Business Valuation Through Market Multiples

Abstract

This chapter is devoted to the valuation of companies through the multiples approach. Despite the simplicity in its application, the multiples method hides many shortcomings. In this chapter, we present the main multiples used in corporate valuations, outline the procedure, and highlight the criticalities in the application process. We conclude the chapter by providing a new approach for using the value maps.

Appendix: The Unlevered Value Maps: An Empirical Evaluation

Since this is a new method that has not been used much by operators in the sector, this appendix aims to highlight whether adjusting the multiple of the company’s debt level could improve the goodness of fit (represented by the R Squared) of the regression, compared to using the simple non-adjusted multiple. To this end, we have considered eight company assessments referring to companies in different sectors. These assessments were made by the authors of this text, using the methodology that is the subject of this analysis.

The Figs. 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8 and 4.9 APP report the values of the multiples of the sample of companies and the regressions. Although a thorough empirical assessment would require a greater number of cases for each regression (as well as an assessment across many more sectors), we believe that the operation presented here can still provide useful indications regarding the validity of the described method.

Fig. 4.1

(Source Data processed by the authors)

APP—Company belonging to the sector of design and production of sun awnings, pergolas, and outdoor structures (APPAREL and HOMEBUILDING)

Fig. 4.2

(Source Data processed by the authors)

APP—Company belonging to the sector of household appliances and kitchen components (FURNISHING)

Fig. 4.3

(Source Data processed by the authors)

APP—Company working in the frozen-food industry (RETAIL GROCERY and FOOD)

Fig. 4.4

(Source Data processed by the authors)

APP—Company belonging to the business consulting sector (SERVICES)

Fig. 4.5

(Source Data processed by the authors)

APP—Company working in the kitchen construction industry (BUILDING MATERIALS)

Fig. 4.6

(Source Data processed by the authors)

APP—Company belonging to the engineering and construction sector (ENGINEERING/CONSTRUCTION)

Fig. 4.7

(Source Data processed by the authors)

APP—Company belonging to the real-estate sector (REAL ESTATE)

Fig. 4.8

(Source Data processed by the authors)

APP—Company belonging to the window manufacturing sector (CONSTRUCTION SUPPLIES)

Fig. 4.9

(Source Data processed by the authors)

APP—Company belonging to the foodservice sector (RESTAURANT)Footnote

In the case of the Longhino comparable, the unlevered multiple is higher than the levered one. This is due to the fact that this company has an NFP that is below zero (presence of liquidity), which in the unlevered multiple has been added to the value of the EV since, given the company’s business, it was deemed of operating nature. In fact, the (levered) EV does not consider this liquidity, since it corresponds to the sum of the market-cap value and the negative NFP (which is algebraically subtracted).

Four of the nine cases presented above show that the regression made with an adjusted multiple have an R-Squared that is substantially in line with the one performed with an unadjusted multiple (in the range of a 1–2% difference). This trend has always occurred for the ROS – EV/Sales ratio, which consequently does not seem to benefit from the debt adjustment, contrary to what happens with the ROIC – EV/IC ratio.

In four cases, the improvement in terms of R-Squared is tangible and greater than 1–2%, validating the usefulness of the unlevered value maps compared to standard ones. Only one case shows a value of the R Squared that is tangibly worse than the standard regression.

In general, we see how the improvement in the goodness of fit of the regression occurs in particular when the standard regression has a value that is below 0.5, and when it refers to businesses that are in the industrial sector, for which we use the ROIC – EV/IC ratio. For these cases, we confirm the usefulness of the adjustment proposed in this paragraph.

Using the data in Fig. 4.5 APP—which refers to a company that works in the kitchen construction industry, with an ROIC equal to 10%, a tax rate of 24%, a net employed capital of €5,000,000, and a net financial position of €3,000,000—we can determine the value of equity in three steps:

• 1. Determining the appropriate unlevered EV/IC:

  $$\frac{EV}{IC}_{UL}=4.6909\cdot 10\%+0.9405=1.41$$

• 2. Determining the value of the assets:

  $$EV={EV}_{U}+D\cdot {t}_{c}=\text{5,000,000}\cdot 1.41+24\%\cdot \text{3,000,000}={7,770,000}{\hbox{\EUR}}$$

• 3. Determining the value of equity:

  $$E=EV-D=\text{7,770,000}{\hbox{\EUR}}-\text{3,000,000}{\hbox{\EUR}}=\text{4,770,000}{\hbox{\EUR}}$$