hec - dow jones - pe fitness rankings - faq_final

8/8/2019 HEC - Dow Jones - PE Fitness Rankings - FAQ_final

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Proprietary and Confidential All Rights Reserved Prof. Oliver Gottschalg

Rank Firm Name

Fitness

Score

(Standar

dized)1 AXA Private Equity 3,10

2 CDC Entreprises Equity Capital (IXIS Equity Cap/Priv Equity) 3,07

3 Providence Equity Partners, Inc. (FKA: Providence Ventures) 2,68

4 Goldman, Sachs & Co. 2,46

5 TPG (FKA:Texas Pacific Group) 2,44

6 Oak Hill Capital Management, Inc. 2,40

7 Norwest Equity Partners 2,33

8 Madison Dearborn Partners LLC 2,14

9 Carlyle Group, The 2,11

10 Welsh, Carson, Anderson & Stowe 2,00

11 3i Group PLC 1,89

12 Warburg Pincus LLC 1,78

13 Apax Partners Worldwide 1,66

14 GMT Communications Partners, Ltd. 1,63

15 Parcom Capital (FKA: Parcom Ventures BV) 1,62

16 AIG Capital Partners 1,45

17 Barclays Private Equity, Ltd. 1,31

18 Kohlberg, Kravis, Roberts & Co. (AKA: KKR) 1,2919 Charterhouse Capital Partners LLP 1,27

20 Hellman & Friedman 1,15

21 Bain Capital 1,09

22 American Capital, Ltd. (FKA: American Capital Strategies) 0,96

23 Odyssey Investment Partners, LLC 0,95

24 Thomas H. Lee Partners (AKA: TH Lee Partners) 0,75

25 TowerBrook Capital Partners L.P. (FKA: Soros Private Equity) 0,68


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GENERAL BACKGROUND

What are the data sources behind the rankings?

To obtain the most accurate picture of the universe of PE firms and their investments, we drew ona variety of available databases and performed a number of cross-checks of the information usedin this study.

To calibrate our model based on the historic relationship firm performance and each of the fitnesscriteria, we drew on a proprietary dataset with information on the activity and performance of PEfirms (the HEC Buyout Database). This dataset contains detailed information on the investmentcharacteristics and performance of thousands of PE transactions over the past 30 years.

To ensure consistency and comparability of the data, we used ThomsonReuters VentureXpertdatabase as the primary source for up-to-date investment activity. Both academics andpractitioners generally consider VentureXpert and as one of the most reliable sources of industry-standard benchmark statistics.

To further enhance the quality of the underlying data, we surveyed 211 PE firms in February2010. In this survey, we provided them with a list of investments made by their firm according toVentureXpert and invited them to confirm, update or correct the information as needed.

How have the evaluated PE firms been selected?

We initially gathered data from VentureXpert all investments made by buyout-type orgeneralists-type PE funds involving portfolio companies located in "Americas" or "Europe". Wefurther considered only the following investor types:

Fund Type

SBIC Affiliated with Commercial Bank

SBIC Affiliated with Investment/Merchant Bank

Independent Private Partnership

Venture/PE Subsidiary of Other Fin. Institution

Evergreen Funds

SBIC Private Partnership

Direct Investor-Investment/Merchant Bank

Commercial Bank Affil. or Subsidiary Partnership

Venture/PE Subsidiary of Investment/Merchant Bank

Venture/PE Subsidiary of Commercial Bank

Investment Bank Affil. or Subsidiary Partnership

Other Fin. Institution Affil or Subsid. Partnership

Venture/PE Subsidiary of Insurance Company


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This data (a total of 35,372 investments1 of US$ 672B in equity by 2,904 funds and 1,403 PEfirms into 18,005 distinct portfolio companies) captures the universe of PE investing.

From this universe, we then selected all those PE firms that met, as of 1/8/2009, the followingobjective criteria:

! More than 20 transactions completed

! More than $100M in equity invested

! Over 5 years of PE investment activity

How large and representative is your sample of PE firms?

The filters we applied led to a sample of 276 PE firms and over 1,200 funds which made over23,000 investments2 totaling over US$ 500B in equity into over 11,000 portfolio companies. Thiscorresponds to about 2/3 of all PE activity covered in VentureXpert in terms of the volume ofequity investment.

For some of these PE firms, insufficient data was available for some of the analyses andconsequently they had to be excluded from the rankings.

METHODOLOGY

According to which criteria is the competitive fitness of the PE firms assessed?

We indentified and empirically validated 10 criteria3

that capture various aspect of a firms

competitive fitness, i.e. ability to generate high future returns. Generally, the components of afirms competitive fitness cannot be measured directly. To make an objective and data-drivenassessment possible, we followed a well-established statistical approach and identified suitableand measurable proxies for the underlying skills and abilities of PE firms. To the extent that theseproxies are strongly correlated with the actual underlying skills and abilities, they can used toassess a firms future ability to generate high returns.

# Criterion What it captures How it is calculated

1 Active PortfolioSize (Volume)

Scale of CurrentActivities

Joint size of all companies in the current portfolio,measured in terms of the total equity invested

2 Avg BAA Yield Ability to takeadvantage ofcheap debtfinancing

Average 1-year yield on BAA corporate bonds overall investments of a firm, measured at the time agiven investment is made.

1 This number includes double-counts for each participant of a club-deal or multiple investments by the same PEfirm in the same portfolio company.2 This number includes double-counts for each participant of a club-deal or multiple investments by the same PEfirm in the same portfolio company.3 Initially, we calculated over 30 criteria, but the model calibration (see below) pointed to 10 empirically validcriteria, so we excluded the others from the analysis.


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3 Market Timing Ability to timethe stock marketto benefit from

market trendsover the holdingperiod

Average percentage difference between the level ofthe S&P 500 index at the date of the entry and levelof the S&P 500 index at the date of the exit, over all

investments made by a firm.

4 Exit Timing Ability to timethe stock marketto exit at high exitvaluations

Average percentage difference between the level ofthe S&P 500 index at the date of the exit and theaverage level of the S&P 500 index over the period182 days prior to and 182 days after the exit, over allinvestments made by a firm.

5 Industry Focus Level of industryfocus

Level of industry concentration (measured as aHerfindahl-type measure of industry concentration)for all investments made by a firm

6 5-yrs-chg-in-Herfindahl

Change in levelof industry focus

Difference between the levels of industryconcentration (measured as a Herfindahl-typemeasure of industry concentration based on theamount of equity invested) for investments made 6-11 years ago and the same measure for investmentsmade in the past 5 years.

7 Procyclicality Quality of dealflow, i.e. abilityto continue toinvest duringperiods when all

other PE firms aredecreasing theirinvesting pace.

Correlation coefficient in amount invested per monthbetween focal firm and all PE firms

8 RecentVariance inDeal Size

Flexibility to takeadvantage ofinvestmentopportunities ofdifferent sizes.

Coefficient of variance in the amount of equityinvested over the investments made by a firm in thepast 5 years.

9 StrategicOverlap

Level of strategicuniqueness/differentiation

Percentage of activity in each strategic cell for (a)the focal firm and (b) all PE firms. A strategic cell isthe combination of a given industry sector and a

given size category. It then calculates the strategicoverlap as the sum of joint activity (minimum of thepercentage invested of the firm and the percentageinvested by all firms in a given cell) over all cells. Astrategic overlap of 1 means that a firm investsexactly like the average firm a score of 0 indicatesthat no other firm makes similar investments.

10 Increase inScale

Recent Change inScale of Activity

Difference between the Scale of Activity (measure asthe number of active investments in the portfolio) (a)today and (b) 5 years ago.


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How are missing values or outliers treated?

Inevitably, we have to deal with missing values and outliers for some firms. We chose a

conservative approach and only considered data points where full information is available. Thismeans that, for example, when the exact exit date on an investment in now known, we ignore thisinvestment for the calculation of the Exit Timing value. If for one of the firms we do not have asufficient number of data points to calculate a given value, e.g. at least six investments with validexit date information to calculate the Exit Timing value, and then we exclude this firm from theranking. We also had to deal with extreme values, for example, a firm may have grown fourstandard deviations faster than the average. Such cases would distort the ranking, so that wefollowed a standard practice in statistics and capped outliers at a value of two standard twostandard deviations above/below the average.

How are the individual values in the 10 criteria combined to obtain the overall ranking of

competitive fitness?

To avoid any subjectivity in our ranking, we have used empirically derived weightings of the 10individual criteria, based on the historic relationship between the score in each criterion andsubsequent performance.

The weights have been calculated based on the following back testing analysis: For the years1996 to 2003, we calculated historic scores for all 10 criteria for 217 anonymous firms in theHEC Buyout Database in all criteria, i.e. considering their investment activity only until thatpoint in time. We then measured the aggregate performance of each firm for a five-year windowstarting on 1/1/1996, 1/1/1997 to 1/1/2003 based on the performance information available in

this database. Then we constructed a panel dataset by linking for each firm and each point in timethe values for the 10 criteria to the 5-year subsequent performance to calibrate a complexmultivariate statistical model

4.

A more simplistic, but conceptually similar approach would be to look at the correlation betweeneach criterion and subsequent performance to see which criterion would have been historically(i.e. in 96, 97 03) a good predictor of subsequent performance and use the correlations asweights to combine the criteria: a criterion that strongly predicts performance has a higher weightthan another.

Based on this model, we were able to quantify to what extent a given criterion (measured in the

past) would have predicted subsequent performance. Using the results from this back testinganalysis, we were able to calibrate a reliable statistical model

5 of the performance impact ofdifferent aspects of competitive fitness for PE firms that enables us to identify and rank the mostcompetitive PE firms worldwide.

4 US Patent Pending5 F-test significant at p


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How reliable is the statistical model behind the aggregate ranking?

The results indicate a strong model fit with the data (F-test significant at p


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What are the most relevant drives of competitiveness according to this analysis?

Order of

Importance

Direction of

PerformanceImpact

Factor Intuitive Interpretation

1 Positive Recent Variance in Deal Size Ability to take advantage ofinvestment opportunitiesacross large range of deal-sizes helps performance

2 Negative Avg BAA Yield Ability to take advantage ofcheap debt financing helpsperformance

3 Positive Industry Focus Specialization on a selectfew industry sectorsfacilitates value creation

4 Positive Market Timing Ability to time the stock

market to benefit frommarket trends over theholding period helpsperformance

5 Positive Exit Timing Ability to time the stockmarket to exit at high exitvaluations helpsperformance

6 Positive 5-yrs-chg-in-Herfindahl Strategy Drift due todiversification into a largerset of industries hurtsperformance

7 Negative Active Portfolio Size A smaller portfolio under

management at a given pointin time facilitates valuecreation to each of theportfolio companies

8 Negative Procyclicality A low level of procyclicality,indicating a high quality dealflow that allows PE firms toinvest even in slow PEmarkets helps performance

9 Negative Strategic Overlap A low level of StrategicOverlap, indicating a highlevel of strategicdifferentiation allows PE

firms to avoid the moneychasing deals phenomenonand helps performance

10 Positive Increase in Scale As our multivariate analysisalready considers thenegative effect of a largeportfolio size, an increase infirm scale is an indication ofstrong deal flow and goeswith higher performance.


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Note that in the multivariate analysis we perform, each factor is considered in terms of itsmarginal influence on performance, i.e. the influence beyond all other factors. Some of the 10criteria have a relatively small impact on our aggregate fitness ranking in a multivariate analysis.

This does not mean that they have no impact on performance, but rather that their considerationdoes not add anything to those factors already included in the model.

Further note that the results of this analysis capture (by design) only the average performanceimpact of a given factor for the typical PE firms. Clearly there are many investors who generate(and will continue to generate) strong returns based on very different, and maybe even opposite,approaches. Considering the broader PE universe we analyzed, however, these will be theproverbial exceptions to the statistical rules identified in our analysis.

How robust is the ranking to alternative model specifications or to measurement error?

The confidential nature of the PE industry makes it impossible to be 100% certain of the accuracyof the data we use, even if the same data sources are typically used for leading academic researchand to compose industry-standard statistics of PE activity. We further conducted a number ofrobustness checks to verify to what extent the membership of a PE firm in the group of the fittestPE firms changes (a) if we exclude one of the 10 criteria from our model or (b) if we consider a25% measurement error for one of the 10 criteria for a given firm or (c) if we consider a 10%measurement error for all 10 criteria for a given firm. The results from these robustness checksconfirmed the overall reliability of the method.

What is the economic impact of the fitness score?

Drawing on the data on 217 anonymous PE firms in the HEC Buyout Database, we can assess theeconomic relevance of the fitness score. To this end, we identified for the period from 1996 to2003 those data points with the highest Competitive Fitness Score. When we compare theaverage performance of the 10% with the highest Competitive Fitness Score to the sampleaverage, we can see that the performance (expressed as the % of annual value creation relative tothe NAVs at a given point of time) of the Top 10% sample is higher than the averageperformance by a factor of 1.7.


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LIMITATIONS

Limitations of the data

The confidential nature of the PE industry makes it impossible to compose a 100% accuratedatabase on private equity and we cannot exclude the possibility of biases in our results due tomissing or inaccurate information. However, we rely on the same data sources typically used tocompose industry-standard statistics of PE activity and we consider our data by far the bestavailable for this kind of analysis. We have taken great care to exclude PE firms from therankings for which no sufficient data was available to derive an accurate fitness score.

Limitations of the method

Our methodology has two inevitable limitations:

First, the ranking of competitive fitness is based on the historic relationship between a givencriterion and subsequent performance. To the extent that the success factors in PE changedrastically over time, the accuracy of the predications from our model decreases. However, thelong time-period (28 years) over which the model has been derived and the fact that therelationships captured in our model generally make intuitive sense (face-validity) suggest thatthe predications from the model are generally valid.

Second, our analysis is limited to aspects of PE firms that are related to hard data on investmentactivity we can observe. Hence our model does not capture unobserved factors, such as thedeparture of key personnel, future changes in strategy that are not yet reflected in recent

investment decisions etc. that may also influence the future performance or a firm. Overall, it isimportant to keep in mind that such an analysis can never be expected to lead to a perfectprediction of future performance. However, it can be a useful indicator that captures a substantialpart of a firms competitiveness. This is illustrated by the fact that an application of our model inthe past (1996-2003) would have captured performance over the 1996-2008 period with anaccuracy of 13.9% (R-square of the statistical model).

CONCLUSIONS

In summary, the HEC - Dow Jones Private Equity Fitness RankingTM constitutes a landmarkproject that increases the understanding of the strategic logic and the performance drivers of PE.

It uses a data-driven methodology to provide investors with reliable and objective insights intothe strategic positioning and competitive fitness of the worlds leading PE firms and gives anindication of which firms are best positioned to generate strong long-term performance goingforward.


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IMPORTANT DISCLAIMER

This material has been prepared on the basis of publicly available information, internally

developed data and other third party sources believed to be reliable, however, HEC Paris andPeracs, LLC have not sought to independently verify information obtained from these sourcesand makes no representations or warranties as to accuracy, completeness or reliability of suchinformation. This material is for information and illustrative purposes only, is not investmentadvice and is no assurance of actual future performance or results of any private equity segmentor fund. HEC and Peracs do not represent, warrant or guarantee that this information is suitablefor any investment purpose and it should not be used as a basis for investment decisions. Nothingherein should be construed as any past, current or future recommendation to buy or sell anysecurity or an offer to sell, or a solicitation of an offer to buy any security. This material does notpurport to contain all of the information that a prospective investor may wish to consider and isnot to be relied upon as such or used in substitution for the exercise of independent judgment.

hec - dow jones - pe fitness rankings - faq_final

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