The importance of industry-specific multiples is further emphasised by Tasker , who finds a systematic use of industry-specific multiples among investment bankers and analysts in acquisition transactions. Bhojraj and Lee and Bhojraj, Lee, and Ng use a regression-based approach for selecting comparable firms independent of industry affiliation. The advantage of this approach that it allows to simultaneously control for the effect of several explanatory variables, and to empirically estimate the appropriate weights to put on each variable.
They find that fundamental factors such as profitability, growth, and risk, are strongly associated with the enterprise value-to-sales and price-to-book ratios. While Bhojraj and Lee and Bhojraj et al. De Franco et al. Moreover, their research suggests that analysts choose peers strategically.
In summary, the literature suggests that objective criteria based on valuation similarity should be applied when selecting peer groups. Moreover, prior research also suggests the importance of industry affiliation in peer-group selection. It is possible to derive expressions for valuation multiples using traditional finance theory. Equation 1 demonstrates the theoretical link between a valuation multiple and its value drivers. Ideally, this model should be at the centre stage of any selection of peer groups.
Companies with similar structural relationships between value-drivers and valuation should be grouped together. The idea is that companies in the same peer group should be characterised by similar relation between valuation and value drivers. If they are not, we should be able to find a structural break in the valuation model.
However, there are some concerns about the appropriateness of model in Equation 1 , especially for oil and gas companies. The price-to-book ratio is not a common multiple for valuing oil and gas companies. Omission of explanatory variables that affect the left-hand side variable in a regression may result in the omitted variables bias, negatively impacting the inference we can make from the models.
Typically, a set of control variables are included, and which act as proxies for unobserved explanatory variables. However, the selection of appropriate control variables is a very challenging task for the researcher and may not be successful. An alternative to using explicit control variables is to apply panel data techniques, such as fixed effects.
The benefit of using a fixed effects model is that the latter technique is designed to capture the impact on the left-hand side variable from unobserved variables. The type of specification in Equation 2 assumes that the relationship is stable, i. This implication allows us to test for structural shifts in the relation between valuation and value drivers. If there are two different peer groups, there will be two different parametric specifications of the relationship between value-drivers and valuation in the sample:.
If the coefficients in the two equations are statistically different from each other, this provides evidence for a structural break in the econometric modelling of multiples valuation see e. Chow, Hence, structural break tests can be applied to examine whether the valuation process changes when extending the group of peers.
We test for structural breaks using the dummy variable approach Gujarati, a , b , which allows us to run a single regression instead of two, which would be the case for a Chow test Chow, Gujarati asserts that the dummy variable method is preferable to the Chow test for several reasons. First, running only a single regression can substantially abridge the analyses. Second, the single regression can be used to test a variety of hypotheses. Third, the Chow test does not explicitly indicate which coefficient, intercept or slope is different. Fourth, pooling increases the degrees of freedom and may improve the relative precision of the estimated parameters.
We test for structural break in the model by testing for joint significance of the interaction terms using a Wald test. That is, one tests if the hypothesis that the interaction terms are jointly significantly equal to 0 i. If the null hypothesis is rejected, then the results provide evidence for a structural break in the econometric modelling of valuation.
The sample consists of oil and gas companies for the — period drawn from John S. From this universe, we select the 50 of the largest oil and gas companies that report both financials and supplementary information in accordance with the U.
The descriptive statistics are presented in Table 1. The aim of the analysis is to examine whether we can expand this initial group of companies by adding additional firms if they are significantly similar. If we find evidence of either serial correlation or heteroskedasticity, or both, we need to adjust the standard errors before calculating the t -values and p -values from the regression. Heteroskedasticity can be corrected for using the White approach and serial correlation can be corrected using the Arrelano method for fixed effects models Arellano, The analysis is carried out as follows.
First, we produce an empirical model of the relationship between price-to-book and its value drivers for a subset of five Super Major oil companies. All other companies will be compared to this particular group. Second, we introduce firms classified as international majors, one by one. Chow test is used to investigate whether the new company has a significantly different relationship between valuation and financial indicators than the five original super majors.
First, we carry out tests to see whether we should use a pooled OLS or a fixed effects model pooling test and whether a fixed effects or a random effects model is appropriate Hausman test: Hausman, The tests conclude that a fixed effects model is the most appropriate for our data Table 3. Secondly, we test for heteroskedasticity and serial correlation in the residuals from the empirical estimation of the model in Equation 5 using the initial subsample of oil and gas super majors.
We cannot find evidence of neither heteroskedasticity, nor serial correlation Table 4 and we do not need to correct our standard errors. Finally, we estimate the model in Equation 5 and the results are presented in Table 5. Note: The benchmark model includes the five super majors and is compared against additional companies. The values in parantheses are p -values from the Breusch—Pagan test for heteroskedasticity and Breusch—Godfrey test for serial correlation. The values in the table are F -values pooled test for pooled OLS vs. The values in parantheses are p -values and the significance is denoted by asterisks:.
The coefficient on the profitability variable is significant Table 5 , which provides evidence that EBITDA is a relevant profitability measure for the oil and gas majors.agendapop.cl/wp-content/locator/quri-como-rastrear-el.php
Equity Valuation Using Multiples : An Empirical Study on Plantation Sector
Moreover, the difference in the two adjusted R 2 measures suggest that the fixed effects, both for time and individuals, capture the effects from unobserved variables. Next, we include new companies to the Super Major group, one by one, using an extended sample. Significance of the joint interaction terms indicates that this new company belongs in the Super Major group.
Our results suggest that several of the oil and gas firms e. The implication of our study is that the oil major peer group could benefit from adding other companies, such as ENI. Arguably, a larger peer group would improve the accuracy of the multiples valuation method. In summary, our results suggest that the approach used in the current study can be used to in the selection of companies to be included in peer groups for the purpose of equity valuation using multiples. The results should be of interest to investors and equity analysts covering the oil and gas sector, as well as other industries.
The Chow test for structural shift is a methodology that can be used to identify peer groups that have similar structures in their valuation process. We do not find that other groups of firms have a structurally similar valuation process. The authors are grateful to IHS Herold for providing the data for our research.
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Value and Business Valuation Bibliography A-L
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Financial Economics. Authors 2. Close Frank Asche frank. Download PDF. Cite this article as:. Article Figures and tables References.
Abstract Abstract This study presents a novel approach to selecting comparable companies in equity valuation. Public Interest Statement Equity valuation is one of the most important applications of finance theory. Introduction Equity valuation is one of the most important applications of finance theory.
Literature review This section presents some of the findings on selection of comparable firms in the finance and accounting literature.
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