the use of multiples in the south african equity

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Meditari Accountancy ResearchThe use of multiples in the South African equity market: is the popularity of the price earnings ratio

justifiable from a sector perspective?

W.S. Nel

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editari Accountancy Research Vol. 17 No. 2 2009 : 101-115 101

The use of multiples in the South African equitymarket: is the popularity of the price earnings

ratio justifiable from a sector perspective?

WS Nel

Department of AccountingUniversity of Stellenbosch

Abstract

The price earnings (P/E) ratio is generally regarded as the most popular multiple used

to value equity in practice. Although this is supported by evidence from practice, the

use of the P/E ratio has not been substantiated by evidence from research. This article

investigates the accuracy of the five most popular multiples, including the P/E ratio,

in valuing the equity of South African companies listed on the JSE SecuritiesExchange, for the period 1988 to 2007. The research results revealed that the P/E

ratio does not perform the most accurate valuations across all sectors and that

different multiples should be used for different sectors. There is an opportunity to

enhance the accuracy of equity valuations based on multiples by employing multiples

other than the P/E ratio.

Key words

Equity valuation

Multiples

Price earnings ratio

Valuation errors

1 Introduction

It is generally held that multiples are not suitable primary valuation techniques and that

they should ideally be used to supplement more acceptable, comprehensive valuation

techniques such as the free cash flow model. This approach was confirmed by Courteau,

Kao, O’Keefe and Richardson (2003:24), who indicated that valuations based on multiples

perform less accurate valuations than more sophisticated alternatives. The results of a

survey conducted by PricewaterhouseCoopers (PwC 2008:13) revealed that the discounted

cash flow technique is used more frequently than market-based techniques such as the price

earnings (P/E) ratio. While multiples are used extensively in practice, usually in

conjunction with other models, there seems to be limited empirical work available to

provide guidance on which multiples best suit different sectors in South Africa. Although

there is ample research on equity valuation internationally, this appears not to be the case in

emerging markets (Bruner, Conroy, Estrada, Kritzman & Li 2002:311).


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Multiples in the SA equity market: is the popularity of the P/E ratio justifiable from a sector perspective?

102 editari Accountancy Research Vol. 17 No. 2 2009 : 101-115

In this study, the five most popular multiples currently used in South Africa will be usedto calculate the equity value of companies listed on the JSE Securities Exchange, in order to

ascertain how well they approximate actual share values. The total population for all the

multiples includes 15 650 observations, spanning 24 sectors, for the period 1988 to 2007.

Section 2 states the objectives of the research, followed by the evidence from research

and practice regarding multiples in section 3. Data selection is covered in section 4. In

section 5, the research methodology is discussed, including the mathematical definition of

the concept of valuation errors, which serves as the premise for the research. The results of

the research are presented in section 6, where the evidence is compared with current

practice in South Africa. Concluding remarks are offered in the final section.

2 Objectives of the research

The primary aim of this article is to establish whether research supports analysts’ preference for the use of the P/E ratio as a market-based approach to equity valuations, as

indicated by the PwC survey (2008:41). Technically, the most appropriate multiples for any

sector will be those with the tightest distribution around the mean, that is, those with the

lowest dispersion or the tightest range (Pratt 2006:4). To this end, the mean, median,

standard deviation, variation coefficient and various dispersion ranges will be calculated in

order to identify the multiples with the tightest dispersion for each sector.

The secondary aim of this article is to determine which multiples that are currently most

popular in practice may be more appropriate – in other words, present a more accurate

equity valuation for different sectors. The five multiples selected for this purpose are the

top five multiples as per the PwC survey, namely the P/E ratio, market value of invested

capital (MVIC)1

/earnings before interest, tax, depreciation and amortisation (EBITDA),MVIC/earnings before interest and tax (EBIT), price/book value of equity (P/BVE) and

price/profit before tax (P/PBT).

3 Evidence from research and practiceEquity valuation techniques based on multiples usually have broad dispersions (Fernándes

2001:2), which is why valuations based on multiples are not generally regarded as the

purest equity valuation models. While multiples may not be the purest approach to

determine a company’s equity value, in practice they are used as value indicators in

conjunction with a more conceptually sound approach. Equity valuations of unlisted entities

performed by means of multiples usually require the identification of an appropriate

benchmark multiple. Most research builds on the comparable company principle work of

Alford (1992:103), who found that the matching of past growth within a sector improves

the performance of multiples. Although research conducted by Berkman, Bradhury and

Ferguson (2000:82) in New Zealand presents evidence to the contrary, their evidence was based on data that were difficult to obtain in a thinly traded capital market, which may have

obscured their results.

1 MVIC = market capitalisation + preference shares + interest-bearing debt


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3.1 Sector multiples According to Goedhart, Koller and Wessels (2005:1), many analysts calculate a sector

average multiple and multiply it by a specific company’s earnings to value the company’sequity. The starting point is usually the identification of a benchmark multiple of a similar

listed company in the same sector, or calculating the average of that multiple for the sector

in which the company operates. Russian researchers Ivashkovskaya and Kuznetsov

(2007:46) investigated the option of seeking comparable companies in developed countries.

They compared various Russian multiples with those of the USA and found that using

comparable across-border multiples led to a significant overvaluation of equity.

3.2 Value drivers

Although empirical work on multiples in emerging markets is limited, a number of

international researchers have conducted empirical research on multiples and value driversin particular. The debate on the main value drivers seems to focus on earnings and cash

flows. Liu, Nissim and Thomas (2002:23) found earnings to be the best value driver in

valuing equity. They focused on price multiples and investigated which value drivers

performed the best amongst earnings, cash flows, dividends and revenue, to approximatestock prices in ten countries, including South Africa. They found that multiples based on

earnings generally performed the best valuations, while those based on cash flows and

dividends produced average results. Multiples based on revenue performed the worst.

Cheng and McNamara (2000:367) found similar results in a study of the valuation accuracy

of the P/E and the P/BVE ratios as benchmarks between 1973 and 1992. Their research

indicated that earnings was the most important value driver. Volker and Richter (2003:216)drew a similar conclusion.

A number of researchers have refined their research to determine which earnings-based

value drivers are superior to others. Baker and Ruback (1999:19) compared EBITDA, EBITand revenue as value drivers and found that sector-adjusted EBITDA outperformed EBIT

and revenue. Lie and Lie (2002:53) came to the same conclusion, finding EBITDA to be a

more accurate value driver than EBIT, and that forward-looking multiples outperformed

historical multiples. The latter was confirmed by Kim and Ritter (1999:430), who

concluded that two-year earnings per share (EPS) forecasts outperformed one-year

forecasts, while one-year EPS forecasts again dominated current EPS, in terms of the

accuracy of forecasts. In keeping with this research, Schreiner and Spremann (2007:18)

came to the conclusion that forward-looking multiples performed more accurate valuations

than trailing multiples. They discovered that the superiority of forward multiples depended

largely on the choice of the value driver.

3.3 The populari ty of the P/E r atio Research on specific multiples has largely focused on price multiples, which typically

includes a discussion of the P/E ratio. Since the general perception is that the P/E ratio is

the preferred multiple in equity valuations, executives may try to orchestrate a high P/E

ratio (Chadda, McNish & Rehm 2004:12). In a survey conducted in the UK, Barker

(1999:414) found that, although the P/E ratio is the primary multiple used by analysts, this

is not the case across all sectors. The survey results indicated that the dividend yield

surpassed the P/E ratio in the utilities and financial sectors, for example. Does this hold true

for South Africa as well, or is the P/E ratio the most appropriate multiple across all sectors?


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3.4 The fi ve most popular multiples used in practice in South Africa

The use of multiples is based on judgments about the worth of an asset compared to what

the market is willing to pay for similar assets (Damodaran 2007:59). This would imply that

there is a large degree of trust in the market for determining accurate valuations, at least on

average.

Figure 1 indicates the results of a biennual survey launched by PwC (2008:41). The

survey results confirmed that the P/E ratio is indeed the most popular multiple used in

practice in South Africa, while the MVIC/EBITDA multiple is a close second choice,

followed by the MVIC/EBIT ratio, P/BVE and P/PBT.

Figure 1 Multiples that are used most frequently in practice in South Africa

MVIC - market value of invested capital; P/CFO - price/cash flow from operations; P/CF - price/earningsplus non-cash charges; P/BVE - price/book value of equity; EBIT - earnings before interest and tax;EBITDA - earnings before interest, tax, depreciation and amortisation; P/E - price/earnings

Source: PwC (2008:41)2

Although practice seems to place the P/E ratio on a pedestal, there is little evidence from

research to support this. The superiority of the P/E ratio as a value indicator has not been

substantiated by research, especially not on a sector-specific basis. Popular belief suggests

that different sectors have different “best” multiples (Liu, Nissim & Thomas 2001:135). Ina study conducted on UK and European sectors, Fernández (2001:6) found that analysts

have a preference for certain multiples in certain sectors, which supports the notion thatdifferent multiples are suited to different sectors. A similar conclusion was drawn by

Abukari, Jog and McConomy (2000:18) in a study of equity valuation techniques based on

companies listed on the Toronto Stock Exchange.

2 The 2007 PwC survey had 25 respondents. The survey used a frequency table between 0-3, where 0

indicated that the multiple is seldom or never used, 1 indicated that the multiple is often used, 2

indicated the multiple is frequently used and 3 indicated that the multiple is always used.

- 0.50 1.00 1.50 2.00 2.50

P/E ratio

MVIC/EBITDA

MVIC/EBIT

P/BVE

P/PBT

P/CF

Other

P/CFO

MVIC/Revenue


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Four of the five multiples that form the focus of this article, the P/E ratio,MVIC/EBITDA, MVIC/EBIT and P/PBT, are based on earnings, while P/BVE is based on

book value. The main point of criticism regarding these multiples is that they are based on

accounting measures, which may be manipulated. These accounting measures, in turn, rest

on accounting rules and principles, which may be applied differently by different

companies.

The inherent flaw in the five most popular multiples is that their value drivers are based

on historical figures, that is, there is an underlying assumption that history is bound to

repeat itself. However, the purpose of an equity valuation is to determine the equity’s

worth, which by definition, should be equal to the present value of an asset’s futureearnings potential.

The P/E ratio and the P/PBT ratio are susceptible to changes in the capital structure. An

all-equity company can, for example, artificially increase these multiples by increasing its

leverage (Goedhart et al. 2005:1). Although the MVIC/EBITDA and MVIC/EBIT multiplesmay prove less susceptible to this kind of manipulation, since they include both equity and

debt, they also include operating leases, which are non-operating items. Consequently,companies with significant operating leases may have an artificially low MVIC, assuming

that the value of lease-based debt is ignored, and an artificially low EBITDA, since rental

payments include interest charges. Other limitations include the fact that EBITDA and

EBIT neglect to take changes in working capital requirements into account and do not

consider capital investments (Stumpp 2000:1).

Apart from book value, which is affected by the accounting treatment of items such as

depreciation, the P/BVE has little relevance for companies with limited tangible assets,

such as technology companies (Damodaran 2002:511).

4 Data selectionThe following variables were extracted from the McGregor BFA database: market price of

shares, preference shares, volume of ordinary shares, interest-bearing debt, headlineearnings per share, depreciation, earnings before interest and tax (EBIT), profit before tax

(PBT), ordinary shareholders’ interest and sector.

The companies were selected on the basis of three criteria: (1) all multiples are positive,

that is, multiples with negative values were discarded; (2) the companies have at least three

years of positive company year multiples; and (3) each sector 3

has at least four observations

that meet criteria (1) and (2) above. The first condition eliminates unrealistic multiples thatcannot be used. The second condition ensures that selected companies have a reasonable

history as a going concern, and the third ensures that the number of companies within each

sector is not unnecessarily small, preventing the situation where there are too few

observations to warrant a realistic mean calculation. The final population of observationsrepresents approximately 65% of the total number of listed companies on the JSE as at

31 December 2007 and approximately 82% of the market capitalisation of the companies

3The McGregor BFA sector classifications are super sector, sector, sub sector and industry. The sector

classification was used for the purpose of this analysis in order to ensure a sufficient number of

companies within each classification. Many companies’ sector classifications have changed over the

past 20 years. However, for the purpose of this analysis, companies were allocated to the sectors where

they resided as at 31 December 2007.


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listed on the JSE at the same date, which serves as a fair representation for the conclusionsdrawn.

The number of observations was different for each multiple, depending on how well the

variables compared to the criteria stipulated above. As a result, the multiples have different

population sizes, varying between 2 902 and 3 534 observations. The total population for

all the multiples includes 15 650 observations, which covered 24 sectors for the period

1988 to 2007. Although the BFA McGregor database provides information for companies

dating back to 1976, the earlier years are not well documented. Information for the years

between 1976 and 1987 was not readily available on the McGregor BFA database – hence

the years 1976 to 1987 were discarded.

The data were used to calculate the P/E ratio, MVIC/EBITDA, MVIC/EBIT, P/BVE and

P/PBT. Although the calculation of MVIC requires the inclusion of interest-bearing debt atmarket value, this information is not readily available on the McGregor BFA database –

hence the use of the book value of interest-bearing debt as a proxy. EBITDA was calculated by adding back depreciation to EBIT, since amortisation is included in depreciation on the

BFA McGregor database.

Research indicates that multiple value drivers based on earnings perform more accurate

valuations than those based on cash flows (Liu et al. 2002:23). Consequently, apart from

P/BVE, this article focuses on multiples with earnings-based value drivers. Although

P/BVE does not contain an earnings-based value driver, the PwC survey results indicated

that it is preferred over P/PBT – hence its inclusion in the analysis.

5 Research methodologyValuations based on multiples assume that the actual value (V) of a company (j) at a given

point in time (t) is equal to the product of a specific multiple (λ) and a specific value driver

(α) at that specific point in time, so thatVjt = λtαjt (1)

The aim of this research is to establish the ability of valuations based on equation (1) toapproximate actual share values. The focus is on different sectors in South Africa and

which multiples best suit each of these sectors. The methodology is the following: First, the

data, as stipulated in section 4, are extracted from the McGregor BFA database and deflated

by the average annual CPI (with 2000 as basis year) to facilitate the use of data over a wide

spectrum of years. The data are then screened according to the criteria stipulated in section

4, and observations outside of the 1st

and 99th

percentiles are removed from the pool of observations.

Next, an estimated sector multiple (Ě[λt]) is calculated for each company by calculatingthe harmonic mean

4of all the other remaining companies in the sector concerned for that

4 There seems to be a lack of consensus in academic research regarding the use of the median, arithmetic

mean or the harmonic mean as averaging procedures (Dittman & Maug 2008:2). The harmonic mean is

preferred to estimate sector multiples since several researchers argue that it avoids the upward bias of

the arithmetic mean. Baker and Ruback (1999:17) suggest that, empirically, it is closer to the minimum

variance estimates deduced from Monte Carlo simulations than the simple mean, median or value-

weighted mean. Liu et al. (2002:6) regard the harmonic mean as a viable and unbiased estimator, while

Beatty, Riffe and Thompson (1999:182) and Bhojraj and Lee (2002:416) also prefer to use the

harmonic mean.


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specific multiple. The estimated sector P/E ratio for company A, for example, in a sector that contains companies A to E, will be equal to the harmonic mean of the P/E ratios of

companies B to E. Although it may seem necessary to pursue a more diligent selection

process by also considering factors such as company size and expected growth rates,

research has indicated that these additional factors do not significantly reduce valuation

errors (Alford 1992:96).

The estimated multiple of each company (Ě[λt]), that is, the harmonic mean of the P/Eratios for companies B to E, is then multiplied by the company’s actual value driver (α j),that is, company A’s earnings, to calculate a value indicator (Vi) of the company’s shares:

Vijt =Ě[λt]αjt (2)

Subtracting equation (2) from equation (1) produces equation (3) for the calculation of ε,

the error margin (valuation error):

ε jt = Vjt - Vijt (3)

The deviation ε jt is expressed proportionally to Vjt, therefore

Vjt - Vijt

(4)

The valuation errors are calculated for each company year. Absolute valuation errors are

used since the results of dispersion measures such as the mean will be obscured if positive

and negative valuation errors are allowed to be netted. This may result in an artificially

narrow dispersion. After calculating the absolute valuation errors for each multiple and

excluding the observations that fall outside the 1st

and 99th

percentiles, the interpercentile

range (IPR) is calculated for each sector as a measure of the dispersion of the pool of

valuation errors. Comparing the IPR of each of the multiples allows for the comparison of

the five multiples per sector in an attempt to establish which multiples may be more suited

to a specific sector.

The multiples are then collated in a multiples value chain (MVC), ranking the multiples

from the widest to the narrowest dispersion per sector. The MVC indicates the potential

valuation performance enhancement as a percentage improvement (IMP) that could be

secured by choosing a multiple that performs a more accurate equity valuation, that is,

moving to a column further to the right on the MVC, and is calculated as

IPR2-IPR1

IPR2

The multiples that are preferred in practice, as obtained from the PwC survey, are then

plotted on the MVC to identify an optimisation gap, that is, the gap between those multiplesthat are preferred in practice and those with the narrowest dispersion of valuation errors.

The optimisation gap is calculated as a potential IMP in the valuation performance within a

certain sector by replacing the most popular multiple with the multiple with the lowest

dispersion.

6 ResultsThis section deals with the dispersion of valuation errors of the five most popular multiples

across various sectors. The measure used to calculate the dispersion of valuation errors is

Vjtε jt =

IMP =


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the IPR. Table 1 contains the results of the IPR calculated for each sector multiple. The 5%to 95% IPR was used as a measure of dispersion, since it eliminates the major outliers

without rendering the size of the pool of observations unnecessarily small. The valuation

errors, however, were also tested for the range 10% to 90%, the interquartile range, the

mean, median, standard deviation and variation coefficient, and all rendered similar

qualitative results. The P/E ratio is the multiple with the narrowest dispersion for between

25% and 50% of the sectors. Its position as a preferred multiple over various sectors

declines as the range approaches the interquartile range.

Although Table 1 indicates that the P/E ratio has the lowest average dispersion across the

24 sectors (1.56), this is not the case for each specific sector. If each sector is consideredseparately, the P/E ratio has the lowest sector dispersion for only eight of the 24 industries,

that is, in 33% of the sectors, followed by MVIC/EBITDA (25%), MVIC/EBIT (21%) and

P/BVE (17%), while P/PBT seems to be the best alternative in only 4% of the sectors. In all

the other sectors there is an opportunity to enhance the valuation performance by utilisinganother multiple.

Table 1 Interpercentile ranges for different sector multiples

P/E MVIC/EBITDA MVIC/EBIT P/BVE P/PBT

N IPR N IPR N IPR N IPR N IPR

Sector

Automobiles & P arts 63 1.48 69 1.45 68 1.93 63 1.99 66 2.33

Banks 117 0.82 108 1.04 111 1.55 121 1.43 112 0.76

Chemicals 77 1.35 78 0.91 78 0.93 79 2.31 75 1.54

Construction & Materials 178 1 .09 190 1.17 185 1.05 201 1.54 174 1.23

Electronic & Electrical Equipment 116 1.34 130 2.69 121 2.52 141 2.54 117 3.20

Equity Investment Instruments 99 2.60 96 2.73 96 2.76 120 1.45 89 3.37

Food & Drug Retailers 58 1.00 57 0.95 57 0.89 55 2.32 57 1.69

Food Producers 182 0.95 181 0.93 182 0.89 203 1.53 175 0.97

General Financial 183 1.91 172 2.28 169 2.42 236 2.61 170 2.36

General Industrials 120 1.97 122 1.17 121 1.35 126 1.79 117 1.61

General Retailers 235 1.06 239 1.72 238 1.54 251 1.68 227 1.48

Industrial Engineering 95 1.44 111 1.79 109 1.79 113 2.09 100 1.62

Industrial Metals 59 2.35 63 1.89 61 2.39 70 2.72 54 2.75

Industrial Transportation 116 1.89 122 2.12 121 1.70 128 2.81 110 2.18

Life Insurance 71 1.53 67 1.95 67 1.91 71 1.05 62 1.98

Media 84 1.10 79 1.56 77 1.66 95 1.97 74 1.79

Mining 319 1.70 362 1.76 351 1.80 500 2.57 338 1.97

Nonlife Insurance 70 1.04 71 1.16 69 0.97 79 0.77 70 1.22

Personal Goods 65 3.57 68 2.63 66 2.49 68 1.93 64 3.74

Real Estate 259 0.92 304 1.21 301 1.31 286 2.37 241 2.09

S of tware & Compu te r S er vi ce s 148 1.6 7 13 1 1.29 127 1.54 172 2.11 128 1.41

Support Services 139 2.04 149 1.38 145 1.49 158 1.71 138 2.23

Technology & Hardware 28 1.31 28 3.26 28 3.01 36 3.96 27 1.54Travel & Leisure 127 1.31 136 1.17 125 1.09 162 2.36 117 1.23

Total 3008 3133 3073 3534 2902

Average 1.56 1.68 1.71 2.07 1.93

Best performance: Number of sectors 8 6 5 4 1

P/E - price earnings; MVIC - market value of invested capital; EBITDA - earnings before interest, tax, depreciation andamortisation; EBIT - earnings before interest and tax; P/BVE - price/book value of equity, P/PBT - price/profit beforetax, N - number of observations; IPR - interpercentile range


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In Table 2, the IPR calculations from Table 1 are ranked from worst (IPR5) to best (IPR1) performance across 24 sectors, that is, from the widest to the narrowest dispersion. Column

IPR1 contains the multiples with the best valuation performance for each sector. Although

favoured in practice as the multiple of choice, the results clearly indicate that the P/E ratio

is not the best alternative across all sectors. The percentage potential improvement (IMP) is

shown for each move to an alternative multiple situated one column further to the right. In

the automobiles and parts sector, for example, moving from the P/E ratio (situated in

column IPR2) to MVIC/EBITDA (situated in column IPR1) may secure a 3% IMP.

Table 2 Multiples value chain: multiples ranked from the widest to the narrowest

dispersion per sector

Ranked multiple

IRP5 IMP IRP4 IMP IRP3 IMP IRP2 IMP IRP1

Sector

Automobiles & Parts P/PBT 14% P/BVE 3% MVIC/EBIT 23% P/E 3% MVIC/EBITDABanks MVIC/EBIT 8% P/BVE 27% MVIC/EBITDA 21% P/E 8% P/PBT

Chemicals P/BVE 33% P/PBT 13% P/E 31% MVIC/EBIT 2% MVIC/EBITDA

Construction & Materials P/BVE 20% P/PBT 5% MVIC/EBITDA 7% P/E 4% MVIC/EBIT

Electronic & ElectricalEquipment P/PBT 16% MVIC/EBITDA 6% P/BVE 1% MVIC/EBIT 47% P/E

Eq ui ty I nve stme nt I ns tr ume nt s P/ PBT 1 8% MVI C/E BI T 1 % M VIC /E BIT DA 4 % P/E 4 4% P/B VE

Food & Drug Retailers P/BVE 27% P/PBT 41% P/E 5% MVIC/EBITDA 7% MVIC/EBIT

Food Producers P/BVE 37% P/PBT 2% P/E 2% MVIC/EBITDA 4% MVIC/EBIT

General Financial P/BVE 7% MVIC/EBIT 3% P/PBT 3% MVIC/EBITDA 16% P/E

General Industrials P/E 9% P/BVE 10% P/PBT 17% MVIC/EBIT 13% MVIC/EBITDA

General Retailers MVIC/EBITDA 2% P/BVE 9% MVIC/EBIT 4% P/PBT 28% P/E

Industrial Engineering P/BVE 14% MVIC/EBITDA 0% MVIC/EBIT 9% P/PBT 11% P/E

Industrial Metals P/PBT 1% P/BVE 12% MVIC/EBIT 1% P/E 20% MVIC/EBITDA

Industrial Transportation P/BVE 22% P/PBT 3% MVIC/EBITDA 11% P/E 10% MVIC/EBIT

Life Insurance P/PBT 2% MVIC/EBITDA 2% MVIC/EBIT 20% P/E 31% P/BVE

Media P/BVE 10% P/PBT 7% MVIC/EBIT 6% MVIC/EBITDA 30% P/E

Mining P/BVE 23% P/PBT 9% MVIC/EBIT 2% MVIC/EBITDA 3% P/ENonlife Insurance P/PBT 5% MVIC/EBITDA 10% P/E 7% MVIC/EBIT 21% P/BVE

Personal Goods P/PBT 5% P/E 26% MVIC/EBITDA 5% MVIC/EBIT 22% P/BVE

Real Estate P/BVE 12% P/PBT 37% MVIC/EBIT 8% MVIC/EBITDA 24% P/E

Software & Computer Services P/BVE 21% P/E 8% MVIC/EBIT 8% P/PBT 9% MVIC/EBITDA

Support Services P/PBT 9% P/E 16% P/BVE 13% MVIC/EBIT 7% MVIC/EBITDA

T echn ol ogy & Ha rdwa re P/BVE 1 8% MVIC/EBITDA 8% MVIC/EBIT 49 % P/PBT 1 5% P/E

Travel & Leisure P/BVE 45% P/E 6% P/PBT 5% MVIC/EBITDA 7% MVIC/EBIT

Average 16% 11% 11% 16%

MVC - multiples value chain; IPR5-1 - interpercentile ranges ordered from the widest (IPR5) to the narrowest (IPR1)dispersion; IMP - percentage potential improvement; P/E - price earnings; MVIC - market value of invested capital;EBITDA - earnings before interest, tax, depreciation and amortisation; EBIT - earnings before interest and tax; P/BVE -price/book value of equity; P/PBT - price/profit before tax

The discussion of the results will focus on each multiple’s best valuation performance. For

each sector, the actual multiple of choice that is applied in practice, that is, the P/E ratio, is

compared with the multiple with the best valuation performance in that particular sector.The former will be based on the results of the PwC survey, while the latter will be based on

the results of the IPR calculated for each sector multiple, as contained in Table 2.

6.1 P/E

The P/E ratio indicates the best valuation performance in the electronic and electrical

equipment, general financial, general retailers, industrial engineering, media, mining, realestate, and technology and hardware sectors. In total, P/E ratios perform the best valuations


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in 33% of the sectors, which is the best performance in aggregate, compared with the other four multiples.

These results are supported by the PwC survey, which, although not sector specific,

indicated that the P/E ratio is the most popular multiple used in practice, scoring a 2 ontheir frequency table. However, as the IPR results indicate, the P/E ratio does not perform

the most accurate equity valuations, that is, with the lowest dispersion of valuation errors,

across all sectors.

By plotting the preferred multiples currently applied in practice, in other words, the

practical multiple of choice (PMC) in these eight sectors on the MVC, an opportunity cost

for these multiples can be calculated. The opportunity cost of any multiple on the MVCwould be the foregone potential IMP as a result of not using the multiple in column IPR1 in

Table 2, that is, the research multiple of choice (RMC). Since the P/E ratio is the PMC and

the RMC for each of these eight sectors, the opportunity cost figure is zero – in other

words, the multiple used in practice corresponds to the multiple suggested by the researchresults.

6.2 MVIC/EBITDA

MVIC/EBITDA indicates the best valuation performance in the automobiles and parts,

chemicals, general industrials, software and computer services, support services and

industrial metals sectors. MVIC/EBITDA performs the best valuations in 25% of the

sectors, which indicates that it is probably one of the better options when choosing a

multiple for equity valuation purposes, especially if it is for equity valuations in the above-

mentioned six sectors.

These results concur with the frequency with which the MVIC/EBITDA is applied in

practice, since the PwC survey indicated that it is the second most popular multiple that is

applied in practice, scoring a 1.75 on their frequency table. As Table 3 indicates, the potential IMP is 3% in the automobiles and parts sector, 32% in the chemicals sector, 41%

in the general industrials sector, 23% in the software and computer services sector, 32% inthe support services sector and a 20% in the industrial metals sector.

Table 3 contains the IPRs of the PMC and the RMC. The PwC survey indicated that the

PMC is the P/E ratio. The IPRs of the P/E ratio for each sector are therefore indicated in the

first column, labelled PMC. The IPR of the RMC for each sector was calculated and is

indicated in the column labelled RMC, that is, those multiples with the smallest dispersion

of valuation errors. The multiple description is included under the label “Multiple”. The potential IMP between the PMC and the RMC in each sector illustrates the optimisation

gap, which indicates the 16 sectors in which the P/E ratio was outperformed by one of the

other four preferred multiples. As Table 3 indicates, there is a 22% average potential

performance improvement in the accuracy of valuations, ranging from 3% in the

automobiles and parts sector to 46% in the personal goods sector.


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Table 3 Optimisation gap: sectors in which the P/E ratio is outperformed by othermultiples

Optimisation gap

PMC RMC Multiple IMP

Sector

Automobiles & Parts 1.48 1.45 MVIC/EBITDA 3%

Banks 0.82 0.76 P/PBT 8%

Chemicals 1.35 0.91 MVIC/EBITDA 32%

Construction & Materials 1.09 1.05 MVIC/EBIT 4%

Equity Investment Instruments 2.60 1.45 P/BVE 44%

Food & Drug Retailers 1.00 0.89 MVIC/EBIT 12%

Food Producers 0.95 0.89 MVIC/EBIT 6%

General Industrials 1.97 1.17 MVIC/EBITDA 41%

Industrial Metals 2.35 1.89 MVIC/EBITDA 20%Industrial Transportation 1.89 1.70 MVIC/EBIT 10%

Life Insurance 1.53 1.05 P/BVE 31%

Nonlife Insurance 1.04 0.77 P/BVE 26%

Personal Goods 3.57 1.93 P/BVE 46%

Software & Computer Services 1.67 1.29 MVIC/EBITDA 23%

Support Services 2.04 1.38 MVIC/EBITDA 32%

Travel & Leisure 1.31 1.09 MVIC/EBIT 16%

Average 1.67 1.23 22%

PMC - practical multiple of choice; RMC - research multiple of choice; IMP - percentage potential improvement; P/E -price earnings; MVIC - market value of invested capital; EBITDA - earnings before interest, tax, depreciation andamortisation; EBIT - earnings before interest and tax; P/BVE - price/book value of equity; P/PBT - price/profit before tax

6.3 MVIC/EBIT

MVIC/EBIT indicated the best valuation performance in the construction and materials,

food producers, industrial transportation, travel and leisure, and food and drug retailers

sectors. MVIC/EBIT performs the best valuations in 21% of the sectors, which indicates

that, although it is not the most popular multiple across the board, it outperforms P/BVE

and P/PBT.

These results concur with the frequency with which MVIC/EBIT is applied in practice,since the PwC survey indicates it as the third most popular multiple method, scoring

approximately 1.35 on their frequency table. The potential IMP in the accuracy of

valuations is 4% in the construction and materials sector, 6% in the food producers sector,

10% in the industrial transportation sector, 16% in the travel and leisure sector and 12% in

the food and drug retailers sector.

6.4 P/BVE P/BVE indicated the best valuation performance in the equity investment instruments, life

insurance, nonlife insurance and personal goods sectors. P/BVE performs the best

valuations in 17% of the sectors, which indicates that it is not the best option when

choosing a multiple for equity valuation purposes, unless it is for equity valuations in the

above-mentioned four sectors.


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These results concur with the frequency with which P/BVE is applied in practice, sincethe PwC survey indicates it as the fourth most popular multiple method, scoring 0.75 on

their frequency table. The potential IMP in the accuracy of valuations is 44% in the equity

investment instruments sector, 31% in the life insurance sector, 26% in the nonlife

insurance sector and 46% in the personal goods sector.

6.5 P/PBT

P/PBT indicated the best valuation performance in the banking sector, that is, in 4% of the

sectors, which indicates that it is not the best option when choosing a multiple for equity

valuation purposes, unless it is for equity valuations in the banking sector.

These results concur with how frequently the P/PBT is applied in practice, since the PwC

survey indicated it as the least popular multiple of the top five multiples that are applied in

practice, scoring 0.5 on their frequency table. The potential IMP in the accuracy of valuations is 8% in the banking sector.

The results therefore contrast the evidence from practice, which indicated that the P/Eratio is the PMC, as suggested by the results of the PwC survey. The IPR calculations

contained in Table 2 indicate that the P/E ratio is the optimal multiple, that is, with a zero

optimisation gap, in only 33% of the sectors. The other four preferred multiples top the list

of best valuation performance for the remaining 67% of the sectors, which suggests that the

P/E ratio is not the best alternative across all sectors.

7 ConclusionThe primary focus of this article was to investigate whether the general preference for the

P/E ratio in practice matches the sector multiples that research seems to suggest. It was

shown that the P/E ratio, although widely advocated in academic circles and applied in practice as the kingpin of multiples, is not the best multiple option across all sectors. The

research results supported the notion that different multiples should be used for different

sectors. This was evident from the optimisation gap, which approximated the potential

performance improvement that may be achieved in the accuracy of equity valuations.

After the data were extracted from the McGregor BFA database and screened, an

estimated sector multiple was calculated for each company by calculating the harmonic

mean of all the remaining companies in the industry concerned. The estimated multiples

were multiplied by the company’s specific value driver to arrive at a value indicator for the

company’s shares. The difference between these value indicators and the actual share

values was subsequently calculated to create a pool of valuation errors. The dispersion of

the pool of valuation errors for each multiple was measured for each sector by calculating

the IPR. The IPRs of each of the five most popular multiples in practice (per sector) were

compared, in an attempt to establish which multiples may be more suited to a specificsector. To this end, an MVC was created, ranking the multiples from the widest to the

narrowest dispersion of valuation errors per sector, indicating the potential valuation

performance enhancement that could be achieved by choosing a multiple that performs a

more accurate equity valuation.

The results should be considered with caution. The research depended on the availability

of data, and clinical calculations such as the harmonic mean were used. Although the

clinical selection of comparable companies may erode the performance of multiples,


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especially when using a large data pool, this should not detract from the relative performance amongst multiples since all multiples were selected in a similar fashion.

Clearly, analysts may follow a more careful selection process and take into account specific

factors that were not considered in this research exercise.

The research indicates the following: Firstly, as was evident from the results of the PwC

survey, the P/E ratio is the preferred multiple that is used in practice. However, the results

of the research revealed that the P/E ratio performs the most accurate equity valuation in

only 33% of the sectors, indicating that it is not the most optimal multiple in all the sectors.

The reader should again consider these results with caution since a reduction in the IPR

from 5% to 95%, which was used for the research analysis, to the interquartile range, for

example, causes the P/E ratio’s position as the optimal multiple to decline to only 25% of

the sectors. However, for all the different measures of dispersion that were tested, the

results indicated that a carte blanche application of the P/E ratio across all sectors is ill

advised.

Secondly, the results of the IPR calculations indicate that each of the five most popular

multiples, as per the PwC survey, outperforms the other four in certain sectors. It is

therefore evident that different multiples should be used for different sectors, as indicated

by the optimisation gap, which was calculated for each of the 16 sectors in which a multiple

other than the P/E ratio was found to perform the most accurate equity valuations. To this

end, the valuation performance of the P/E ratio was pitted against that of the best

performing sector multiple in these 16 sectors. The results indicate that by substituting the

P/E ratio for one of the other four preferred multiples in these sectors, the accuracy of the

valuations can be improved by between 3 and 46%.

What are the implications? Finance lecturers in academia generally proclaim that the P/E

ratio is the most widely used multiple in practice – and rightly so. However, the P/E ratio is

not the most accurate multiple per se, since it does not necessarily constitute best practiceacross all sectors. The academic environment would do well to take cognisance of these

results and present the P/E ratio with the necessary caution to their students. Although, in

practice, analysts do not view multiples in isolation, but rather consider a range of

multiples, and usually in conjunction with more comprehensive models, the evidence does

suggest that there is a somewhat large, probably unwarranted, emphasis on the P/E ratio.

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