earnings used in the ratio are affected by non-operating revenues and expenses. For example deduction of a non-cash expense which is a non-operating item, results in lower earnings, but does not affect the firm value. The P/S ratio gives the least accurate results both according to Lie and Lie (2002) and Dragos (2009). In contrast, Liu et al. (2002) state that the P/E ratio performs best based on their empirical analysis. Cheng and McNamara (2000) analyse the performance of P/E and P/B ratios in relation to valuation based on 30,310 observations of company data over 20 years and conclude that a combination of these two ratios gives the most exact results, however if one ratio has to be chosen then the P/E ratio is found to be superior to the P/B ratio. Besides the abovementioned multiples that focus on the price, i.e. the equity, there are also those, that focus on enterprise value. A commonly used enterprise value multiple is the enterprise-valueto-EBITDA (EV/EBITDA), where EBITDA stands for earnings before interest, taxes, depreciation and amortization (Koller et al., 2005). Increasing P/E is often associated with company growth by investors, however, Koller et al. (2005) argue that it is more correct to draw conclusions about a companys growth based on increases in the EV/EBITDA multiple because it also considers the return on invested capital (ROIC). And according to Koller et al. (2005), it is only possible to conclude that a company is growing, based on increase in a multiple, when the companys ROIC is higher than the cost of capital. Additionally, Koller et al. (2005) recommend using the EV/EBITDA multiple because it is independent of capital structure, and can thus be easily applied to comparable companies that have different capital structure. Koller et al. (2005) also discuss the sales multiple and state that this multiple can be used when the valued company has small or negative profits, however they recommend using the EV/S ratio instead of the P/S. Benninga and Sarig (1997) state that valuation using multiples often requires several average ratios in order to be applicable in practice. According to Yoo (2006), if the multiples are calculated based on historical numbers, then it is advise