1 Rethinking the Comparable Companies Valuation Method 1 Abstract: This paper studies a commonly used method of valuing companies, the comparable companies method, also known as the method of multiples. We use an intuitive graphical presentation to show why the comparable companies method is arbitrary and imprecise. We then show how valuations can be significantly improved using regression analysis. Regression analysis is superior to the comparable companies method because, by using more of the available data and imposing fewer unreasonable assumptions, it is more accurate and can value more firms. I. Introduction The valuation of privately-held firms is a substantial and challenging problem. One method of valuation often used in practice is called the comparable companies method, also known as the method of multiples. In this method, the value of a firm is estimated using a handful of comparable companies. Some measure of a value-toearnings ratio is calculated for each of the comparable companies. To estimate the firm s value, one simply multiplies the average of the ratio of the comparable firms by the firm s own earnings. The comparable companies method of valuation is used in many different contexts. In mergers and acquisitions, analysts on both sides of the transaction often estimate the value of the target company using this method. It is also used in a variety of litigation contexts. 2 For instance, dissident shareholders may take legal action to dispute the price proposed for their shares in a merger. Another example occurs when settling disputes over economic damages and lost profits. The comparable companies method can be used to estimate the value of the plaintiff s firm but-for an alleged bad act Securities Litigation and Consulting Group, Inc., 3998 Fair Ridge Drive, Suite 250, Fairfax, VA The primary authors are Paul Godek, Craig McCann, Dan Simundza and Carmen Taveras. Dr. Godek can be reached at or Dr. McCann can be reached at or Dr. Simundza can be reached at or and Dr. Taveras can be reached at or 2 See Weil, Wagner, and Frank (2001) for a more complete discussion. Securities Litigation and Consulting Group, Inc
2 The comparable companies method is also used when there is a taxable transaction involving a business. For instance, a business owner might give a family member shares in a private company as a gift or as an inheritance, and the value of the business must be estimated to calculate the beneficiary s gift or estate tax burden. Lastly, in the context of marital dissolutions, any family businesses must be accurately valued in order to reach a fair settlement. In this paper, using real-world data and simple graphs, we examine the arbitrariness and imprecision of the CCV method and suggest a demonstrably superior alternative based on regression analysis. Using a simple empirical test we measure the accuracy of these two valuation methods. We show that the method based on regression analysis is superior to the comparable companies method because, by using more of the available data and imposing fewer unreasonable assumptions, it is more accurate and can value more firms. We value 250 public companies using these two methods and find that regression analysis generates more accurate predictions for approximately 85% of the firms. Moreover, we show that regression analysis can accurately value firms which the comparable companies method cannot. Our main criticisms of the comparable companies method can be conveyed through a simple example. Presented with Figure 1, any student in a first-year, undergraduate statistics course should be able to estimate the relationship between the Y- variable plotted on the vertical axis and the X-variable plotted on the horizontal axis. That same student is likely to plot a linear relationship using Ordinary Least Squares that looks like the solid line in Figure 1 and warn you that, although this is the best she can do given the data, you should not place much credence in the relationship because you only gave her six observations. Now, if you instructed her to ignore the observation with the negative X-value and to assume the relationship between Y and X has to be strictly proportional, a good student would protest mightily that you now have only five observations and that Y is clearly not proportional to X and so the resulting relationship represented by the dashed line is nearly meaningless. In what follows, we explain that what our first year statistics student knows is worthless passes for analysis under the comparable companies approach to valuing companies. 2 Rethinking Comparable Companies Method, First Draft.
3 Figure 1: Too Few Observations, Not Enough Freedom Y X II. Review of the Practitioner-Oriented Comparable Companies Valuation Literature The group of comparable companies typically consists of a handful of firms from the same industry as the firm being valued. The market values of these peer group firms are known either because they are publicly traded companies or were recently valued in a market transaction. The observed market value of the peer group firms used in the numerator of the ratios can be measured by the market value of their common stock outstanding (equity value) or by the market value of all their outstanding securities including debt (enterprise value). The denominator in ratios using equity value is commonly net income or free cash flow. In ratios using enterprise value, revenue, earnings before interest and taxes (EBIT) or earnings before interest, taxes, depreciation and amortization (EBITDA) are common. The comparable companies method implies that equity or enterprise value is a simple multiple of the measure of earnings, revenues or assets used. Table 1 lists some valuation multiples commonly referenced in the practitioner-oriented literature. 3 3 Sources checked include: Stowe et al (2002), pp ; Ibbotson Associates (2004), pp ; Cornell (1993), pp.56-98; Koller, Goedhart, and Wessels (2010), pp ; CFA Program Curriculum (2009), Volume 3 pp ; Damodaran (2006), pp Securities Litigation and Consulting Group, Inc
4 Table 1: Commonly Used Multiples Equity Value Net Income Equity Value Free Cash Flow Equity Value Book Value of Assets Enterprise Value Revenue Enterprise Value EBIT Enterprise Value EBITDA Equity multiples can be misleading if there is considerable variation in the amount of financial leverage across the peer group firms and between the peer group firms and the firm being valued, as they lead to different valuations for otherwise similar firms. 4 Enterprise value multiples are preferable to equity value multiples if there is substantial variation in financial leverage across the peer group firms and the firm being valued. If the enterprise value is being estimated, the scaling variable should be a cash flow available to both equity and debt EBIT or EBITDA. After the decision is made to use one or more of the multiples listed in Table 1 and the requisite data is collected, either some of the comparable firms or the target itself may have a negative or zero-value for the variable in the denominator. For example, the analyst may decide to value a firm based on enterprise value to EBITDA and equity to net income ratios for eight publicly traded firms but learn that two of the eight comparable firms have negative EBITDA and the subject firm has negative net income. The practitioner literature suggests dropping the two comparable companies with negative EBITDA values and abandoning the equity to net income multiple. 5 The standard comparable companies approach thus severely limits the data and methods available to an analyst resulting in unnecessarily imprecise and inaccurate estimates of value. 4 For examples, see Koller, Goedhart, and Wessels (2010), p. 307, and Bader (2002), pp These issues are related to the original insights of Modigliani and Miller that the value of a firm should, as a first approximation, be independent of its capital structure. See Modigliani and Miller (1958), pp , and Miller (1977), pp For examples see Koller, Goedhart, and Wessels (2010), p. 312, Exhibit 14.6, and Damodaran (2006), p Rethinking Comparable Companies Method, First Draft.
5 III. An Example We present as an example a valuation which took place in a recent merger. On October 21, 2009, Equinix Inc. announced its intent to acquire Switch and Data Facilities Company, Inc. Both companies were involved in the internet exchange services industry. The companies filed a joint proxy statement on November 25, 2009 advising stock holders to vote for the merger. As is common in such proxy statements, the firms financial advisors issued a fairness opinion, in which they found the proposed deal to be fair, from a financial point of view, to the stockholders. 6 The valuation analysis supporting the fairness opinion is included in the proxy statement. 7 Raymond James acted as a financial advisor for the target. In determining the fairness of the transaction, Raymond James estimated the value of Switch and Data using a variety of methods, one of which was the comparable companies approach. In this analysis, Raymond James used four publicly traded companies. All were data center collocation and interconnection providers. Equinix, the acquirer, was used as one of the comparable companies. Raymond James calculated enterprise value to revenues and adjusted EBITDA multiples for the four comparable companies over three time frames: the most recent twelve months for which data were available, and the 2009 and 2010 calendar years (both estimated). 8 Table 2, copied from the proxy statement, provides information about the ratios Raymond James calculated for the comparable companies. Table 2: Summary Statistics for Multiples Used In a Merger Enterprise Value / Revenues Enterprise Value / Adjusted EBITDA Trailing 12 Trailing E 2010E 2009E 2010E Months Months Mean Median Minimum Maximum Merger Consideration See Cain and Dennis (2011) for a thorough discussion of the use of fairness opinions. 7 The SEC filing can be found at: 8 Adjusted EBITDA is earnings before interest, taxes, depreciation and amortization, plus stock-based compensation expense, extraordinary one-time expenses, and non-cash deferred rent expenses. Securities Litigation and Consulting Group, Inc
6 Enterprise Value (Millions) The first four rows list summary statistics. The last row, titled Merger Consideration, is included to help interpret these ratios in the context of the merger. The terms of the merger gave Switch and Data shareholders the choice between shares of Equinix common stock or $19.06 per share for each share of Switch and Data owned. The values in the last row are the multiples implied by the $19.06 value for shares of Switch and Data common stock. For instance, the value of 4.5 in the first column of the last row is found by first computing Switch and Data s enterprise value under the hypothesis that each share of common stock is worth $19.06, and then dividing by Switch and Data s actual revenue from the previous twelve months. The rest of the values in the last row are computed in a similar manner. We can also display the information contained in Table 2 graphically. 9 Figure 2 plots enterprise value against revenue over the trailing twelve months for the comparable companies (i.e. the data in the first column in Table 2). Figure 2: Enterprise Value and Revenue for the Comparable Companies $5,000 $4,500 $4,000 $3,500 $3,000 $2,500 $2,000 $1,500 $1,000 $500 $0 $0 $200 $400 $600 $800 $1,000 Revenue (Millions) 9 The proxy statement provides summary statistics of the ratios, but not the underlying data. We used Bloomberg to access the relevant data. Our multiples are slightly different than those reported in the proxy statement. 6 Rethinking Comparable Companies Method, First Draft.
7 Enterprise Value (Millions) To represent the ratio of enterprise value to revenue graphically, we draw a line from the origin (the 0,0 point on the graph) to each data point on the graph identified with an X. The slope of a straight line is simply its rise over run so the slope of the line connecting the origin and the company s data point is equal to the ratio of the firm s enterprise value to revenue. These lines have been added to the graph in Figure 3. Figure 3: Representing Multiples Graphically $5,000 $4,500 $4,000 $3,500 $3,000 $2,500 $2,000 $1,500 $1,000 $500 $0 $0 $200 $400 $600 $800 $1,000 Revenue (Millions) The steepest line corresponds to the maximum multiple from Table 1 (6.0), while the flattest line corresponds to the minimum (1.5). The dark solid line labeled Average represents the mean multiple of the four comparable companies. The graph shows that the comparable companies are actually quite disparate. This is one reason the CCV method generates inaccurate predictions. Using these multiples and estimates of revenue and adjusted EBITDA, Raymond James computed the implied estimates of the equity price per share of Switch and Data. These estimates are reported in Table 3. Securities Litigation and Consulting Group, Inc
8 Table 3: Estimates of Switch and Data s Value of Equity Enterprise Value / Revenue Enterprise Value / Adjusted EBITDA Trailing Trailing 2009E 2010E 2009E 2010E 12 Months 12 Months Mean $14.89 $15.29 $16.55 $15.43 $16.14 $16.88 Median $14.77 $14.90 $15.99 $17.57 $17.29 $17.40 Minimum $2.98 $4.06 $5.82 $6.57 $8.84 $11.35 Maximum $27.02 $27.33 $28.42 $20.00 $21.12 $21.39 Merger Consideration $19.06 $19.06 $19.06 $19.06 $19.06 $19.06 To compute the value in the first column of the row titled Mean, Switch and Data s revenue over the previous twelve months is multiplied by the mean multiple of 3.7, listed in Table 2, to get Switch and Data s estimated enterprise value of $725 million. 10 Subtracting debt, minority interest and preferred shares, and then adding cash, gives an estimate of Switch and Data s equity value. Dividing Switch and Data s equity value by the number of shares outstanding yields an estimate of the equity value per share of $ Figure 4 illustrates this application of the comparable companies approach. Switch and Data s estimated enterprise value is the point on the Average line directly above $195.8 million on the revenue axis. 11 The range of estimates generated by the comparable companies approach and reported in Table 3 is quite large and is reflected in the dispersion of the dotted lines in Figure 2. Using the lowest valuation ratio gives a per share equity value for Switch and Data of $2.98, while using the largest valuation ratio gives a per share value of $ Given the number of shares outstanding, this range of multiple alone could have justified a transaction price ranging from $100 to $935 million. To put this range into perspective, the range itself is greater than the actual transaction price ($670 million). 10 While information on Switch and Data s revenue over the twelve months prior to the merger is not publicly available, we estimate it at $195.8 million using data supplied in the proxy statement. 11 Since we do not have access to the data Raymond James used, our multiple is slightly different than the value of 3.7 reported in Table 2, and hence our estimated value is slightly lower. 8 Rethinking Comparable Companies Method, First Draft.
9 Enterprise Value (Millions) Figure 4: Estimated Enterprise Value $5,000 $4,500 $4,000 $3,500 $3,000 $2,500 $2,000 $1,500 $1,000 $500 $0 $0 $200 $400 $600 $800 $1,000 Revenue (Millions) IV. Methodology In this section, we describe a simple test of the accuracy of the comparable companies approach to valuation. We use Bloomberg to obtain financial data for 250 public firms in the three Standard Industry Classification (SIC) codes described in Table 4. We will value each of these firms, using other firms in the same industry as its comparables, and compare the accuracy of the different methods. Our analysis will use two multiples: Enterprise-Value-to-EBITDA, and Enterprise-Value-to-Revenue. Enterprise value is calculated as of December 31, EBITDA and Revenue are measured over the 2010 calendar year. Since fiscal years can vary by firm, we collected quarterly data and aggregated the EBITDA and revenue data so that all firms are measured over the same time period. 12 We discarded 19 firms whose fiscal quarters do not align with the calendar quarters. We define two samples for each multiple: the firms with positive multiples (the Positive sample), and all firms (the Full Dataset sample). The comparable companies 12 Because of earnings revisions and corrections, the sum of the quarterly measures does not always equal the annual measures. Due to the firms different fiscal years, it is not possible to use the updated annual measures for all firms. Our qualitative results do not change when using revised annual earnings where possible (i.e. the firms whose fiscal year ends on 12/31/2010.) Securities Litigation and Consulting Group, Inc
10 method is only used on the Positive sample, while the regression method is used on both samples. Table 4 provides information about the different samples we use by industry. Table 4: Description of Industries and Samples EV/EBITDA EV/Revenue Positive Sample Full Dataset Sample Positive Sample Full Dataset Sample Pharmaceutical Preps (2834) Perfumes & Cosmetics (2844) Household Audio & Video (3651) While all of firms within the same SIC code are in the same industry, they may nevertheless not be truly comparable. For instance, in the pharmaceutical industry, long-established, multi-billion dollar firms like Pfizer and Johnson & Johnson should not be used to value young, small firms who have little revenue and who derive most of their value from potential future success. Therefore, in the Pharmaceutical industry, we limit the group of comparable firms to be those with similar enterprise values to the firm being valued. The results we present below use the next 10 larger firms, and the next 10 smaller firms (for a total of 20), as the group of comparable companies. 13 The Comparable Companies Method The comparable companies estimates are computed in the same manner as described earlier in this paper. For each firm in the sample, we compute the Enterprise- Value-to-EBITDA and Enterprise-Value-to-Revenue ratios for the comparable companies, average these ratios, and multiply the average peer company ratio by either the subject firm s EBITDA or Revenue. The Regression Method The original motivation for this paper came from an observation that the comparable companies method is in fact quite similar to running a regression on an extremely small sample of comparable firms, with the regression constant constrained to equal zero. Since there is no compelling reason that enterprise value must be directly 13 We experimented with different size groups and found no substantive change in the qualitative results. 10 Rethinking Comparable Companies Method, First Draft.
11 proportional to EBITDA or Revenue, we relax this constraint in our regression analysis. We model enterprise value as a linear function of the earnings variable: where is enterprise value, is either EBITDA or Revenue, α and β are parameters to be estimated, and ε is the error term. We follow Liu, Nissim, and Thomas (2002) and scale both sides by enterprise value. This is done to correct for Heteroskedasticity, and, as explained in Baker and Ruback (1999), is likely to give more precise estimates. The equation we estimate is:. We estimate this equation using ordinary least squares, which chooses values for α and β that minimize the sum of the squared differences between the actual and predicted enterprise values. The group of comparable firms is formed in the same way as in the comparable companies estimates. The estimate of enterprise value is computed as where is the target firm s predicted enterprise value, is the value of the target s scaling variable, is the estimate of the constant, and is the estimate of the slope coefficient. 14,15 Comparing the Comparable Companies and Regression Methods To measure accuracy, we compute the absolute percentage error of each estimate. The absolute percentage error is defined as the absolute value of the difference between the estimated value and the true value, divided by the true value. Before stating our results, it is useful to see how the two estimation techniques differ graphically. We will show how the comparable companies and regression analysis methods estimate the value of Astex Pharmaceuticals, Inc. For expository purposes, the group of comparable companies is limited to five firms of similar value from the same SIC code (2834). This example was chosen from our dataset because it nicely illustrates the problems with the comparable companies method and shows how the regression method can improve the valuation. Figure 5 plots enterprise value and EBITDA for the five comparable companies. 14 A similar model omitting the constant was also estimated. As expected, this model, which effectively restricts the constant to be zero, performed worse than the unconstrained model. 15 Extending the model to incorporate more than one measure of earnings as an explanatory variable does not improve estimates. The problem is that the earnings variables are highly correlated, which leads to multicollinearity in the explanatory variables. As explained in Greene (2003), the variance of the estimated slope coefficients becomes very large when the explanatory variables are highly correlated. When this is the case, the predicted values become very inaccurate. Securities Litigation and Consulting Group, Inc
12 Enterprise Value (Millions) Enterprise Value (Millions) Figure 5: Enterprise Value and EBITDA for the Comparable Companies $160 $140 $120 $100 $80 $60 $40 $20 $0 $0 $5 $10 $15 $20 $25 $30 $35 $40 $45 EBITDA (Millions) The enterprise-value-to-ebitda multiples for these five firms can be represented graphically by drawing a line from the origin to the data point for each firm. These multiples, along with the average, are shown in Figure 6. Figure 6: Representing Multiples Graphically $160 $140 $120 $100 $80 $60 $40 $20 $0 $0 $5 $10 $15 $20 $25 $30 $35 $40 $45 EBITDA (Millions) 12 Rethinking Comparable Companies Method, First Draft.
13 Enterprise Value (Millions) Astex s approximately $110 million estimated enterprise value, computed by multiplying the mean of the comparable companies multiples by the Astex s $16.4 million EBITDA, is illustrated in Figure 7. Figure 7: Graphical Representation of the CCV Estimate $160 $140 $120 $100 $80 $60 $40 $20 $0 $0 $5 $10 $15 $20 $25 $30 $35 $40 $45 EBITDA (Millions) Some of the practitioner-oriented literature suggests using the median of the multiples in addition to, and sometimes instead of, the mean. To use the median multiple graphically, we would simply use the firm with the median slope to predict the target s value instead of drawing a new line with the average (mean) slope. In Figure 8 we plot the predicted enterprise value against the observed enterprise value. The prediction error is the vertical distance between the two points. In order to turn this into a percentage error, we would simply divide the prediction error by the observed enterprise value of the firm. In this case, the predicted value is $108.8 million, while the observed enterprise value of Astex Pharmaceuticals is $42.9 million. This corresponds to a percentage error of more than 150%. If we use the median multiple, the estimated enterprise value is $105.2 million, giving a percentage error of 145.3%. Securities Litigation and Consulting Group, Inc
14 Enterprise Value (Millions) Enterprise Value (Millions) Prediction Error Figure 8: CCV Prediction Error $160 $140 $120 $100 Predicted Value $80 $60 $40 Observed Value $20 $0 $0 $5 $10 $15 $20 $25 $30 $35 $40 $45 EBITDA (Millions) Regression analysis, on the other hand, fits a line to the data in order to minimize the sum of the squared prediction errors. The prediction line for the regression for the valuation of Astex is shown in Figure 9. To compute the estimated value, we multiply Astex s $16.4 million EBITDA by the estimated 1.19 slope coefficient and add the estimated constant. The predicted value and error are also shown in Figure 9. Figure 9: Regression Analysis Predicted Values and Prediction Error $160 $140 $120 $100 $80 $60 $40 Predicted Value Observed Value $20 $0 $0 $10 $20 $30 $40 $50 EBITDA (Millions) 14 Rethinking Comparable Companies Method, First Draft.
15 The estimate obtained from regression analysis is $63.8 million, which corresponds to a prediction error of 48.7%. This is much lower than the comparable companies estimates percentage error of over 150%. V. Results In this section we present the results of our empirical analysis. There are three ways in which regression analysis is superior to the comparable companies method. First, regression analysis is more accurate when it is constrained to use the same data as the comparable companies method. Second, it is able to take advantage of more data than the comparable companies method, and its estimates improve when using this data. Third, regression analysis can value firms which the comparable companies method cannot. Table 5 provides summary statistics of the absolute percentage errors obtained from our different estimation methods. Three estimation techniques are used in this table: the comparable companies method with both the mean and median multiple, and regression analysis. All valuations in this table are on firms from the Positive sample, using only firms from the Positive sample as comparables. The table is split into two parts because results are reported when both EBITDA and revenue are used as explanatory variables. Table 5: Absolute Percentage Errors of Comparable Companies and Regression Estimates EBITDA as the Explanatory Variable Estimation Method Absolute Percentage Error Mean Median CCV Mean 389.3% 107.0% CCV Median 102.1% 64.3% Regression 55.5% 39.7% Revenue as the Explanatory Variable Estimation Method Absolute Percentage Error Mean Median CCV Mean 11,641.8% 1,016.4% CCV Median 11,217.7% 957.5% Regression 31.7% 9.0% Securities Litigation and Consulting Group, Inc
16 The first two rows of Table 5 show that the median multiple performs much better than the mean multiple as an estimator in the comparable companies method. This is because the mean can easily be skewed by one or two large values, while the median is less susceptible to this problem. The third row in Table 5 reports the results of the regression analysis estimates. Comparing this row to the first two rows in the table provides a direct comparison of the comparable companies and regression analysis methods of valuation. The same firms are valued, using the same group of comparables, for each method. The mean and median absolute percentage errors are smallest when using the regression analysis method. This shows that the regression method generates, on average, more accurate estimates than the comparable companies method. As further evidence, we found that the estimate from regression analysis was better than the comparable companies estimate for more than 84% of the firms. The regression estimates are much better because the regression technique does not impose as many restrictions on the data as the comparable companies method. In particular, value need not be directly proportional to the scaling variable in the regression model. While the comparable companies method effectively imposes this constraint, the regression method does not. In addition, the Ordinary Least Squares algorithm chooses the parameters to minimize the sum of squared errors in the group of comparables. The comparable companies method, in contrast, simply uses the mean or median of the comparable firms ratios. This renders the comparable companies estimates more susceptible to outliers. Another advantage of the regression analysis method of valuation is that it can make use of more data than the comparable companies method. Returning to our earlier example of valuing Astex Pharmaceuticals, Figure 10 shows why the comparable companies method does not typically include firms with negative multiples in its analysis. 16 Rethinking Comparable Companies Method, First Draft.
17 Enterprise Value (Millions) Figure 10: The Comparable Companies with Negative Multiples $160 $140 $120 $100 $80 $60 $40 $20 $0 -$10 $0 $10 $20 $30 $40 $50 EBITDA (Millions) This graph is identical to Figure 4 except a firm with negative EBITDA has been added to the group of comparable companies. The two firms with EBITDA near zero in the graph provide approximately the same information: in particular, firms can have a positive enterprise value even with very low EBITDA. The comparable companies method would typically discard the observation on the firm with the negative EBITDA. This is because its multiple would be a very large negative number. In contrast, the nearby firm with the slightly larger (and positive) EBITDA would have a very large positive multiple. So even though these firms provide very similar information, the comparable companies method would treat them very differently. Regression analysis, on the other hand, can easily incorporate this additional observation. If the firms are otherwise comparable, it is wasteful to throw out useful information. The regression method therefore allows the analyst to take advantage of more data than the comparable companies method. Figure 11 shows how the predicted values of the regression change as the additional observation is taken into account. Securities Litigation and Consulting Group, Inc
18 Enterprise Value (Millions) Figure 11: Regression Analysis Predicted Values with Negative Multiples $160 $140 $120 $100 $80 $60 $40 $20 $0 -$5 $5 $15 $25 $35 $45 EBITDA (Millions) The solid line is the original prediction line, estimated without the firm with negative EBITDA. The dashed line is the new prediction line after taking into account all relevant data. In this case, the predicted value of Astex, which has an EBITDA of $16.4 million, decreases, and the estimate moves closer to the true value. The summary statistics in Table 6 show that the valuation can be improved by incorporating all available information. Table 6: Absolute Percentage Errors When Including All Information EBITDA as the Explanatory Variable Estimation Method Sample Valued Comparables Sample Absolute Percentage Error Mean Median Regression Positive Positive 55.5% 39.7% Regression Positive Full Dataset 27.3% 10.7% Regression Full Dataset Full Dataset 50.8% 7.4% Revenue as the Explanatory Variable Estimation Method Sample Valued Comparables Sample Absolute Percentage Error Mean Median 18 Rethinking Comparable Companies Method, First Draft.
19 Regression Positive Positive 31.7% 9.0% Regression Positive Full Dataset 31.3% 7.1% Regression Full Dataset Full Dataset 32.4% 7.4% The third row of Table 5 is reproduced here as the first row of Table 6 for ease of comparison. Comparing the first two rows in Table 6 shows that valuation accuracy improves when more information is included in the estimation process. The sample of firms being valued is the same for these two rows (the Positive sample). The difference between these rows is in which firms are included in the group of comparable companies: in the second row, the comparable firms might have negative earnings, while in the first row all comparable firms must have positive earnings. 16 Since the average absolute percentage errors are smaller in the second row of Table 6, using all available data improves the valuation s accuracy. The estimates in the third row of Table 6 come from valuing all of the firms in our database, including those with negative earnings variables. The mean and median absolute percentage errors are approximately equal to the corresponding values in the second row, and do not differ in any systematic way. The regression method can be used to accurately value firms which the comparable companies method cannot. These results show that the regression analysis method of valuation is superior to the comparable companies method for three reasons. First, regression analysis is more accurate when it is constrained to use the same data as the comparable companies method. Second, it is able to take advantage of more data than the comparable companies method, and its estimates improve when this data is used. Third, it is able to accurately value firms which the comparable companies method cannot. VI. Conclusion This paper studied the Comparable Companies Valuation method as it is commonly used in practice. We presented a simple graphical description of the algorithm underlying the comparable companies method. These graphs show intuitively why the 16 In the context of our graphical analysis the group of comparables for estimations in the second row might look like Figure 10, while the group of comparables for estimations in the first row must look like Figure 5. Securities Litigation and Consulting Group, Inc
20 this method generates poor predictions of value. It is a very rudimentary technique without rigorous foundation. We then showed that an alternative prediction methodology using regression analysis performs much better than the comparable companies method. The estimates using regression analysis were shown to be much closer to the true value when using the same set of information as the comparable companies method. Additionally, regression analysis is able to take advantage of useful information contained in observations on firms with negative multiples. Including this information in the sample improves the estimates. Since the computational cost of using regression analysis is only slightly higher than the comparable companies method, we argue that practitioners should forego the comparable companies method in favor of using regression analysis. References Bader, L., Valuing Companies, Valuing Pension Plans, Contingencies, September/October Baker, M. and Rubak R. S., Estimating Industry Multiples, Working Paper, Cain, M. and Dennis, D., Information Production by Investment Banks: Evidence From Fairness Opinions, Working Paper, CFA Program Curriculum, Corporate Finance Level II, Pearson Custom Publishing, Boston, Cornell, B., Corporate Valuation, Irwin, Damodaran, A., Damodaran on Valuation: Security Analysis for Investment and Corporate Finance, Second Edition, Wiley Finance, Greene, W., Econometric Analysis, Fifth Edition, Prentice Hall, Ibbotson Associates, Cost of Capital 2004 Yearbook, Ibbotson Associates, Chicago, Koller, T., Goedhart, M., and Wessels, D., Valuation: Measuring and Managing the Value of Companies, McKinsey & Company, 5th Edition, John Wiley and Sons, Liu, J., Nissim D., and Thomas, J., Equity Valuation Using Multiples, Journal of Accounting Research, Vol. 40, No. 1, Rethinking Comparable Companies Method, First Draft.
Chapter 5: Business Valuation (Market Approach) This methodology values larger companies based upon the value of similar publicly traded For smaller companies, otherwise known as micro businesses (e.g.,
Chapter 340 Principal Components Regression Introduction is a technique for analyzing multiple regression data that suffer from multicollinearity. When multicollinearity occurs, least squares estimates
Business Valuation Review Regression Analysis in Valuation Engagements By: George B. Hawkins, ASA, CFA Introduction Business valuation is as much as art as it is science. Sage advice, however, quantitative
Chapter 14 Web Extension: Financing Feedbacks and Alternative Forecasting Techniques I n Chapter 14 we forecasted financial statements under the assumption that the firm s interest expense can be estimated
19878_09W_p001-009.qxd 3/10/06 9:56 AM Page 1 C H A P T E R 9 Web Extension: Financing Feedbacks and Alternative Forecasting Techniques IMAGE: GETTY IMAGES, INC., PHOTODISC COLLECTION In Chapter 9 we forecasted
Non-GAAP Net Income and Earnings Per Share Reconciliation (in thousands, except per share data): Fiscal 2013 Year Ended February 1, 2014 Recovery of Asset As Previously Impairment Non-GAAP Reported Impaired
ABSTRACT What accounting students should know about the price-earnings ratio Dean W. DiGregorio Southeastern Louisiana University The price-earnings ratio (P/E ratio) is a valuation multiple that can be
APPENDIX D: CALCULATION OF EVA FOR A HYPOTHETICAL SIMULCASTER As noted in the text, we calculated EVA for a hypothetical simulcaster in five steps, which are summarized below. Step 1: Identify firms with
Freeze Partnerships: Establishing the Preferred Rate Aaron M. Stumpf, CPA/ABV email@example.com Brian A. Hock firstname.lastname@example.org Overview n n n Partnership freezes involving related party transfers are generally
A Piece of the Pie: Alternative Approaches to Allocating Value Cory Thompson, CFA, CIRA email@example.com Ryan Gandre, CFA firstname.lastname@example.org Introduction Enterprise value ( EV ) represents the sum of debt
Business Valuation Insights Adjusting for Underfunded Pension and Postretirement Liabilities Christopher W. Peifer Fewer and fewer companies have pension liabilities recorded on their balance sheets. This
Breakeven, Leverage, and Elasticity Dallas Brozik, Marshall University Breakeven Analysis Breakeven analysis is what management is all about. The idea is to compare where you are now to where you might
1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 3(x - x) B. x 3 x C. 3x - x D. x - 3x 2) Write the following as an algebraic expression
Individuals: The objects that are described by a set of data. They may be people, animals, things, etc. (Also referred to as Cases or Records) Variables: The characteristics recorded about each individual.
What Do Short-Term Liquidity Ratios Measure? What Is Working Capital? HOCK international - 2004 1 HOCK international - 2004 2 How Is the Current Ratio Calculated? How Is the Quick Ratio Calculated? HOCK
Financial Statement Analysis: An Introduction 2014 Level I Financial Reporting and Analysis IFT Notes for the CFA exam Contents 1. Introduction... 3 2. Scope of Financial Statement Analysis... 3 3. Major
Research methods - II 3 2. Simple Linear Regression Simple linear regression is a technique in parametric statistics that is commonly used for analyzing mean response of a variable Y which changes according
Financial Highlights Data Overview Published: January 2013 Updated March 27, 2013 Institutional Shareholder Services Inc. Copyright 2013 by ISS www.issgovernance.com Table of Contents FINANCIAL HIGHLIGHTS
A Basic Introduction to the Methodology Used to Determine a Discount Rate By Dubravka Tosic, Ph.D. The term discount rate is one of the most fundamental, widely used terms in finance and economics. Whether
Valuation multiples A reading prepared by Pamela Peterson rake James Madison University Table of Contents Introduction... 1 Understanding the use of multiples... 1 Identifying the comparables... 1 Choosing
Journal of Finance, Accounting and Management, 3(2), 1-14, July 2012 1 Impact of Earnings per share on Market Value of an equity share: An Empirical study in Indian Capital Market Dr. Pushpa Bhatt, Sumangala
Journal Of Financial And Strategic Decisions Volume 8 Number 1 Spring 1995 THE DETERMINANTS OF ACTUARIAL ASSUMPTIONS UNDER PENSION ACCOUNTING DISCLOSURES V.Gopalakrishnan * and Timothy F. Sugrue * Abstract
COMMUNICATING THE VALUATION REPORT Dave Diehl, CFA Prairie Capital Advisors, Inc. email@example.com Chieoke Moore, CPA Prairie Capital Advisors, Inc. firstname.lastname@example.org OUTLINE OF TODAY S PRESENTATION
03-Seidman.qxd 5/15/04 11:52 AM Page 41 3 An Introduction to Business Financial Statements In this chapter, we build on the basic knowledge of how businesses are financed by looking at how firms organize
Section 1.5 Linear Models Some real-life problems can be modeled using linear equations. Now that we know how to find the slope of a line, the equation of a line, and the point of intersection of two lines,
Multiples Used to Estimate Corporate Value Erik Lie and Heidi J. Lie We evaluated various multiples practitioners use to estimate company value. We found, first, that the asset multiple (market value to
ISS Governance Services Proxy Research Company Financials Compustat Data Definitions June, 2008 TABLE OF CONTENTS Data Page Overview 3 Stock Snapshot 1. Closing Price 3 2. Common Shares Outstanding 3 3.
Earnings Announcement and Abnormal Return of S&P 500 Companies Luke Qiu Washington University in St. Louis Economics Department Honors Thesis March 18, 2014 Abstract In this paper, I investigate the extent
A Primer on Valuing Common Stock per IRS 409A and the Impact of Topic 820 (Formerly FAS 157) By Stanley Jay Feldman, Ph.D. Chairman and Chief Valuation Officer Axiom Valuation Solutions May 2010 201 Edgewater
Comparable Companies Analysis Educational TMT Group with Assistance from the FIG Group Mario Campea, Michael Liu, Steve Lo, Kevin Gryp & Vinayak Modi 06-Nov-13 Disclaimer The analyses and conclusions of
DETERMINING AGENCY VALUE PART 5 VALUATION METHODOLOGY (continued) By: Chuck Coyne, ASA This month we continue our discussion of how to determine an agency s value. Last month we discussed many of the typical
King Saud University College of Administrative Science Department of Accounting 2 nd Semester, 1426-1427 Accounting for Multiple Entities Chapter 15 Prepared By: Eman Al-Aqeel Professor : Dr: Amal Fouda
R. Halsey Wise Chairman and Chief Executive Officer MedAssets, Inc. 100 North Point Center, East, Suite 200 Alpharetta, GA 30022 August 3, 2015 cc: Board of Directors Dear Halsey, Starboard Value LP, together
RIVIER ACADEMIC JOURNAL, VOLUME 3, NUMBER 2, FALL 2007 AN ANALYSIS OF WORKING CAPITAL MANAGEMENT EFFICIENCY IN TELECOMMUNICATION EQUIPMENT INDUSTRY Vedavinayagam Ganesan * Graduate Student, EMBA Program,
VALUATION JC PENNEY (NYSE:JCP) Prepared for Dr. K.C. Chen California State University, Fresno Prepared by Sicilia Sendjaja Finance 129-Student Investment Funds December 15 th, 2009 California State University,
A Primer on Forecasting Business Performance There are two common approaches to forecasting: qualitative and quantitative. Qualitative forecasting methods are important when historical data is not available.
1 THE EFFECT OF FINANCIAL PERFORMANCE FOLLOWING MERGERS AND ACQUISITIONS ON FIRM VALUE Edwin Yonathan, Universitas Indonesia Ancella A. Hermawan, Universitas Indonesia 2 THE EFFECT OF FINANCIAL PERFORMANCE
MINITAB ASSISTANT WHITE PAPER This paper explains the research conducted by Minitab statisticians to develop the methods and data checks used in the Assistant in Minitab 17 Statistical Software. One-Way
Analysis of School Finance Equity and Local Wealth Measures in Maryland Prepared for The Maryland State Department of Education By William J. Glenn Mike Griffith Lawrence O. Picus Allan Odden Picus Odden
UNDERSTANDING THE CHARACTERISTICS OF YOUR PORTFOLIO Although I normally use this space to ruminate about various economic indicators and their implications, smartly advancing asset prices have encouraged
A Review of Cross Sectional Regression for Financial Data You should already know this material from previous study But I will offer a review, with a focus on issues which arise in finance 1 TYPES OF FINANCIAL
CHAPTER 7: OPTIMAL RIKY PORTFOLIO PROLEM ET 1. (a) and (e).. (a) and (c). After real estate is added to the portfolio, there are four asset classes in the portfolio: stocks, bonds, cash and real estate.
Business Value Drivers by Kurt Havnaer, CFA, Business Analyst white paper A Series of Reports on Quality Growth Investing jenseninvestment.com Price is what you pay, value is what you get. 1 Introduction
Carbonite Reports Record Revenue for Second Quarter of 2014 BOSTON, MA July 29, 2014 - Carbonite, Inc. (NASDAQ: CARB), a leading provider of hybrid backup and recovery solutions for businesses, today announced
Gift and Estate Tax Valuation Insights Voting Stock and Nonvoting Stock: Allocating Equity Value Aaron M. Rotkowski Business valuations performed for gift tax or estate tax purposes often involve the valuation
2013 Canadian Pay for Performance Methodology Frequently Asked Questions January 23, 2013 BE SURE TO CHECK OUR WEBSITE FOR THE LATEST VERSION OF THIS DOCUMENT BEFORE RELYING ON THE GUIDANCE HEREIN Institutional
Frequent Acquirers and Financing Policy: The Effect of the 2000 Bubble Burst Autoria: Eduardo Kazuo Kayo, Douglas Dias Bastos Abstract We analyze the effect of the 2000 bubble burst on the financing policy.
Fundamentals, Techniques & Theory CAPITALIZATION/DISCOUNT RATES CHAPTER FIVE CAPITALIZATION/DISCOUNT RATES I. OVERVIEW Money doesn t always bring happiness People with ten million dollars are no happier
CHANGE IN REPORTING THE FUNDED STATUS OF PENSIONS: IMPACT ON DEBT-ASSET AND DEBT-EQUITY RATIOS Douglas K. Schneider, East Carolina University Mark G. McCarthy, East Carolina University Lizabeth Austen-Jaggard,
UBS Securities LLC 299 Park Avenue New York NY 10171 www.ubs.com September 12, 2005 VARIG, S.A. (VIAÇÃO AÉREA RIO-GRANDENSE) Em Recuperação Judicial Brazilian Bankruptcy Court in Rio de Janeiro, Brazil
1) Introduction Marketing Mix Modelling and Big Data P. M Cain Big data is generally defined in terms of the volume and variety of structured and unstructured information. Whereas structured data is stored
Telesat Reports Results for the Quarter and Year Ended December 31, 2014 OTTAWA, CANADA, February 26, 2015. Telesat Holdings Inc. ( Telesat ) today announced its financial results for the three month and
ISSUES ON USING THE DISCOUNTED CASH FLOWS METHODS FOR ASSET VALUATION CRISTINA AURORA BUNEA-BONTAŞ 1, MIHAELA COSMINA PETRE 2 CONSTANTIN BRANCOVEANU UNIVERSITY OF PITESTI, FACULTY OF MANAGEMENT-MARKETING
TYPES OF FINANCIAL RATIOS In the previous articles we discussed how to invest in the stock market and unit trusts. When investing in the stock market an investor should have a clear understanding about
Using Statistical Data to Make Decisions Module 3: Correlation and Covariance Tom Ilvento Dr. Mugdim Pašiƒ University of Delaware Sarajevo Graduate School of Business O ften our interest in data analysis
Models of Risk and Return Aswath Damodaran Aswath Damodaran 1 First Principles Invest in projects that yield a return greater than the minimum acceptable hurdle rate. The hurdle rate should be higher for
COMPANY CONTACTS: Jay S. Hennick Founder & CEO D. Scott Patterson President & COO John B. Friedrichsen Senior Vice President & CFO (416) 960-9500 FOR IMMEDIATE RELEASE FirstService Reports Record Fourth
Preparing Consolidated Statements Web This reading illustrates the preparation of consolidated financial statements for Company P and Company S. Learning how to interpret and analyze consolidated financial
For Financial Professional Use Only Factoring In and in the US Market Morningstar Research Paper January 2014 Paul Kaplan, Ph.D., CFA Director of Research, Morningstar Canada +1 416 484-7824 email@example.com
The Directors Education Series Understanding Bank Ratios Bankers Insight Group, LLC JEFFERY W. JOHNSON What Banking Factors Should be Measured? Asset Quality Capital Adequacy Earnings Liquidity 1 Asset
CHAPTER 2 Accounting for Accruals and Deferrals LEARNING OBJECTIVES After you have mastered the material in this chapter, you will be able to: SECTION 1: SHOW HOW ACCRUALS AFFECT FINANCIAL STATEMENTS LO
Discussion of Which Approach to Accounting for Employee Stock Options Best Reflects Market Pricing? David Aboody firstname.lastname@example.org UCLA Anderson School of Management, 110 Westwood Plaza, Los Angeles,
the determinants of p/e ratio in telecommunication sector: developed vs emerging markets Author : NICULCEA SIMONA Coordinator: Conf. Univ. Dr. CIOBANU ANAMARIA THE DETERMINANTS OF P/E RATIO IN TELECOMMUNICATION
From Saving to Investing: An Examination of Risk in Companies with Direct Stock Purchase Plans that Pay Dividends Raymond M. Johnson, Ph.D. Auburn University at Montgomery College of Business Economics
FREDER IC W. COO K & CO., INC. NEW YORK CHICAGO LOS ANGELES SAN FRANCISCO ATLANTA HOUSTON BOSTON May 1, 2015 SEC Proposes Pay-for-Performance Disclosure Rules On April 29, 2015, nearly five years after
Nuveen NWQ Global Equity Income Fund Summary Prospectus October 30, 2015, as supplemented June 1, 2016 Ticker: Class A NQGAX, Class C NQGCX, Class I NQGIX This summary prospectus is designed to provide
VALUATIONS I Financial Metrics, Ratios, & Comparables Analysis Fall 2015 Comp Week 6 CODE: COMPS Timeline Date Topic 9/10/15 Introduction to Finance 9/17/15 Qualitative Analysis: SWOT and Porter s Five
Examining the Relationship between Innovation And Company Values of Apple Inc. Ascariena Rafinda, and Ana Noveria Abstract--- The purpose of this study is to estimating the company value and performance
INVESTMENTS IN OFFSHORE OIL AND NATURAL GAS DEPOSITS IN ISRAEL: BASIC PRINCIPLES ROBERT S. PINDYCK Bank of Tokyo-Mitsubishi Professor of Economics and Finance Sloan School of Management Massachusetts Institute
Income Tax Valuation Insights Buyers and Sellers of an S Corporation Should Consider the Section 338 Election Robert P. Schweihs There are a variety of factors that buyers and sellers consider when deciding
The Profit Function: A Pedagogical Improvement For Teaching Operating Breakeven Analysis Bruce D. Bagamery, Central Washington University - Lynnwood Abstract This paper presents a graphical approach for
SPDR Wells Fargo Preferred Stock ETF Summary Prospectus-October 31, 2015 PSK (NYSE Ticker) Before you invest in the SPDR Wells Fargo Preferred Stock ETF (the Fund ), you may want to review the Fund's prospectus
MØA 155 PROBLEM SET: Summarizing Exercise 1. Present Value  You are given the following prices P t today for receiving risk free payments t periods from now. t = 1 2 3 P t = 0.95 0.9 0.85 1. Calculate
CREATING A CORPORATE BOND SPOT YIELD CURVE FOR PENSION DISCOUNTING I. Introduction DEPARTMENT OF THE TREASURY OFFICE OF ECONOMIC POLICY WHITE PAPER FEBRUARY 7, 2005 Plan sponsors, plan participants and
Chapter 6: Constructing and Interpreting Graphic Displays of Behavioral Data Chapter Focus Questions What are the benefits of graphic display and visual analysis of behavioral data? What are the fundamental
Mathematics Probability and Statistics Curriculum Guide Revised 2010 This page is intentionally left blank. Introduction The Mathematics Curriculum Guide serves as a guide for teachers when planning instruction
FOR IMMEDIATE RELEASE Contact: Olivia Snyder, Investor Relations Analyst (617) 219-1410 Government Properties Income Trust Announces Third Quarter 2015 Results Normalized FFO of $0.59 Per Share for the
The Case for Investing in Master Limited Partnerships (MLPs) By Richard Fortin, CFA Senior V.P. Portfolio Manager, Stonebridge Advisors LLC July 1, 2008 Advisor Perspectives welcomes guest contributions.
CHAPTER 2 ACCOUNTING STATEMENTS, TAXES, AND CASH FLOW Answers to Concepts Review and Critical Thinking Questions 1. True. Every asset can be converted to cash at some price. However, when we are referring
Simple linear regression Introduction Simple linear regression is a statistical method for obtaining a formula to predict values of one variable from another where there is a causal relationship between
to raise new ideas and improve policy debates through quality information and analysis on issues shaping New Hampshire s future. One Eagle Square Suite 510 Concord, NH 03301-4903 (603) 226-2500 Fax: (603)
Fama-French and Small Company Cost of Equity Calculations This article appeared in the March 1997 issue of Business Valuation Review. Michael Annin, CFA Senior Consultant Ibbotson Associates 225 N. Michigan
News Release ACI Worldwide, Inc. Reports Financial Results for the Quarter Ended March 31, 2014 HIGHLIGHTS SNET bookings of $122 million, up 59% from Q1 last year Recurring revenue up 57% from last year,
Using the Bloomberg terminal for data Contents of Package 1.Getting information on your company Pages 2-31 2.Getting information on comparable companies Pages 32-39 3.Getting macro economic information
Dear Profit Master, Congratulations for taking the next step in improving the profitability and efficiency of your company! Profit Guard will provide you with comparative statistical and graphical measurements
Chapter 7 7-1 Income bonds do share some characteristics with preferred stock. The primary difference is that interest paid on income bonds is tax deductible while preferred dividends are not. Income bondholders