finexpert report capital market data · It also contains Q1 2014 capital market data from our website including industry betas, cost of capital and our estimate for the German risk-free

finexpert report capital market data

03 | 2014 Volume 4

Content

1 Preface & People

3 Multiples: Procedure & How to read our charts

4 Multiples: EV/EBIT

12 Multiples: EV/EBITDA

20 Multiples: EV/Sales

23 Multiples: P/E

32 Multiples: P/Sales

35 CAPM Beta Factors

37 Term Structure of listed German Federal Securities

38 Current Research: Inorganic Growth Strategies in Private Equity

finexpert | capital market data | Vol. 4

Dear finexpert members,

we are pleased to release the Q1 2014 finexpert capital market data update. Our current issue focuses on the development of trailing and forward EV/EBIT, EV/EBITDA, EV/Sales, P/E and P/Sales multiples. It also contains Q1 2014 capital market data from our website including industry betas, cost of capital and our estimate for the German risk-free yield curve (Svensson). Finally, the research corner - section presents a recent working paper from our chair dealing with add-on acquisitions of Private Equity Sponsors. Please note that we have slightly changed the structure and timing of our PE corner; it will appear from now in semi-annual sequence.

Preface

Sincerely yours,

Prof. Dr. Bernhard Schwetzler,

Chair of Financial Management

HHL - Leipzig Graduate School of Management

1


People

Jun.-Prof. Dr. Alexander Lahmann Capital market data, Yield Forecasts Research Interests: Asset Pricing & Corporate Valuation E-mail: [email protected]

Johanna Stein, cand. B.Sc. Technical editing, Current Research Research Interests: Mathematical & Financial Economics

Benjamin Hammer, M.Sc. Capital Market Data, Current Research Research Interests: Private Equity, Entrepreneurial Finance E-mail: [email protected]

Daniel Schönekäs, B.A. Technical editing Research Interests: Applied Econometrics and Financial Economics

2


We estimated industry multiples based on industry indices provided by Deutsche Börse AG

Time frame: January 2009 – January 2014

We calculated trailing and 1 year forward EV/EBIT, EV/EBITDA, EV/Sales, P/E, P/Sales

Earning estimates for forward-multiples have been taken from I/B/E/S

Data bases on quarterly estimates; Industry composition changes over time

In each estimation period we excluded outliers multiples beyond the limit of the upper 5%-quantile

Multiples: Procedure

Multiples: How to read our Charts

In the following charts you will find forward multiples (blue) and trailing mutiples (green) combined in one chart.

3


Analysis

Year-on-year (y-o-y) comparison of the median EV/EBIT multiples1 shows considerably improved valuation of the Prime All Share Standard (from 11.3x to 13.8x). In part, this holds also true for the most important sub-indices, among which the TecDAX 30 exhibits the by far highest y-o-y increase (from 12.4x to 17.9x). DAX30 (from 13.3x to 14.4x) and MDAX50 (from 13.5x to 14.8x) display smaller but still significant valuation gains. On industry level, the y-o-y comparison draws a familiar picture: the highest EV/EBIT multiple still appears in the Telecommunication industry (last year 15.7x vs. current year 26.9x); the lowest one in the Food & Beverages Branch (last year 6.2x vs. current year 3.2x). Interesting is the significant dispersion among the current EV/EBIT multiples in the Telecommunication sector. While companies such as Drillisch (44.1x)

or Telefonica Deutschland (49.5x) have rather high EV/EBIT valuations, others such as Telegate (0.3x) show very low ones. Such high dispersion also leads to differing industry multiples for different aggregation methods: using the harmonic mean for aggregation, for example, yields a Telecommunication industry multiple of just 1.5x, being substantially lower than the multiples basing on the arithmetic mean or median2. This should be taken into account when applying the aggregate industry multiple for valuation purposes. Besides the telecommunication industry, many other branches have gained in valuation too, most notably the sectors basic resources (from 7.5x to 15.8x)3, technology (from 7.8x to 13.8x) and software (from 10.9x to 16.0x). The opposite holds true for only few branches. The only considerable decline in EV/EBIT valuation is apparent in the food & beverages industry (from 6.2x to 3.2x).

Multiples: EV/EBIT

Executive Summary

EV/EBIT multiples have predominantly increased since last year; only exception is the food & beverages industry

Significant increase especially in technology and software industry

EBIT growth expectations are predominantly positive, except for the food & beverages industry again

1 Respective due dates are January 15, 2013 and 2014

2 Among the presented aggregation methods, the harmonic mean is generally the most conservative one. It mitigates the impact of large outliers but augments the impact of small ones.

3 Please note that both the basic resources trailing and forward multiple traditionally base on very few data points so that small changes in sector composition or data availability can sig-nificantly affect the aggregated industry multiple

4


When looking at the quarterly4 development since last year, some of the y-o-y changes seem rather exceptional. In the basic resources industry, for example, we observe a remarkably high compounded annual growth rate (CAGR) of roughly 21% since last year. This growth rate is predominantly driven by the recent valuation increase from Q4 2013 to Q1 2014 (from 7.0x to 15.8x); during the first three quarters of 2013, however, the EV/EBIT multiple in the basic resources branch even declined twice. A more sustainable, yet smaller, valuation increase is the case for the technology branch (CAGR 15%) where the EV/EBIT multiple increased consistently since Q1 2013. Remarkable is also the very flat EV/EBIT development in the construction (variance = 0.16), industrials (variance = 0.25) and utilities sector (variance = 0.27).

Comparing the current trailing and forward EV/EBIT multiples allows for conclusions about EBIT growth expectations: lower forward than trailing multiples indicate optimistic EBIT projections. Accordingly, the outlook is positive for the Prime All Share Standard (Trailing 13.8x vs. Forward 13.5x) and its most important sub-indices, the DAX30

(Trailing 14.4x vs. Forward 13.9x), TecDAX30 (Trailing 17.9x vs. Forward 17.8x) and MDAX50 (Trailing 14.8x vs. Forward 13.2x). Several industries exhibit positive growth expectations too, for example the sectors telecommunication (Trailing 26.9x vs. Forward 13.0x), basic resources (Trailing 15.8x vs. Forward 12.4x), and utilities (Trailing 11.8x vs. Forward 9.6x). Lower trailing than forward multiples in the food & beverages (Trailing 3.2x vs. Forward 4.6x) and retail industry (Trailing 10.4x vs. Forward 11.8x) indicate pessimistic growth expectations though.

For the analysis of the trailing and forward EV/EBIT multiples we used cut off values of 51.13x and 58.42x, respectively, to avoid bias through outliers. Both values equal the upper 5% quantile. This led to the exclusion of 11 out of 213 companies for the trailing multiple and 11 out of 209 for the forward multiple. Last year’s cut-off values have been 40.28x and 36.56x, respectively, which led to the exclusion of 13 out of 233 companies for the trailing multiple and 14 out of 222 for the forward multiple.

Multiples: EV/EBIT

4 Respective due dates are: January 15, 2013 (Q1 2013), April 15, 2013 (Q2 2013), July 15, 2013 (Q3 2013), October 15, 2013 (Q4 2013) and January 15, 2014 (Q1 2014).

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finexpert | capital markets data | Vol. 4

Development of Multiples EV/EBIT - Indices

Fig. 1: EV/EBIT - Prime All Share

Fig. 2: EV/EBIT - DAX 30

Fig. 3: EV/EBIT - TecDax30

Fig. 4: EV/EBIT - MDAX 50

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Jan‐09 Jul‐09 Jan‐10 Jul‐10 Jan‐11 Jul‐11 Jan‐12 Jul‐12 Jan‐13 Jul‐13 Jan‐14

Multiples ‐ Prime All Share

EV/EBIT +SD EV/EBIT ‐SD EV/EBIT EV/EBIT 1YF +SD EV/EBIT 1YF ‐SD EV/EBIT 1YF

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Multiples ‐ TecDAX 30


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7


Development of Multiples EV/EBIT - Per Industry I/IV

Fig. 5: EV/EBIT - Automobiles

Fig. 6: EV/EBIT - Basic Resources

Fig. 7: EV/EBIT - Chemicals

Fig. 8: EV/EBIT - Construction

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Multiples ‐ Construction


8


Development of Multiples EV/EBIT - Per Industry II/IV

Fig. 9: EV/EBIT - Consumer

Fig. 10: EV/EBIT - Industrial

Fig. 11: EV/EBIT - Media

Fig. 12: EV/EBIT - Pharma & Healthcare

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Multiples ‐ Pharma


9


Development of Multiples EV/EBIT - Per Industry III/IV

Fig. 13: EV/EBIT - Retail

Fig. 14: EV/EBIT - Software

Fig. 15: EV/EBIT - Technology

Fig. 16: EV/EBIT - Telecommunication

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Development of Multiples EV/EBIT - Per Industry IV/IV

Fig. 17: EV/EBIT - Transport & Logistics

Fig. 18: EV/EBIT - Utilities

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Multiples ‐ Transportation


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Multiples ‐ Utilities


11


Analysis

Year-on-year (y-o-y) comparison of the median EV/EBITDA multiples1 confirms the results of the EV/EBIT analysis: operating valuations have improved since last year (Prime All Share Standard from 6.9x to 9.0x). For some of the major sub-indices, valuation improvements are even greater, e.g. for the DAX30 (from 7.6x to 8.6x) and MDAX50 (from 8.6x to 10.7x). The valuation gain of the TecDAX30 (from 9.3x to 11.9x) is less pronounced but still remarkable. On industry level, the software industry (12.0x) has the highest multiple whereas the food & beverages branch (2.5x) exhibits the lowest one. The telecommunication sector (6.2x) is among the industries with the lowest EV/EBITDA valuation too, being in sharp contrast to the results of the EV/EBIT analysis where it displayed both the currently highest multiple

and one of the largest y-o-y gains. These differences show how even two operating multiples can yield contradicting valuation results depending on the specifics of the industry. Other industries such as automobiles or software display almost similar developments though. The basic resources (from 5.0x to 9.1x)2, consumer (from 6.1x to 10.5x), and pharma & healthcare industries (from 11.2x to 11.6x) show the largest relative gains in EV/EBITDA valuation, mainly driven by Salzgitter (from 6.0x to 9.0x), Puma (from 7.8x to 16.9x) and Geratherm Medical (from 6.8x to 12.1x), respectively. The food & beverages (from 4.9x to 2.5x), construction (from 7.3x to 6.4x)3 and utilities sectors (from 7.2x to 6.4x), in contrast, show the largest y-o-y declines, mainly driven by Haikui Seafood (from 2.0x to 0.1x), Hochtief (from 5.5x to 3.7x) and Eon (from 16.6x to 6.1x).

Multiples: EV/EBITDA

Executive Summary

EV/EBITDA valuations have improved since last year

The quarterly development of EV/EBITDA since Q1 2013 shows consistency

EBITDA growth expectations are rather conservative

1 Respective due dates are January 15, 2013 and 2014.

2 Please note that both the basic resources trailing and forward multiple traditionally base on very few data points so that small changes in sector composition or data availability can sig-nificantly affect the aggregated industry multiple.

3 Please note that both the construction trailing and forward multiple traditionally base on very few data points so that small changes in sector composition or data availability can signifi-cantly affect the aggregated industry multiple.

12


A closer look at the quarterly development since Q1 2013 reveals that the pharma & healthcare industry has long had the highest EV/EBITDA multiple, losing its spot in Q1 2014 for the first time to the software industry. Interesting is also that many industries have slightly improved (e.g. automobiles, technology) or kept up (e.g. telecommunication) their valuation since Q1 2013 without great fluctuation. The dispersion among the EV/EBITDA multiples over the past quarters4 is therefore smaller than among the EV/EBIT multiples. The construction sector is the only industry with consistent EV/EBITDA decline since Q1 2013. Other industries with y-o-y decline have either lost in valuation just recently (e.g. food & beverages) or have already started to rebound from lower valuations (e.g. utilities).

Comparing the current trailing and forward multiples allows for analyzing expected EBITDA development. Accordingly, growth expectations are almost unchanged for the Prime All Share (Trailing 9.0x vs. Forward 8.9x), and DAX30 (Trailing 8.6x vs. Forward 8.7x).

Far more optimistic is the outlook for the TecDAX30 (Trailing 11.9x vs. Forward 11.3x), MDAX50 (Trailing 10.7x vs. Forward 9.6x) and some industries, e.g. pharma & healthcare (Trailing 11.6x vs. Forward 10.1x) or utilities (Trailing 6.4x vs. Forward 5.7x). There are also several industries with negative EBITDA growth expectations, most notably the sectors food & beverages (Trailing 2.5x vs. Forward 3.3x), retail (Trailing 7.5x vs. Forward 9.2x) and construction (Trailing 6.4x vs. Forward 7.6x).

For the analysis of the trailing and forward EV/EBITDA multiples we used cut off values of 27.19x and 25.93x, respectively, to avoid bias through outliers. Both values equal the upper 5% quantile. This led to the exclusion of 12 out of 223 companies for the trailing multiple and 11 out of 218 for the forward multiple. Last year’s cut-off values have been 18.32x and 16.01x, respectively, which led to the exclusion of 14 out of 244 companies for the trailing multiple and 14 out of 227 for the forward multiple.

Multiples: EV/EBITDA


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Development of Multiples EV/EBITDA - Indices

Fig. 19: EV/EBITDA - Prime All Share

Fig. 20: EV/EBITDA - DAX 30

Fig. 21: EV/EBITDA - TecDAX 30

Fig. 22: EV/EBITDA - MDAX 50

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EV/EBITDA +SD EV/EBITDA ‐SD EV/EBITDA EV/EBITDA 1YF +SD EV/EBITDA 1YF ‐SD EV/EBITDA 1YF

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Jan‐08 Jul‐08 Jan‐09 Jul‐09 Jan‐10 Jul‐10 Jan‐11 Jul‐11 Jan‐12 Jul‐12 Jan‐13 Jul‐13 Jan‐14



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Development of Multiples EV/EBITDA - Per Industry I/IV

Fig. 23: EV/EBITDA - Automobiles

Fig. 24: EV/EBITDA - Basic Resources

Fig. 25: EV/EBITDA - Chemicals

Fig. 26: EV/EBITDA - Construction

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Development of Multiples EV/EBITDA - Per Industry II/IV

Fig. 27: EV/EBITDA - Consumer

Fig. 28: EV/EBITDA - Industrial

Fig. 29: EV/EBITDA - Media

Fig. 30: EV/EBITDA - Pharma

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Development of Multiples EV/EBITDA - Per Industry III/IV

Fig. 31: EV/EBITDA - Retail

Fig. 32: EV/EBITDA - Software

Fig. 33: EV/EBITDA - Technology

Fig. 34: EV/EBITDA - Telecommunication

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Jan‐09 Apr‐09 Jul‐09 Oct‐09 Jan‐10 Apr‐10 Jul‐10 Oct‐10 Jan‐11 Apr‐11 Jul‐11 Oct‐11 Jan‐12 Apr‐12 Jul‐12 Oct‐12 Jan‐13 Apr‐13 Jul‐13 Oct‐13 Jan‐14



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Development of Multiples EV/EBITDA - Per Industry IV/IV

Fig. 35: EV/EBITDA -Transportation

Fig. 36: EV/EBITDA - Utilities

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Executive Summary

TecDAX30 shows largest year-on-year EV/Sales increase and most optimistic sales growth expectations

Automobiles industry with largest y-o-y EV/Sales increase; food & beverages branch with largest y-o-y decline

Pharma & healthcare industry with highest EV/Sales valuation for all quarters since Q1 2013

Multiples: EV/Sales

Analysis

At first glance, year-on-year (y-o-y) analysis shows almost similar median EV/Sales multiples1: neither the Prime All Share Standard (from 0.8x to 0.9x), nor the DAX30 (from 1.2x to 1.4x) or MDAX50 (from 0.9x to 1.0x) exhibit significant changes in EV/Sales valuation. Only the TecDAX30 multiple shows substantial improvement (from 1.2x to 1.8x), confirming the results from the EV/EBIT and EV/EBITDA analysis. On industry level, the pharma & healthcare industry (1.8x) has the highest EV/sales valuation; the basic resources sector (0.4x) has the lowest one. The automobile industry displays the largest relative increase since last year (from 0.8x to 1.1x), mainly due to substantially improved multiples of Leoni (from 0.3x to 0.6x), Continental (from 0.8x to 1.2x) and SHW (from 0.6x to 0.9x). The opposite holds true for the food & beverages branch exhibiting the largest relative decline

(from 0.8x to 0.4x). Responsible for that have been the decreases of the Hakui Seafood (from 0.5x to 0.02x) and Südzucker (from 1.1x to 0.8x) multiples.

The spread between the minimum and maximum EV/Sales multiples is small. This holds true across both industries as well as quarters. Even small changes in valuation can therefore change the rank order of the different industries with the lowest or highest multiple. Since Q1 2013, for example, the industry with the lowest EV/Sales multiple has changed every quarter (transportation & logistics in Q1 2013 with 0.4x, basic resources in Q2 2013 with 0.4x, retail in Q3 2013 with 0.4x, food & beverages in Q4 2013 with 0.5x and currently basic resources with 0.4x)2. In light of these rather frequent changes, it is remarkable that the pharma & healthcare industry has consistently had the highest multiple among all industries since Q1 2013.

1 Respective due dates are January 15, 2013 and 2014.


20


A comparison of the current trailing and forward multiples confirms the conclusions from the y-o-y analyses: the TecDAX30 shows the only significant difference between trailing (1.8x) and forward multiple (1.5x) indicating positive sales growth expectations. Close-to-zero differences are the case for the Prime All Share Standard, DAX30 and MDAX50. In line with this, few industries exhibit very positive or negative growth outlook. Worth mentioning are only the optimistic sales projections for the telecommunication industry (trailing 0.8x vs. forward 0.4x) and the rather pessimistic growth projections for the transportation & logistics sector (trailing 0.5x vs. forward 0.7x).

For the analysis of the trailing and forward EV/Sales multiples we used cut off values of 5.25x and 4.63x, respectively, to avoid bias through outliers. Both values equal the upper 5% quantile. This led to the exclusion of 13 out of 259 companies for the trailing multiple and 13 out of 244 for the forward multiple. Last year’s cut-off values have been 3.65x and 3.11x, respectively, which led to the exclusion of 16 out of 273 companies for the trailing multiple and 15 out of 252 for the forward multiple.

Multiples: EV/Sales

21


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22


Executive Summary

Year-on-year analysis reveals positive overall market development

P/E ratio of Prime All Share Standard has continuously improved since Q1 2013

Forward multiples indicate positive earnings growth expectations for the overall market and the major sub-indices

Multiples: P/E

Analysis Year-on-year (y-o-y) comparison of the median P/E multiples1 reveals a very positive overall market development (Prime All Share Standard from 15.0x to 20.2x), from which all the major sub-indices could clearly benefit (DAX30 from 14.9x to 20.2x; TecDAX30 from 16.9x to 26.4x; MDAX50 from 17.5x to 21.5x). Within this positive market environment, the transportation & logistics multiple stands out with the currently highest valuation on industry level (25.5x). The food & beverages branch exhibits the lowest P/E multiple (5.9x). Relative to the previous year, the banking industry provides the highest P/E increase, although this increase is difficult to interpret due to the very small number of available firms in this Prime All Share sub-index and the reduced data availability since last year2. More reliable are the increases of the transportation &

logistics (from 15.9x to 25.5x), and technology (from 14.7x to 23.5x) multiples, which are mainly driven by improved valuations of Fraport (from 14.9x to 25.5x) and Paragon (from 7.1x to 27.1x), respectively. The telecommunication industry shows the largest y-o-y decline (from 14.8x to 7.0x). This decline is mainly caused by the substantially reduced P/E multiple of Telefonica Deutschland (from 45.4x to 5.6x).

Compared to the rather stable EV-multiples, the P/E ratio fluctuates generally much more across industries and also over time. Static y-o-y comparisons can therefore be misleading. The TecDAX30 index, for example, exhibits a compounded annual growth rate (CAGR) of roughly 12% from Q1 2013 (16.9x) to Q1 2014 (26.4x) although the P/E ratio even reduced to 14.8x in the meantime (Q3 2013).

1 Respective due dates are January 15, 2013 (Q1 2013) and 2014 (Q1 2014).

2 The current banks multiple solely bases on the valuation of Aareal Bank.

23


Nevertheless, few examples for continuous improvement (e.g. automobiles, banks, industrials) are still available and the Prime All Share Standard itself is probably the best example (Q1 2013: 15.0x; Q2 2013: 15.3x; Q3 2013: 15.8x; Q4 2013: 17.1x; Q1 2014: 20.2x)3. A continuous P/E decline since Q1 2013 is not observable for any industry, which is not surprising though given the overall positive market development.

The current P/E forward multiples are below the respective trailing multiples for the Prime All Share Standard (Trailing 20.2x vs. Forward 17.9x), DAX30 (Trailing 20.2x vs. Forward 17.6x), TecDAX30 (Trailing 26.4x vs. Forward 24.9x) and MDAX50 (Trailing 21.5x vs. Forward 19.5x) indicating positive earnings growth expectations for the overall market and its major sub-indices. Many industry indices exhibit similarly positive or even better expectations too, for example basic resources (Trailing 20.2x vs. Forward 11.9x)4, utilities (Trailing 15.9x vs. Forward 11.6x)5,

transportation & logistics (Trailing 25.5x vs. Forward 19.6x) as well as technology (Trailing 23.5x vs. Forward 18.5x). Although there are few branches with negative earnings growth expectations, these few branches largely display forward multiples that are far above the trailing ones. This is especially the case for the telecommunication (Trailing 7.0x vs. Forward 14.0x) and food & beverages industry (Trailing 5.9x vs. Forward 7.9x).

For the analysis of the trailing and forward P/E multiples we used cut off values of 104.45x and 57.69x, respectively, to avoid bias through outliers. Both values equal the upper 5% quantile. This led to the exclusion of 12 out of 231 companies for the trailing multiple and 13 out of 244 for the forward multiple. Last year’s cut-off values have been 65.05x and 40.30x, respectively, which led to the exclusion of 12 out of 239 companies for the trailing multiple and 13 out of 253 for the forward multiple.

Multiples: P/E


4 Please note that both the basic resources trailing and forward multiples traditionally base on very few data points so that small changes in sector composition or data availability can significantly affect the aggregated industry multiple

5 Please note that both the utilities trailing and forward multiples traditionally base on very few data points so that small changes in sector composition or data availability can significantly affect the aggregated industry multiple.

24


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Development of Multiples P/E - Indices

Fig. 37: P/E - Prime All Share

Fig. 38: P/E - DAX 30

Fig. 39: P/E - TecDAX 30

Fig. 40: P/E - MDAX 50

0

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26


Development of Multiples P/E - Per Industry I/V

Fig. 41: P/E - Automobiles

Fig. 42: P/E - Consumer

Fig. 43: P/E - Basic Resources

Fig. 44: P/E - Chemicals

0

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Multiples ‐ Banks


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27


Development of Multiples P/E - Per Industry II/V

Fig. 45: P/E - Construction

Fig. 46: P/E - Consumer

Fig. 47: P/E - Financial Services

Fig. 48: P/E - Industrial

‐10

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Development of Multiples P/E - Per Industry III/V

Fig. 49: P/E - Insurance

Fig. 50: P/E - Media

Fig. 51: P/E - Pharma

Fig. 52: P/E - Retail

0

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29


Development of Multiples P/E - Per Industry IV/V

Fig. 53: P/E - Software

Fig. 54: P/E - Technology

Fig. 55: P/E - Telecommunication

Fig. 56: P/E - Transportation & Logistics

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Development of Multiples P/E - Per Industry V/V

Fig. 57: P/E - Utilities

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31


Executive Summary

Substantially increased overall market valuation

Financial services (construction) industry with highest (lowest) P/Sales valuation for every quarter since Q1 2013

Very optimistic sales growth expectations for the retail sector; very pessimistic ones for the banks and financial services industries

Multiples: Price/Sales

Analysis

Year-on-year (y-o-y) comparison of the median P/Sales multiples1

reveals substantially increased valuation of the Prime All Share Standard (from 0.7x to 0.8x), DAX30 (from 0.7x to 0.9x), TecDAX30 (from 1.5x to 1.9x) and MDAX50 (from 0.8x to 1.0x) although, overall, the relative valuation gains are smaller than those obtained from the P/E analysis. The construction (0.2x)2 and financial services industry (2.3x) exhibit the currently lowest and highest valuation, which is contrary to the P/E analysis where food & beverages as well as transportation & logistics displayed the lowest and highest multiples. The largest y-o-y increase is observed in the telecommunication industry (from 0.7x to 1.0x) whereas the food & beverages branch exhibits the largest y-o-y decline (from 0.7x to 0.4x). Compared to the results of the P/E analysis, especially the

remarkable increase of the telecommunication multiple stands out3. The different conclusions result from different data availability though: for the P/Sales multiple, data is available for the entire sub-index whereas the P/E ratio only bases on a subset of telecommunication shares. The same subset of shares would have yielded a decline in telecommunication P/Sales multiple too. P/Sales multiples are generally more stable than P/E ratios thus showing smaller fluctuation across industries and over time. The financial services industry, for example, has consistently showed the highest P/Sales multiple since Q1 2013 with a variance of just 0.07. The fact that a variance of just 0.07 constitutes the largest one across all industries over the same time span4 underpins the stability of the P/Sales multiple. Similarly, the construction sector has consistently displayed the smallest valuation since Q1 2013.

1 Respective due dates are January 15, 2013 (Q1 2013) and 2014 (Q1 2014).

2 Please note that both the construction trailing and forward multiple traditionally base on very few data points so that small changes in sector composition or data availability can significantly affect the aggregated industry multiple.

3 The P/E analysis shows the largest y-o-y decline for the telecommunication industry.


32


Some industries, e.g. the technology or insurance sector, even show close-to-zero fluctuation.

A comparison of the current trailing and forward multiples yields ambiguous results. While it indicates slightly positive sales growth expectations for the TecDAX30 (trailing 1.9x vs. forward 1.8x), growth expectations are slightly negative for the DAX30 (trailing 0.9x vs. forward 1.0x) and the Prime All Share Standard (trailing 0.8x vs. forward 0.9x). There is no significant difference between the MDAX50 trailing and forward multiple. On industry level, the very optimistic growth expectations for the retail sector stand out (trailing 0.8x vs. forward 0.4x). The banks (trailing 0.8x vs. forward 1.7x) and financial

services industry (trailing 2.3x vs. forward 3.3x) show pessimistic sales growth expectations.

For the analysis of the trailing and forward P/E multiples we used cut off values of 6.83x and 6.84x, respectively, to avoid bias through outliers. Both values equal the upper 5% quantile. This led to the exclusion of 16 out of 306 companies for the trailing multiple and 15 out of 291 for the forward multiple. Last year’s cut-off values have been 6.18x and 5.18x, respectively, which led to the exclusion of 16 out of 316 companies for the trailing multiple and 12 out of 293 for the forward multiple.

Multiples: Price/Sales

33


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36


Term Structure of listed German Federal Securities as

at 1

1.03

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4S

ourc

e: D

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ank

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151

years

10

11

12

13

14

15

16

17

18

19

20

for

liste

d federa

l securities

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0,0

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256

0,0

262

0,0

266

0,0

270

years

21

22

23

24

25

26

27

28

29

30

for

liste

d federa

l securities

0,0

268

0,0

26997

0,0

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0,0

271

0,0

27

0,0

269

0,0

268

0,0

267

0,0

265

0,0

263

dis

cre

te y

ield

s0,0

272

0,0

274

0,0

274

0,0

275

0,0

274

0,0

273

0,0

272

0,0

270

0,0

268

0,0

266

Te

rm S

tru

ctu

re o

f lis

ted

ge

rma

n f

ed

era

l se

cu

riti

es

yiel

ds w

ith r

esid

ual m

atur

ities

of

0

0,51

1,52

2,53

05

10

15

20

25

30

35

40

Yield in %

Yield Cu

rve: Svensson (1994)

37


Inorganic Growth Strategies in Private Equity by Benjamin Hammer and Johanna Stein

This edition’s current research focuses on a recent study of the Chair of Financial Management at HHL Leipzig Graduate School of Management dealing with add-on acquisitions of Private Equity portfolio companies1. The growing importance of such acquisitions has been linked to the quest for new value creation strategies in a maturing Private Equity industry. Fierce competition, saturated markets and increasing return pressure, amongst others, have brought so-called “buy & build” strategies, which rely on an initial platform acquisition and a set of smaller subsequent add-ons, into vogue. To put it in the words of the 2012 Bain Global Private Equity Report:

“When done right, buy-and-build can be a portfolio management strategy ideally suited for markets like today’s, when PE firms can no longer ride in the tailwinds of multiple expansion and leverage but need to generate alpha to earn their carry”.2

Despite the seemingly growing importance of add-on acquisitions, academic evidence is still scarce. The few existing studies have furthermore examined intermediate M&A activity as a mere return driver, whereas no study has highlighted

the determinants of add-on activity itself. Thus, the Chair of Financial Management’s study “Inorganic Growth Strategies in Private Equity: Empirical Evidence on Add-on Acquisitions” addresses the need for empirical analysis of:

the overall add-on relevance in the PE market

the reasons for add-on acquisitions and the way they are executed

the determinants of add-on acquisition strategies.

Besides shedding light on a hitherto unexplored but evidentially important component of PE value creation, the study also sets standards in terms of market coverage. With a total of 9,548 buyouts and 4,973 associated add-on acquisitions, it truly constitutes of the largest studies of the PE market in recent years.

The findings of the study are threefold. First, it shows that add-on acquisitions generally move along the same cycles as the overall buyout market although the global financial crisis has affected add-on activity slightly less (see figure).

1 The research paper “Inorganic Growth Strategies in Private Equity: Empirical Evidence on Add-on Acquisitions” by Benjamin Hammer, Alexander Knauer, Magnus Pflücke and Bernhard

Schwetzler is available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2338115.

2 The 2012 Bain Global Private Equity Report is available at: http://www.bain.com/Images/Bain_and_Company_Global_Private_Equity_Report_2012%

38


The fact that around 12% of involved PE sponsors account for 80% of add-on acquisitions furthermore shows that relatively few PE firms rely on inorganic growth strategies. These few PE firms are predominantly large and successful PE sponsors indicating that only such sponsors have access to add-on acquisitions. Regarding reasons for add-ons, secondly, the results suggest that PE firms aim at exploiting synergy affects since most of the subsequent add-on acquisitions occur in the same industry as the platform acquisition. Portfolio firms furthermore conduct

add-on acquisitions at a rather early stage of the holding period which might account for the pressure of PE sponsors to realize these synergies before exit. Finally, the study finds several determinants that increase add-on likeliness: large buyouts, public-to-private and financial buyouts as well as those sponsored by large and successful PE firms are found to be significantly more likely to pursue inorganic growth strategies. Buyouts in less fragmented industries exhibit high add-on likeliness too.

Indexed development of buyouts and add-on acquisitions

39


The study of the Chair of Financial Management provides a good first overview on the add-on market and enhances understanding for such acquisitions and the way PE firms make use of it. In light of the very few existing studies, however, much work is still to come. In that sense, spadework was also done by Mariela Borel and Diana Heger from the Centre for European Economic Research (ZEW) with their recent discussion paper “Sources of Value Creation Through Private Equity-Backed Mergers and Acquisitions: The Case of Buy-and-Build Strategies”.3 This study adds insight

into the operating characteristics of platform and add-on targets and the impact of buy & build strategies upon their performance. Therewith, the ZEW discussion paper complements the findings of the Chair of Financial Management’s add-on study. Both research papers together hopefully enhance the decision-making abilities of Private Equity professionals and investors as well as the understanding for contemporary value creation strategies of PE firms.

3 The research paper “Sources of Value Creation Through Private Equity-Backed Mergers and Acquisitions: The Case of Buy-and-Build Strategies” by Mariela Borel and Diana Heger is available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2356191&download=yes.

40

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