Diploma Thesis, 2007
77 Pages, Grade: 1
2 Relative Valuation
2.1 Traditional Approach
2.1.1 Common Multiples and their Drawbacks
2.1.2 The Accuracy of Multiples and Best Practices
2.2 Modifications and Extensions
2.2.1 Multiples Based on Non-financial Data
2.2.2 Growth-adjusted Multiples
2.2.3 Knowledge-related Multiples
3 DCF Valuation
3.1 General Framework
3.2 Modifications for High Growth Companies
3.2.1 Scenario-based DCF
3.2.2 Estimating Cash Flows
3.2.3 Estimating Growth
3.2.4 Estimating the Discount Rate
4 Other Methods
4.1 Real Options
4.2 Venture Capital Method
5 Case Study: Valuing bwin
5.1 The Problem
5.2 Market Review and Key Value Drivers
5.3 Relative Valuation
5.4 DCF Valuation
List of Abbreviations
List of Literature
Everyone still remembers the internet bubble at the end of the 1990ies. There the question arose, how to value new economy firms, or better, how to legitimate the billion dollar stock market valuations of companies with no track record and huge negative earnings. New more or less reasonable multiples were created, the traditional discounted cash flow approach was often viewed as not suitable, or it was modified to cope with the “new” kind of companies. After the burst of the bubble traditional, moderately growing companies were taken back into the portfolios and everything comprising “dot com” or new technologies was avoided by serious investors.
Now, six years later the picture has brightened again and companies like Google delight investors with more than 500% performance since its IPO in August 2004. Despite Google’s revenues of USD 6.14 billion in 2005, its actual market capitalisation of USD 152.7 billion shows that the demand for modified valuation techniques is still there. A recent development of the hype was the USD 1.65 billion acquisition of YouTube on 13. November 2006, a video entertainment site which was founded just in February 2005. So is it possible to create USD 1.65 billion value in less than 2 years with a simple website without any idea of making profit?
Google is not the only example, and the internet is not the only market where such companies can be found. In this paper I shortly discuss traditional valuation methods and their drawbacks for valuing such companies. Consequently I discuss possible modifications or amendments to these methods to value high growth companies, while some seem quite promising at first sight and some may turn out to be useless. In the case study, I try to apply some of the presented amendments to value a company in the online gaming industry.
Definition of high growth companies
First there is the question how to define high growth companies which are emphasised in this paper. Koller et al. (2005) define them as companies whose organic growth – through new products, new technologies and a rapidly growing end-product market – exceeds 15% annually.
Damodaran (2001) also handles the problem talking about “technology firms”. He further differentiates between two groups: the first group with companies that deliver “technology-based or technology-oriented products” like hardware and software, for example Cisco and Oracle, and also high growth telecommunications firms. The second group consists of companies using technology to deliver products or services that have been delivered by more conventional means some years ago. The prime example in the “consumer serving” segment is amazon.com, the famous online retailer. Examining the life cycle of a firm, the associated availability of information and the source of value (see Figure 1), in the focus of this paper are mainly firms in the second (“rapid expansion”) and third stage (“high growth”). Some of the presented valuation techniques may also be applied to value “start-up or idea companies” in the sense of Figure 1, but in many cases valuing these early stage companies will be more a guess than science, regardless of the diligence used for estimating the inputs.
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Figure 1: Valuation Issues across the Life Cycle
Schwarz and Moon (1999) handle the subject exclusively for “Internet Companies”, while aiming at the same problem. For this paper the definition of Koller et al. most accurately describes the focus of companies – without limitation to specific industries – for which valuation techniques are discussed. In principle this paper tries to handle the valuation of firms that invest their cash flow into growing their business instead of posting profits and paying dividends. Very often such firms post huge negative earnings in their financial statements. The reason for this may not be the managers’ intention to burn the cash of shareholders. Frequently the key asset is the customer itself (as in customer-driven internet companies) and acquired customers can not be capitalized on the balance sheet. Therefore stock prices increasing with simultaneously rising losses could be observed during the internet bubble, as large investments were expensed through the income statement as marketing expenses.
Overview of valuation methods
Valuation methods generally may be divided into three basic approaches which can be found in practice:
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Figure 2: Overview of Valuation Methods
The cost approach, also called “net asset approach”, does only make sense for valuing companies with strong investments into tangible assets or companies where income from operations is insignificant in relation to the underlying assets. Also in these cases its usefulness for going-concern company valuation seems limited; it is therefore not discussed in this paper. The market approach aims at the analysis of the price – both on the stock market and on the market for corporate control – of comparable companies to derive a theoretical value for a specific company. This very common method is covered in chapter 2 as “relative valuation”. The income approach stands for the valuation of companies based on the income they produce, and will be discussed on the basis of discounted cash flow valuation, the most comprehensive valuation method, in chapter 3.
In a DCF valuation the objective is to derive the value of assets based on their cash flow pattern and their growth and risk characteristics. In a multiples valuation, on the other hand, the objective is to derive the value of assets using current market prices of similar assets. The comparable company analysis using multiples is widespread in the practice of business valuation. Analysing the operating and equity market valuation characteristics of companies which are comparable by their operating, financial and ownership profiles can deliver essential information about the company to value and its industry. And most important, it is possible to use valuation multiples of comparable companies to derive a theoretical value for a business which should be valued.
Although this application is useful, a profound company valuation should not be based solely on multiples. For valuing companies, the theoretically correct approach is to forecast future cash flows and discount these cash flows at an appropriate risk-adjusted discount rate. Although also more positive opinions about multiples can be found in literature, the problems in finding perfectly comparable companies and the “basis of substitutability” seem to support DCF analysis as the more accurate method. Also Koller et al. mention that a DCF analysis is still the most accurate and flexible method for valuing projects, divisions and companies; a multiples analysis can however be helpful for making forecasts for a DCF valuation. It can be used to test cash flow forecasts and key input parameters for plausibility, or to derive facts about the strategic position and the competitive situation of a firm. By examining reasons why a company’s multiples are higher or lower than those of competitors, insights about key factors that create value in an industry can be obtained. In practice, multiples analysis is often used to derive a possible value range instead of a definite value. Although multiples are regularly used reasonably, they are also often misapplied. It is for example common among financial analysts to calculate an industry average price-to-earnings ratio and multiply this ratio with a company’s earnings to derive a “fair” share price (as described in footnote 12). This proceeding does not take into account that the firms in this average calculation can have substantially different growth expectations, profitability figures and capital structures, although they are in the same industry. Actually, the ease of their application makes multiples often erroneous. A well-done multiples analysis will need many of the same adjustments (and efforts) as a DCF analysis. In the following, the most common multiples are shortly discussed, including their implicit assumptions and drawbacks, and followed by a review of empirical findings and derived best practices for the sound application of traditional multiples.
The price-to-earnings (P/E) ratio is the most common but also the most misused multiple. It is defined as the firm’s share price divided by earnings per share, or equivalently, its market capitalisation divided by earnings. This “equity multiple” is consistently, as a firms earnings are the fraction of income (after deducting e.g. interest expense and taxes) which is attributable to equity holders. Though it is consistent in this respect, it is influenced by a firm’s capital structure, what places a big constraint on its applicability by restricting the number of comparable firms to firms with similar capital structure. In addition, earnings mix a firm’s operating and non-operating performance.
Despite its deficiencies, the P/E ratio can serve as a valuable tool for valuation if it is fully understood and applied reasonably. Thus it is important to note that the determinants of the P/E ratio are the same as in a DCF valuation, namely the firm’s cash flow pattern and its growth and risk characteristics. Examining the simplest discounted cash flow model for equity value, a stable growth dividend discount model, the value of equity can be expressed as follows:
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DPS1 denotes the expected dividend in the next year, ke the cost of equity and gn the expected stable growth rate. Dividing both sides of the equation by earnings yields the discounted cash flow equation for the P/E ratio for a stable growth firm:
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This model could also be extended to a two-stage dividend discount model to account for a period of higher growth.
Nevertheless the capabilities of the model end simply when a firm’s earnings are negative or very small. The main reason for “non-meaningful” earnings at high growth companies was already outlined in the introduction: investments in R&D or in the growth of the customer base often represent the largest part of a high growth firm’s investments, however, due to accounting principles these investments are treated as operating expenses and lower the firm’s earnings and thus the informational value of earnings for valuation purposes.
Enterprise value-to-operating income multiples
Enterprise value (the value of equity and debt minus cash) divided by a measure for operating income (e.g. EBIT, EBITDA or EBITA) yields another consistently defined type of multiple. It avoids some of the shortfalls of the P/E ratio; disregarding taxes and distress costs, this multiple is unaffected by leverage. In practice, the company’s WACC also drives its value, and the WACC contains these two elements. Therefore, in theory, the value of tax shields and distress costs would have to be removed from enterprise value. However, the complexity of removing them outweighs the potential errors they cause if they are ignored. The choice of the company’s measure for operating income depends on several factors like the industry of the firm. It is a sensible question if depreciation should be included in the multiples. Koller et al. show an example of two almost identical firms, which differ only in their production policy. One firm manufactures its products using its own equipment whereas another firm outsources manufacturing to another company. Consequently, the first firm reports a much higher EBITDA than the second firm, as it records the “cost” of manufacturing via the depreciation. However, the EBITA is equal at both firms. As a result, the first firm will look cheaper than the second if only the EV/EBITDA multiple is considered. Although this example seems plausible at first glance, these two firms would not necessarily be identified as comparable in the opinion of the author, as the first one is a manufacturer and the second one is actually a trading firm (if the product is a commodity). An EBITDA multiple can therefore definitely make sense if the peer group is chosen accurately.
Like shown for the P/E ratio, this multiple can also be decomposed to show its key determinants of value. Koller et al. use a cash flow-based constant growth formula for enterprise value, where they replace NOPLAT by EBITA * (1 - t). Dividing both sides of the equation by EBITA then yields an algebraic representation of the EV/EBITA multiple:
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According to this formula, four variables drive this multiple – the company’s growth rate (in this case of EBITA), return on invested capital, the cash tax rate and cost of capital. While the latter two may be quite similar for companies in the same industry within the same regions, ROIC and growth can vary substantially, even within an industry. This explains about the fact that multiples of companies within an industry can be widely dispersed for sound reasons.
Although enterprise value multiples avoid or alleviate some of the drawbacks of the P/E ratio, namely the influence of capital structure or accounting choices on a firm’s earnings, the value drivers are again lowered by operating expenses which represent investments. One might argue that this effect cancels out if the whole peer group has these “lowered” earnings. This is not true, as some firms will invest lower amounts and thus experience relatively lower growth, and some firms will invest higher amounts and thus might look overpriced compared to the first kind of firms. Therefore, when using earnings multiples to value high growth companies, modifications may be helpful.
Enterprise value-to-sales multiples
The before mentioned multiples based on operating income require a similar growth rate and ROIC among comparable firms. This multiple (enterprise value divided by sales) additionally requires a similar operating margin for the existing business. Generally, this multiple is not very helpful for explaining company valuations. Nevertheless it could be used in situations where the relevant companies have a very small or negative operating income, wherefore the EV/Sales multiple is very common in the venture capital industry. Also in this scope of application it has to be used carefully, as it is mostly not possible to control for differences in costs and profit margins across firms. This can result in assigning misleading values to firms with negative operating income. Empirical work confirms these weaknesses, as multiples based on sales mostly perform worst. A possible advantage of this multiple is that sales are generally far less affected by different accounting choices or even accounting systems than earnings or book value figures. This may facilitate the comparison of firms across markets with different accounting systems.
Book value multiples
Another popular multiple is the price-to-book value (P/BV) multiple, which relates the actual market value of equity to the book value of equity. As book values depend on originally paid prices for assets, depreciation and accounting principles, book value multiples should also be used with care while keeping these effects in mind. It is though relatively often used to value banks, firms in the paper and pulp industry and real estate companies.
Intuitively, this multiple may be appropriate for banks, where book values of the largest positions (e.g. loans and deposits, market valued financial instruments) relate quite well to their fair values, and industries which derive a large part of their value from tangible assets (e.g. machinery of a paper mill) and where the book value is also a good approximation of the fair value of these tangible assets. In contrast, book value multiples are definitely not useful for high growth companies which mostly derive the largest part of their value from future cash flows, respectively intangible assets which are not captured in book values.
Baker and Ruback (1999) analyse industry multiples of the S&P 500 in 1995 with the objective of finding the optimal “basis for substitutability” (a value driver like EBITDA) and the best measurement of industry multiples. They find the best value driver (the financial performance measure with the lowest standard deviation around the harmonic mean) being EBITDA for 10 of 22 industries in the S&P 500. EBIT performs best for 9 of the 22 examined industries, while revenue multiples perform worst in estimating the companies’ values. They argue that the basis of substitutability yielding the most precise estimate of value varies by industry, as the underlying value drivers vary across industries. In few industries (e.g. chemicals) even revenue seems to be proportional to value.
Liu et al. (2002) examine the valuation performance of multiples based on commonly used value drivers (forward or historical earnings, cash flow and book value measures, sales) and find forward earnings per share (in particular two year consensus earnings forecasts) performing best across industries, followed by historical earnings measures, cash flow measures (e.g. EBITDA), book value of equity measures, and last again, sales. They add that results may not be descriptive because of excluded data, at least for start-up firms reporting losses and high growth firms with negative operating cash flows. The fact that forward earnings perform best is consistent with Kim and Ritter (1999), who also find forward P/E ratios performing better than other multiples and better than “trailing” P/E ratios (which are based on the most recent financial data from quarterly figures, aggregated to twelve months).
In a recent paper, Schreiner and Spremann (2007) examine the accuracy of different market multiples in European equity markets and find that multiples generally approximate market values reasonably well. They empirically test and approve three hypotheses. First they find that, using their model, for the underlying sample equity value multiples outperform enterprise value multiples in accuracy. They explain this fact (which is not consistent with conventional wisdom) with potential uncertainties concerning the approximation of the value of net debt for enterprise value with book values of debt. Second they find that knowledge-related multiples outperform traditional multiples in science-based industries. Knowledge-related means, they add back R&D expenditures or amortisation of capitalised intangible assets or both (as “knowledge costs”) to EBIT or net income. This should yield earnings figures with higher quality for corporate valuation. Third, their evidence indicates that multiples based on forward looking value drivers (especially two-year consensus forecasts for earnings per share) outperform their equivalents based on historical financial data. This is consistent with prior empirical evidence from U.S. markets (notably Kim and Ritter (1999) and Liu et al. (2002)) and with the principles of valuation, as the value of a firm is determined by the discounted stream of expected future payoffs. Another interesting fact is that in contrast to Liu et al. (2002), the median delivered superior results compared to the harmonic mean in defining the synthetic peer group multiple.
Best Practices for using multiples
All in all, the cited empirical results deliver valuable aspects for the application of (traditional) multiples analysis, which mostly confirm the “best practices” for using multiples defined by Koller et al.; these will be shortly outlined and critically reviewed in the following, including implications for high growth companies. In certain aspects, the presented empirical work also allows to amend or adapt these best practices:
Choose comparables with similar prospects
The creation of a comprehensive peer group is the first step in a multiples analysis. In practice, this step may be the most important one. As in the mentioned empirical studies about the accuracy of multiples only mechanically selected peers were used, there is even room for improvements of results, by a thorough “manual” selection of suitable peers. Analysts usually begin by examining a company’s industry (e.g. by using an industry classification system like the GICS developed by S&P and Morgan Stanley) to find comparable firms. This should be followed by a closer analysis of the firms characteristics, dependent on which multiples are used. When a list of comparables is established and multiples are computed, profitability and growth characteristics of the firms have to be viewed in context with their relatively higher or lower multiples. If a representative multiple should be generated (e.g. to value minority interests or a company before an IPO), the median multiple of the comprehensive peer group should be used, as the harmonic mean also recommended by Koller et al. might not systematically deliver more accurate multiples.
In the case of peer groups containing comparable companies with negative earnings (which may be the case especially for high growth firms), Koller et al. note that excluding them would positively bias the industry multiple. In this context it may be useful to switch to a value driver with a positive value across peers (e.g. sales are always positive). This proceeding requires additional care, as the number of determinants for comparability increases when moving up in the income statement. Furthermore, Schreiner and Spremann found multiples based on value drivers closer to the bottom line of the income statement performing better, which advises for instance that mechanically chosen peers (as used in the literature cited above) should not be used for an analysis based on value drivers like sales.
For valuing high growth companies with negative earnings it may often be the case that accurate multiples for the chosen peer group cannot be established with traditional approaches, simply as the observed value of such firms often does not (or even negatively) correlate with the value drivers used for traditional multiples. In these cases modified multiples or a DCF analysis represent more adequate valuation techniques.
Use multiples based on forward looking estimates
Following the examined empirical work and the principles of valuation (value corresponds to future cash flows), multiples should be based on forecasts for their specific value drivers (if available), not on historical data from published financial statements.
This recommendation is definitely reasonable for large, mature firms which are covered by many analysts. For some high growth companies (this applies also to small caps or firms in emerging markets), however, there may be few forecasts available. Combined with a smaller set of comparables (or even no comparable firm), a “forward-looking” multiples analysis may then be dependant on sparse information, and its informational value should be questioned. In addition, forecasts are much more volatile for rapidly changing high growth firms than for mature firms, which enlarges the possibility of valuation errors. If a diligently conducted DCF analysis with profit forecasts already exists for a high growth company, using these forecasts for a multiple analysis may not increase the accurateness of a valuation, as multiples based on these forecasts would only reiterate the results of the DCF analysis. Multiples based on forward-looking estimates thus might work well also for high growth firms, as long as there are enough forecasts of good quality which can be used. Whether forecasts are regarded as reliable or not should be decided individually for each case.
Use enterprise value multiples
Beside the drawback that consistent equity multiples like the P/E ratio are more affected by leverage than consistent enterprise value multiples (see subsection 2.1.1), they also contain non-operating gains and losses. A non-cash write-off thus may significantly affect net earnings and increase the P/E ratio, without a comparable effect on value. In addition, taxes also affect the P/E ratio, what is problematic when firms have different corporate tax environments.
With respect to these theoretical facts, a multiple like EV/EBITA would obviously be preferred to the P/E ratio. Above mentioned empirical evidence however indicates that equity value multiples explain stock prices better than enterprise value multiples. Nevertheless, multiples should not be defined inconsistently (e.g. price-to-EBIT) in the opinion of the author, as there is no theoretical foundation which supports such multiples. Analysing only consistent equity value multiples, where underlying earnings are subject of several accounting choices, taxes and capital structure, may not satisfy the needs of comprehensive company valuations; thus the use of both types of multiples (equity and enterprise value) may be the best choice, whereas attention can be shifted to these multiples which feature the least dispersion. Considering high growth companies, enterprise value multiples still should dominate, simply because the value drivers for equity value multiples are more often negative than for example EBITDA. As enterprise value multiples do not solve the problem of high growth firms expensing investments over the income statement, again the application of modified multiples (see subsection 2.2) should be considered.
Adjust multiples for non-operating items
Also enterprise value multiples like EV/EBITA should be adjusted for non-operating items. These include excess cash, as the value drivers used exclude the interest income from excess cash. EBITA also includes implicit interest expense from operating leases, whereas the value of the lease-based debt is ignored in EV. Further adjustments are required for employee stock options, if they are not expensed, pension liabilities, and all other non-operating items. In fact, similar adjustments as for a DCF analysis (see subsection 3.2.2) should be made, to create a sound basis for comparing operating performance.
For high growth companies, such adjustments may be sensible e.g. for stock options, when they are extensively used for managers’ compensation. In addition, extraordinary write-offs can reach huge dimensions, for instance if overpaid acquisitions have to be written off. The use of a value driver before amortisation and / or depreciation would automatically exclude such items; in other cases, adjustments are necessary. Other non-operating items may have a lower impact on the value of high growth firms (e.g. young technology firms usually do not own large non-operating land or buildings).
 Calculated with 219.193,569 class A common shares and 85.167,040 class B common shares (given in the Q-10 SEC filings of 31. July 2006) and a closing price of USD 505.00 on NASDAQ on 24. November 2006.
 http://investor.google.com/releases/20061114.html [24.11.2006]
 Koller et al. (2005), p. 655.
 Damodaran (2001), p. 1 – 18.
 Damodaran (2001), p. 13.
 Although the mentioned 15% organic growth seem almost too conservative, as the seemingly irrational values go along with much higher growth rates.
 Koller et al. (2005), p. 656.
 A different classification is done for instance by Damodaran (1994), p. 9. He differentiates between DCF valuation, relative valuation and “contingent claim valuation” (using option pricing models) instead of the “cost approach”.
 Source: CBIZ Valuation Group Inc., presentation for “5th Annual Early Stage Venture Investing Conference”, October 2004; compare also Friedlob and Schleifer (2002), p. 210.
 Friedlob and Schleifer (2002), p. 210.
 Damodaran (2001), p. 251.
 E.g. if the business to value has earnings of EUR 10 million and a comparable listed company has a price-to-earnings ratio of 15, the value of equity of the company to value would be EUR 150 million (EUR 10 million times 15), when using this multiple.
 Bajaj et al. (2004), p. 1.
 Baker and Ruback (1999), p. 1, argue, “if a truly comparable publicly traded firm or transaction were available, if the basis of substitutability could be determined, and if the multiple could be estimated reliably, then the method of multiples would be clearly superior to discounted cash flow analysis”.
 Koller et al. (2005), p. 371.
 For example in the field of mergers & acquisitions, an analysis of trading multiples and transaction multiples accompanies most business valuations, while the main valuation method is a DCF analysis (respectively a Leveraged Buyout analysis, if a financial investor is involved).
 Koller et al. (2005), p. 371f.
 Damodaran (2001), p. 275f. The Wall Street Journal Europe, November 2 – 4, 2007, p. 16: “These are probably the most used indicator of corporate performance” – according to this article, the IASB and the FASB actually want to ban the use of P/E ratios as earnings can be misleading indicators.
 Actually the P/E ratio could be “unlevered”, what requires additional calculation steps. The use of enterprise value-to-operating income multiples counters the problem without additional effort.
 Koller et al. (2005), p. 379.
 Damodaran (2001), p. 262 – 264.
 Damodaran (2001), p. 282 – 285.
 Operating earnings are available to the firm and thus to debt holders and equity holders, therefore using enterprise value in the numerator is consistent.
 Koller et al. (2005), p. 380f.
 In the airline industry for example, analysts often use the EBITDAR for creating multiples, as it excludes rental expenses for planes and thus allows the comparison of the operating performance of airlines which buy their planes and airlines which lease them.
 Koller et al. (2005), p. 383f.
 Koller et al. (2005), p. 373f.
 Koller et al. (2005), p. 374.
 Koller et al. (2005), p. 385.
 Damodaran (2001), p. 320.
 For instance in Liu et al. (2002) or Schreiner and Spremann (2007); for details see subsection 2.1.2.
 Damodaran (2001), p. 254f.
 Damodaran (2001), p. 254.
 Fernández (2002), p. 5; compare e.g. Deloitte Valuation Services (2007), p. 324.
 Baker and Ruback (1999), p. 19.
 They exclude firms not covered by I/B/E/S (typically small and mid caps) and firm-years with negative values for any value driver.
 Liu et al. (2002), p. 4.
 Liu et al. (2002), p. 5f; Kim and Ritter (1999), p. 1f.
 Schreiner and Spremann (2007), p. 5; they employ a four-step “multiple valuation method“: selection of the kind of value of interest (e.g. equity value) and the value driver (e.g. net income), selection of the peer group, aggregation of peer group multiples in one single number (e.g. by taking the median), and finally, estimation of the target firm’s value with this synthetic peer group multiple.
 Generally, enterprise value multiples are less affected by leverage than equity value multiples and should perform better.
 Schreiner and Spremann (2007), p. 6f.
 These proposed modified multiples are discussed separately in subsection 2.2.3.
 Schreiner and Spremann (2007), p. 7 – 9.
 Koller et al. (2005), p. 376 – 378.
 Koller et al. (2005), p. 376f.
 In the opinion of the author; as mentioned earlier in this subsection, the median delivered better results than alternatives (simple mean, harmonic mean, etc.) in the most recent cited study – Schreiner and Spremann (2007), p. 11.
 Koller et al. (2005), p. 378.
 Schreiner and Spremann (2007), p. 14.
 Koller et al. (2005), p. 378f; Schreiner and Spremann (2007), p. 9.
 Koller et al. (2005), p. 379.
 Schreiner and Spremann (2007), p. 14; in their study the P/PBT multiple outperformed the P/E ratio, as the comparability of net income across firms in different countries is limited.
 An important constraint of the empirical evidence is that it is limited to trading multiples. An evaluation of the accuracy of multiples in comparable transactions analysis may deliver different results (e.g. in favour of enterprise value multiples).
 Koller et al. (2005), p. 381 – 384.
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