3. private equity

8/10/2019 3. Private Equity

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Dr. Denis Schweizer Associate Professor of Finance John Molson School of Business, Concordia UniversityMailing address: 1455 de Maisonneuve Boulevard West, Montreal, Quebec H3G 1M8Office: MB 11.305Phone: +1(514)-848-2424, ext. 2926Fax: +1(514)-848-4500E-Mail: [email protected]

3. Private Equity

Investment Analysis



Investment AnalysisDenis Schweizer

Agenda

I. Private Equity as an Asset Class

II. Investment Process of a Private Equity Fund

III. Private Equity Returns

IV. Strategic Asset Allocation




What is Private Equity?*

Private Equity

= „any equity investment in a company which is not quoted on a stock exchange…“

What about companies which were publicly listed but are taken private?

Special Purpose Acquisition Companies (SPACs)?

Buying stakes in a company, with the major intention to gain ownership of underlying

assets (e.g. real estate)?

Secondary transactions?

Activism strategies?

…

A famous judge in the UK said: “It is hard to define what an elephant is, but you still

recognize one when you see it!”

* See Frasor-Sampson (2007)




What is Private Equity?*

Private Equity means providing medium- to long-term funds to companies in a criticalphase of their development without sufficient collaterals and if required entrepreneurialsupport. The intent to sell the stake in the future guarantees risk adjusted profit-taking.

The following counts as Private Equity as well:

Mezzanine Capital: Funds which are (per se) not provided by shareholders but do havemore or less characteristics of equity

De-listing respective Taking-Private of publicly listed firms (LBO)

Activism strategies

Special Purpose Acquisition Companies (SPAC)

Private Investments in Public Equity (PIPE)

…

* See Sahlman (1990)




Systematization of Private Equity by Funding

Phase Helps to Classify

The investment spectrum spans over all stages of corporate life

Public-to-Private

St. Ex.Growth Stage

Seed

Production

design

• Conceptassessment

• Businessanalysis

• Marketanalysis

First-Stage

Production start

• Marketentry

• First

sales

Start-up

Formation ofthe company

• Marketingconcept

• Develop-ment ofproducts

Second-

Stage

Scaling

• Market entry

• Marketleader

• Private Equity

• MBO / MBI

• Mezzanine Capital

• Venture Capital

• Private Equity

• Mezzanine Capital

• Loans

• Business Promotions

• Invest-mentbanks

• Free Float

• Early Stage

Venture Capital

• Incunators• Business Angels

• StrategicInvestors

• Entrepreneur

• Small businesspromotion

• Friends, Relatives

• Business Angels

• Incubators

Take-Private

Stage

Delisting

• Undervaluation

• Acquisition

Third-

Stage

Standard-ization

• Internat-

ioanliza-tion

Fourth-

Stage

Pre-IPO

• Prep-aration of

IPO• Acquisition

Early Stage

S t a g e

o f l i f e

S o u r c e o f

f u n d i n g

Venture Capital Buy-Outs / MezzanineSpecial Situations




Typical Factors of Success and Risks

Characterize Different Private Equity Segments

Late StageEstablished GrowthStrong GrowthEarly StageStage of Life

Typical

Investment

Phase

Typical

Earnings

Development

Typical Factors

of Success Technology Marketing Operations

Financial RiskManagement and

Financial RiskMarket RiskProduct RiskMain Risks

Profit zone

Loss area

Private Public

Seed Start-upExpansion /

Development

Late Stage

Pre-IPO

Turn

aroundMBO / MBI




Every Funding Phase Requires Specific Skills

by the Private Equity Manager

Late StageGrowth StageEarly Stage

DistressedMatureMiddle MarketGrowthEarly Stage

Venture Capital

• Technical Know-How

•Infrastructure / Seed

Capital

•Often Minor Stakes

Examples:

Buyout

•Operational / Strategic

Expertise

•Financial Know-How

Examples:

Special Situations

• Turnaround, Distressed

•Mezzanine

•Financial Know-How

Examples:

Source: Partners Group



Page 9Investment AnalysisDenis Schweizer

Buy-Out Funds Dominate the Private Equity

Fundraising Market in Europe

Source: Thomson Reuters / EVCA (2000-2006) & EVCA / PEREP Analytics (2007-2011)




Global Private Equity Fundraising

Fundraising activity remains moderate

Source: Preqin, Credit Suisse / IDC




Deal Activity and Size

Lower investment volumes but still high number of deals





Private Equity Exit Activity

Exit activity slowed down somewhat in Q3 2012


E M k S i i A d




European Market Statistics – Amount and

Number of Companies

M th 50% f th P i t E it I d t I




More than 50% of the Private Equity Industry Is

Funded by Investors from the U.S. and the U.K.

32.4

23.9

8.8

5.7

5.5

4.3 3.4

Allocated Funds by Country 2010(Bn. €)

USA UK France SwedenNetherlands Germany

Asia

29.2

19.6

15.5

10.9

9.6

9.4

4.03.9 5.7

Allocated Funds by Investors2010 (Bn. €)

Pension Funds Funds of FundsBanks Insurance CompaniesPrivate GovernmentsCorporates UniversitiesOther

S o u r c e

: B V K S p e c i a l P r i v a t e E q u i t y

i n E u r o p e , o w n p r e p a r a t i o n




Agenda





Private Equity is a Heterogeneous Asset Class




Private Equity is a Heterogeneous Asset Class

with Diverging Investment Alternatives

Region Vintage Funding Stage

Instruments

USA, Europe,

Asia, others

Investment

environment is

changingcontinuously (new

regulation /

deregulation, etc.)

1991, 1992 …

2007

Every vintage year

is characterized byspecific market

conditions with

strong impact on

return

Venture Capital

Buyout Special Situations

Every corporate stage of

life has key successfactors for an effective

investment (leverage,

cost structure, economic

cycle, exit options, etc.)

Primaries

Secondaries Manager Secondaries

Financial Secondaries

Listed Private Equity

Direct-/Co-Investments

SPAC

Due Diligence and

management process

alter with the underlying

Relative attractiveness of divergent instruments, funding stages, vintages and regions variesstrongly




Return Sources for Private Equity (1/2)

Value generation

approach

Levers of valuecapturing

Increase in equity

value throughchanges in valuation

Levers of value

creation

Increase in equity

value by changes in

profitability

(revenue, margin,net debt)

Financial

arbitrage

Secondary levers Levers with no

direct bottom line

effect, but the ability

to reinforce primary

levers

Financial engineering

Increasing operational

effectiveness

Increasing strategicdistinctiveness

Parenting effects

Reducingagency costs

Primary levers

Levers with directbottom line effect




Return Sources for Private Equity (2/2)

V a l u e g e n e r a t i o n a p p r o a c h

L e v e r s o f v a l u

e

c a p t u r i n g

L e v e r s o f v a l u e

c r e a t i o n

Financial

Arbitrage

Financial

Engineering

Increasing operat.effectiveness

Increasing strategic

distinctiveness

Parenting effects

Reducingagency costs

… based on changes in market valuation (A-1)… based on private information about the portf. Company (A-2)

… through superior market information (A-3)… through superior dealmaking capabilities (A-4)… through optimization of corporate scope (A-5)

Optimizing capital structure (B-1)Reducing corporate tax (B-2)

Cost cutting and margin improvements (C-1)

Reducing capital requirements (C-2)Removing managerial inefficiencies (C-3)

Corporate refocusing (D-1)Buy and build strategies (D-2)

Reducing agency costs of free cash flow (E-1)Improving incentive alignment (E-2)Improving monitoring and controlling (E-3)

Restoring entrepreneurial spirit (F-1) Advising and enabling (F-2)

Productivity and Employment Growth for PE-




Productivity and Employment Growth for PE-

Backed Companies, 2005 – 2011

Behind PE outperformance and PE value creation, productivity (as measured by EBITDAper employee) and employment are key drivers of business performance

PE has been able to improve productivity significantly (6.9% on average p.a. in Europe)

Employment grew by an average of 2.2% p.a. under PE ownership

Dotted lines for Benelux show productivity and employment growth without outliers. N=178 (excluding deals with insufficient data

S o u r c e : E r n s t & Y

o u n g d a t a , D a t a S t r e a m

EBITDA Growth Attribution by Investment




EBITDA Growth Attribution by Investment

Rationale, 2006 – 10

Organic revenue growth accounted for over 40% ofEBITDA growth. Cost reductions were responsible

for approximately 30%, and acquisitions also beganto play a significant role, representing about 20% ofgrowth

Good investors follow a simple rule: They look forthe fat in the company — and those guys are really

good — and cut it off. The trick is not to cut off themuscles (Professor Steven Kaplan - UniversityChicago / Booth School of Business)

Jesse Edgerton (FED economist) showed that theprobability of having an airplane three years after aPE investor in the company is roughly 40% lower

compared to their rivals Immediately after the acquisition of TXU (an

energy supplier) by KKR and TPG for a recordsum of $ 43.3 billion they sold companies‘

Gulfstream-V-Jet

Source: Ernst & Young

Impact of Vintage and Funding Stage on Return




Impact of Vintage and Funding Stage on Return

is Substantial




Historical Discounts on NAV

What is the relationship between the discount and the IRR?

Source: NYU Salomon Center




Private Equity Vintage Returns

Historically, recession vintage years were attractive

Source: Preqin, Credit Suisse PB Research

U.S. Equity Contribution and Purchase Price




q y

Multiples

Purchase prices have decreased and equity contribution has increased since 2007





Source: Reuters LPC/DealScan

Monthly Debt Volume

What are the consequences for „private equity“ investments?

Private Equity Funds as an Interface Between




Entrepreneur

Capital needs for:

• Business idea

• Growth• Operational

management• Funding

Exit strategy via Trade-Sale, IPO etc.Return Flow

Limited Partner (LP)

Capital Provision

Particularly:

• Insurances• Pension funds

• Corporate groups• Family Offices

• etc.

General Partner (GP)

Provides minor capital

stakes and manages the

private equity fund:

• Evaluation

• Employ strategies

• Offer value added

• Operate

• Impart knowledge• etc.

General Partner (GP)

q y

Investors and Companies

Exposure in Private Equity Is Set Up Slowly,



Page 32Investment Analysis

Denis Schweizer

q

however, Capital Is Locked Up

Set up of exposure starts with the so-called (Over-) Commitment. Cumulated Capital Calls

(Drawdown Capital) indicates the amount of committed capital which has been called by the General

Partner (GP). Invested Capital describes the interest of Drawdown Capital, which has been called orrefunded, respectively. The setup of a desired exposure can take several years.

0

200

400

600

800

1,000

1,200

M i l l i o n U . S . $

Invested Captial CommitmentCumulative Capital Calls Cumulative Profits

Dry Powder - Committed but Un-Invested




Denis Schweizer

Capital

Managers are well equipped to take advantage of upcoming opportunities

S o u r c e : P r e q i n , C r e d i t S u i s s e / I D C

The J-Curve Effect Dominates Short-Term




Denis Schweizer

Refunds

An investment process for Private Equity can feature a several years lasting J-Curve

Effect

1 Year 2 Years 3 Years 4 Years 5 Years 6 Years

N A V

Ca. 36 months J-Curve Effect

Growth Phase

Private Equity Instruments Feature Divergent




Denis Schweizer

--

P e r f o r m a n c e ( N

A V + R e f u n d i n g )

Year 3 Year 6 Year 9 Year 12

-

Manager Secondaries

Partly well-known and appraisableportfolio

A relative small fraction of firms in theportfolio has seen appreciation

Financial Secondaries

Promises to pay are mostly called and invested Portfolio is known and appraisable

A predominant fraction of firms in the portfolio hasseen appreciation

‚J-Curve Effect‘

Investors give the General Partner a promise to pay Portfolio is unknown at this stage Incurring management fees do have, among others, a

negative effect on the NAV (J-Curve Effect)

Primaries

Source: Partners Group

What are the resulting risk andreturn profiles?

Value-Creation Potential




Denis Schweizer

Agenda





Return Differences of Private Equity Funds




Denis Schweizer

Source: BVI, Venture Economics calculations by Braun & Schreiber

U S V C

Return p.a.

in %

Between Top and Bottom Quartile Are Substantial

Only TOP Funds outperform other asset classes sustainably

E U

B O

E U

V C

U S

B O

-20

0

20

40

60

80

100

M o n e y m a r k e t f u n d s , E

U R

M o n e y m a r k e t f u n d s , I n

t e r n a t i o n a l

F i x e d i n c o m e f u n d s ,

E U

R ,

G e r m a n y


E U

R


U S

D


I n t e r n a t i o n a l


C o

r p o r a t e B o n d s

E q u i t y f u n d s ,

G e r m a n y


E u r o p e


N o r t h A m

e r i c a


I n t e r n a t i o

n a l

U S M e z z a n i n e f u n d s

1.Quartile 2.Quartil 3.Quartil 4.Quartil1.Quartil

Return and Risk Measures of Private Equity Vary

Ti A A l i i N




Denis Schweizer

Calculation base per 30.6.2003. Continuous quarterly returns (TWP) for 10 years each from starting year.

Calculation on pooled Cash-Flows and NAVs of floating years 1980 – 2003. Risk free rate 3% p.aSource: TFSD Venture Economics,

B&S Research

0

5

10

15

20

25

-2

0

2

4

6

8

10

US Venture Capital

Rendite, Volatilität, Semivolatilität

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Return, Volatility, Semivolatility

Sharpe Ratio, Schiefe, Kurtosis

1980 – 1990

1982 – 1992

1984 – 1994

1986 – 1996

1988 – 1998

1990 – 2000

1992 – 2002

1980 – 1990

1982 – 1992

1984 – 1994

1986 – 1996

1988 – 1998

1990 – 2000

1992 – 2002

US Buy-Out

0

5

10

15

20

25

-2

0

2

4

6

8

10

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

1980 – 1990

1982 – 1992

1984 – 1994

1986 – 1996

1988 – 1998

1990 – 2000

1992 – 2002

1980 – 1990

1982 – 1992

1984 – 1994

1986 – 1996

1988 – 1998

1990 – 2000

1992 – 2002

Rendite, Volatilität, Semivolatilität

Sharpe Ratio, Schiefe, Kurtosis

Return, Volatility, Semivolatility

Sharpe Ratio, Skewness, Kurtosis Sharpe Ratio, Skewness, Kurtosis

over Time – an Accurate Analysis is Necessary

How Does the Internal Rate of Return Method

(IRR) W k?




Denis Schweizer

Example: + = = + = for not realized + = −+ = 0

(IRR) Work?

The IRR is the interest rate for which the following holds: the sum of capital values of all Cash-In-

Flows/ Refunds (CIF) must equalize the sum of capital values of all Cash-Out-Flows / Investments

(COF):

1 A B C D

2

Year COF CIF

Nett

CashFlow

3 0 -1

-1

4 1 -2 1

-1

5 2 -3 1

-2

6 3 2

2

7 4 2

2

8 5 4

4

9

IRR=

26%

=IKV(D3:D8)

-1-2

-3

1 12 2

4

-4

-2

0

2

4

6

0 1 2 3 4 5

C a s h - F l o w

Year

COF CIN

Solution: + + + + + + + +6% +6% +6% +6% 4+6% 1 +6% 3+6%

Vintage Year and Access to “Top-Quartile”

D t i R li d IRR’ S b t ti ll




Denis Schweizer

Determines Realized IRR’s Substantially

IRR Distribution of VE Funds

e

r c e n t

1 9 8 5

1 9 8 6

1 9 8 7

1 9 8 8

1 9 8 9

1 9 9 0

1 9 9 1

1 9 9 2

1 9 9 3

1 9 9 4

1 9 9 5

1 9 9 6

1 9 9 7

1 9 9 8

1 9 9 9

2 0 0 0

2 0 0 1

2 0 0 2

2 0 0 3

2 0 0 4

0

50

100

EU BO

1 9 8 5

1 9 8 6

1 9 8 7

1 9 8 8

1 9 8 9

1 9 9 0

1 9 9 1

1 9 9 2

1 9 9 3

1 9 9 4

1 9 9 5

1 9 9 6

1 9 9 7

1 9 9 8

1 9 9 9

2 0 0 0

2 0 0 1

2 0 0 2

2 0 0 3

2 0 0 4

0

50

100

EU VC

Mean per Vintage Year

Is the IRR an adequate performance measure?

Is there a J-Curve?

Problems in Applying the IRR as PerformanceM




Denis Schweizer

Measure

The IRR is strongly determined by the time structure of cash flows – accounting Cash-In-Flows at closer dates increases the IRR and leads to higher manager-performance

The IRR method implicitly assumes that the whole Commitment until Drawdown (COF)and all CIF (subject to distribution) can be re-invested at the IRR. This is not applicable ingeneral as equivalent investment projects are missing (re-investment hypotheses)

The calculation of the IRR neither has to lead to a unique solution (polynomials of higher

degrees) nor any solution (within the real numbers – fundamental law of algebra)

∙ = ≥ 1 , ∈, ≠ 0

A typical solution for this problem is to use multiples: Total Value to Paid In (TVPI) accounts for the distribution of realized and outstanding

investments:

Problems of the IRR stem from the underlying calculation method:

IRR vs TVPI a Case of Time Dependence?




Denis Schweizer

IRR vs. TVPI – a Case of Time Dependence?

For high IRRs the timing is important: the TVPI is the same for all three cases

But different IRRs:

Different IRRs can yield to the same TVPI:

TVPI = 2

Year Distribution DrawdownDistribution DrawdownDistribution Drawdown

1 0 500 0 100 0 100

2 0 0 0 100 250 100

3 0 0 0 100 250 100

4 0 0 0 100 250 100

5 1000 0 1000 100 250 100

IRR =

Scenario 1 Scenario 2 Scenario 3

18.9% 35.2% 145.9%

How to Calculate a Pooled IRR for a Portfolio?




Denis Schweizer

How to Calculate a Pooled IRR for a Portfolio?

In most cases the invested capital, fund volume, commitment etc. is used as a weightingfactor

What is the pooled IRR for a portfolio of funds (Fund of Private Equity Funds)?

IRRs are not additive – but TVPIs are additive

Year Fonds 1 Fonds 2 Fonds 3 Pooled CF

1 -1000 -500 -500 -2000

2 0 0 700 700

3 0 750 0 7504 0 0 0 0

5 1120 0 0 1120

Pooled IRR 2.9% 22.5% 40.0% 10.5%

Mean IRR 21.8%

Weighted Mean IRR 17.1%

Weight 2 1 1 4

IRR vs TVPI




Denis Schweizer

IRR vs. TVPI

Which fund is favored?

A long holding period can trigger a high TVPI when the IRR is comparable low

Year Distribution DrawdownDistribution DrawdownDistribution Drawdown

1 0 500 0 500 0 500

2 0 0 0 0 700 0

3 0 0 750 0 0 0

4 0 0 0 0 0 05 1120 0 0 0 0 0

IRR =

TVPI= 2,24 1,50 1,40

Fund 1 Fund 2 Fund 3

22,3% 22,5% 40,0%

The Results of IRR and TVPI DivergeSignificantly




Denis Schweizer

Significantly

Trade-off between IRR and TVPI

Why are the TVPIs forthe VC funds in general

higher compared to the

buyout funds?

TVPI Distribution of VE Funds

I

1 9 8 5

1 9 8 6

1 9 8 7

1 9 8 8

1 9 8 9

1 9 9 0

1 9 9 1

1 9 9 2

1 9 9 3

1 9 9 4

1 9 9 5

1 9 9 6

1 9 9 7

1 9 9 8

1 9 9 9

2 0 0 0

2 0 0 1

2 0 0 2

2 0 0 3

2 0 0 4

1

2

3

4

5

6

EU BO

1 9 8 5

1 9 8 6

1 9 8 7

1 9 8 8

1 9 8 9

1 9 9 0

1 9 9 1

1 9 9 2

1 9 9 3

1 9 9 4

1 9 9 5

1 9 9 6

1 9 9 7

1 9 9 8

1 9 9 9

2 0 0 0

2 0 0 1

2 0 0 2

2 0 0 3

2 0 0 4

1

2

3

4

5

6

EU VC


IRR Distribution of VE Funds

1 9 8 5

1 9 8 6

1 9 8 7

1 9 8 8

1 9 8 9

1 9 9 0

1 9 9 1

1 9 9 2

1 9 9 3

1 9 9 4

1 9 9 5

1 9 9 6

1 9 9 7

1 9 9 8

1 9 9 9

2 0 0 0

2 0 0 1

2 0 0 2

2 0 0 3

2 0 0 4

0

50

100

EU BO

1 9 8 5

1 9 8 6

1 9 8 7

1 9 8 8

1 9 8 9

1 9 9 0

1 9 9 1

1 9 9 2

1 9 9 3

1 9 9 4

1 9 9 5

1 9 9 6

1 9 9 7

1 9 9 8

1 9 9 9

2 0 0 0

2 0 0 1

2 0 0 2

2 0 0 3

2 0 0 4

0

50

100

EU VC


Risk Structure of Private Equity Investments IsNot Comparable to Traditional Asset Classes




Denis Schweizer

Not Comparable to Traditional Asset Classes

Private Equity returns are not normally distributed

Calculation base: Continuous Quarterly returns based on pooled Cash-Flows and NAVs of floating years 1980 – 2008. All VY from starting year to 30.06.2001.

Source: TFSD Venture Economics,Bloomberg, B&S Research

-15% -10% -5% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55%

R e l a t i v e F r e q u e n c y

US Venture Capital

-15% -10% -5% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55%

Nasdaq Composite


-15% -10% -5% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55%


US Buy-Outs

-15% -10% -5% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55%


S&P 500

Agenda




Denis Schweizer

Agenda





What Is the Value Added of Private Equity inTraditional Portfolios?




Denis Schweizer

Traditional Portfolios?

Fraction in Private Equity

P o r t f o l i o V

o l a t i l i t y p . a .

10% Fraction of Private Equity increases Portfolio Stability

Source

Yale Endowment – Private Equity Has theLargest Portfolio Weight




Denis Schweizer

g W g

Private Equity allocation increased monotonically until 2011 up to 35.1%

S o u r c e : Y a l e E n d o w

m e n t R e p o r t 2 0 1 1

Heterogeneity of this Asset Class Complicatesthe Problem of Optimal Asset Allocation




Denis Schweizer

p

Private Equity is a very heterogeneous asset class and shows low correlation within

itself

What is the optimal allocation in single instruments and funding stages?

Why do we find such a heterogeneity in the return distributions?

Source: Bloomberg, Thomson Venture Economics (quarterly cash flow summaries), period 1.1.1993 - 30.06.2006

US VC US BO US Mezz US All PE EU VC EU BO EU All PE

US VC 1.00 0.50 0.55 0.92 0.51 0.57 0.63

US BO 0.50 1.00 0.39 0.80 0.37 0.33 0.43

US Mezz

0.55 0.39 1.00 0.57 0.35 0.40 0.38

US All PE 0.92 0.80 0.57 1.00 0.51 0.53 0.62

EU VC

0.51 0.37 0.35 0.51 1.00 0.66 0.76

EU BO 0.57 0.33 0.40 0.53 0.66 1.00 0.86

EU All PE 0.63 0.43 0.38 0.62 0.76 0.86 1.00

Use of Historical Return Time Series in PortfolioOptimization Context leads to Misallocation




Denis Schweizer

p

The evaluation of a Private Equity investment does not have to coincide with its true value

due to diverse biases… Stale Pricing – Book values of stakes do not reflect actual market values and react

delayed to Public Equity Why?

Appraisal Smoothing – Volatility is underestimated due to backing on valuation history

of illiquid investments (Gompers and Lerner, 1997) Why?

Illiquidity –

Based on longer valuation periods (low numbers of observations) volatilityis underestimated (Geltner, 1991) Why?

Managed Pricing – GP disposes of scope in assessing illiquid investments (often

problematic in situation of total losses) Strategy?

Direct, naïve calculation of performance measures from Venture Economics (orequivalent databases) time series results in too low volatilities and correlations as well as positive autocorrelation!„True“ values need to be calculated with adjustments (e.g. Geltner’s or Getmansky,

Makarov and Lo’s method)

An Intensive Analysis of Characteristics ofPrivate Equity Gains Importance




Denis Schweizer

q y p

A representative benchmark has to be the starting point of strategic asset allocation

Potential biases distort return / risk profile, leading to distortion of allocation andundesired return / risk profiles

Cash-Flow patterns are important for multi-periodic models, the compound interest effectshould not be underestimated

Only if the benchmarks’ return time series are representative, the

specification and calibration of a model will be successful

Private Equity – Benchmarking




Denis Schweizer

q g

0

100

200

300

400

500

600

700

800

Feb. 99 Jun. 00 Nov. 01 Mrz. 03 Aug. 04 Dez. 05 Apr. 07 Sep. 08

I n d e x

Datum

Private Equity

CepreX - US Growth/Small Buyout CepreX - US Venture Capital

VE US VC VE US BO

LPX Venture LPX America

LPX Buyout

CepreX - US

Growth/Sma

ll Buyout

CepreX - US

Venture

Capital

Venture

Economics

US VC

Venture

Economics

US BO

LPX Venture

LPX

America

LPX Buyout

CepreX - US Growth/Small BO

1,00

0,06

0,19

0,18

0,02

-0,10

-0,05

CepreX - US VC 0,06 1,00 0,28 0,21 0,27 0,23 0,21

Venture Economics US VC 0,19 0,28 1,00 0,52 0,59 0,49 0,25

Venture Economics US BO 0,18 0,21 0,52 1,00 0,55 0,47 0,41

LPX Venture 0,02 0,27 0,59 0,55 1,00 0,80 0,62

LPX America -0,10 0,23 0,49 0,47 0,80 1,00 0,75

LPX Buyout -0,05 0,21 0,25 0,41 0,62 0,75 1,00

Low correlation of all indices

Venture Economics data is only available on

a quarterly base with a six month lag andexhibit appraisal smoothing

CepreX data is available on a monthly basis,

but exhibit a 6-9 month lag.

All non-listed Indices show an appraisal

smoothing

Listed indices have stock market risk

See Appendix A for a construction idea of

adequate private equity benchmarks

Agenda




Denis Schweizer





Appendix A - Private Equity Benchmarks and Portfolio

Optimization

Motivation – Cumming, Haß and Schweizer(2014)




Denis Schweizer

Private equity is an established asset class, but its performance measurement is

ambiguous sharp measurement is important for e.g. portfolio optimization,risk management

Three different index methodologies are used with different strengths and weaknesses

Listed Private Equity Indices have the strength of daily data availability and (high) liquidity,

Overstated volatility due to stock market influences (data provider: LPX Group)

Appraisal Value Based Indices have the strength that there are no stock market influences, but

have a show appraisal smoothing and a one quarter time lag (Data provider: Thomson Reuters

VentureXpert)

Transaction Based Private Equity Indices have the strength that they are based on realized cash

flows (Case-Shiller approach), but can only be computed with considerable time lag (Data

provider: CEPRES)

Idea: Combine strengths of different index methodologies in one index toadequately represent private equity as an asset class

Idea of Constructing a Private EquityBenchmark




Denis Schweizer

Appraisal Value Based Index

De-Smoothed Monthly AVBI

Up-to-date De-smoothedMonthly AVBI

De-Smoothing and Re-scaling:

Getmansky, Lo, Makarov (2004)

Forecasting:

Gompers and Lerner (1998)

Autocorrelation-Structure of Appraisal ValueBased Private Equity Indices




Denis Schweizer

Lag 1 Lag 2 Lag 3 Lag 4

US Buy Out 0,3355 0,3005 0,2314 0,1508

US Venture Capital 0,6153 0,4998 0,3905 0,0450

January 1995 to December 2008 for the Lag 1 to 4 — bold formatting represents the significance at least at thelevel of 95%.

Correction for Autocorrelation – Intuition (1/2)




Denis Schweizer

New method by Getmansky, Lo und Makarov (2004) is especially for alternative

investments and real estate

Private Equity return series show autocorrelation du to appraisal smoothing, stale pricingetc.

The observed returns -

- are the weighted sum of the previous returns:

− . . . − , ∈ 0,1 , 0, … , , and 1 . . .

It follows:

∙ ≤ with ≡ . . .

Correction for Autocorrelation – Intuition (1/2)




Denis Schweizer

To solve the problem Getmansky, Lo and Makarov (2004) show a de-smoothing technique

1. step: Estimation of the parameters . . . with Maximum Likelihood (MLE)

2. step: Calculation of the true returns and variances

Example:

0 . 2 5 ∙ 0 . 2 5 ∙ − 0 . 2 5 ∙ − 0 . 2 5 ∙ −3 0.25

It can be seen that the true variance is four times higher then the observed variance

Private Equity – Benchmarking




Denis Schweizer

Appraisal Smoothing can be „corrected“ with method of Getmansky, Makarov und Lo

(2004) Increase in volatility from 10.36% to 17.77%!

The missing six months can be estimated with a forecast model which uses theinformation from the Listed Private Equity indices

Forecasts of Private Equity Indices – RegressionResults of the Forecast Model




Denis Schweizer

Running the following regression toidentify the driver of private equity

returns: ∙ ∙ BO

3 ∙

4 ∙

∙ℎ 6 ∙ 7 ∙ 8 ∙

9 ∙

∙ ∙

, ℎ 1, … ,

U.S. BuyoutU.S. Venture

Capital

Beta BetaConstant 0,0045** 0,006*

LPX Buyout 0,0204

LPX Venture Capital 0,113**

EA 0,4623** 0,733*

GDP 0,6511 2,070

Interest (short) 1,2993* 2,929*

Interest (long) 0,0017 -1,026Inflation 0,2797 0,180

Nasdaq 0,055NYSE 0,1076**

NYSE Liquidity -0,3196

Nasdaq Liquidity 1,204

Nobs 167 167F-Test 15,00** 11,68** Adj, R 2 40,28% 33,99%** and * indicate statistical significance at the 1% and 5% levels,

respectively.

Zeitraum: Januar 1995-Dezember 2008

Monthly Descriptive Statistics for Private EquityIndices




Denis Schweizer

US Buy Out

(smoothed) US Buy Out LPX 50

US Venture

Capital

(smoothed)

US Venture

CapitalLPX 50

Mean 0,72% 0,72% 0,58% 1,14% 1,14% 0,16%

Standard

Deviation1,42% 2,73% 6,09% 2,99% 5,72% 8,48%

Skewness -0,65 -1,14 -3,70 1,64 1,51 -0,32

Kurtosis 3,31 7,68 23,05 8,86 19,88 4,28LPM 0,30% 0,62% 1,63% 0,53% 1,12% 3,17%

CVaR (α= 95%) -2,73% -7,32% -18,00% -3,83% -11,10% -19,32%

Maximum Drawdown 23,34% 25,69% 79,96% 52,65% 57,17% 89,07%

arque-Bera 1 1 0 1 1 0 A Jarque-Bera value of 1 means that the assumption of the normal distribution at the level of 1% can be rejected.

January 1999 until December 2009

Descriptive Statistics for all Asset Classes




Denis Schweizer

NIKKEI

500 S&P 500 DJ EURO

STOXX

JPM

EUROPE

JPM

US JPM UK JPM

Japan NAREIT S&P GSCI HFRI LIBOR

Mean 0,41% 0,92% 0,27% 0,65% 0,51% 0,30% 0,71% 1,10% 0,96% 0,63% 0,45%

Standard

Deviation6,59% 4,13% 6,27% 2,81% 1,37% 3,70% 2,66% 3,75% 5,77% 1,71% 0,09%

Skewness 3,04 3,13 4,12 3,31 3,79 8,92 3,03 4,72 2,93 6,92 2,02

Kurtosis 0,52 -0,29 -0,11 0,32 -0,46 1,21 0,11 -0,56 0,07 -0,15 0,03LPM 2,44% 1,26% 2,23% 0,78% 0,33% 1,15% 0,72% 1,01% 1,84% 0,36% 0,00%

CVaR (5%) -10,10% -8,24% -13,81% -4,73% -2,63% -6,90% -4,79% -7,22% -10,40% -2,92% 0,29%

Maximum

Drawdown66,69% 43,07% 77,12% 23,16% 4,84% 31,45% 11,22% 26,32% 47,51% 13,08% 0,00%

arque-Bera 0 1 1 0 1 0 1 1 1 1 1 A Jarque-Bera value of 1 means that the assumption of the normal distribution at the level of 1% can be rejected.

January 1999 to December 2009

Correlation




Denis Schweizer

NIKKEI S&P500

DJSTOXX

JPMEurope

JPM US JPM

Japan JPMUK

NAREIT GSCI HFRI LPX VC LPXBO

PE BO PE VC SPAC

NIKKEI 1,00

S&P 500 0,52 1,00DJ

STOXX 0,54 0,87 1,00

PMEurope

-0,02 -0,19 -0,23 1,00

PM US 0,13 -0,04 -0,36 0,41 1,00

PM

apan 0,02 -0,20 -0,43 0,39 0,73 1,00

PM UK 0,10 0,05 0,00 0,56 0,35 0,21 1,00

NAREIT 0,34 0,75 0,71 -0,12 -0,27 -0,24 -0,09 1,00

GSCI 0,16 0,27 0,36 -0,26 -0,24 -0,40 0,09 0,11 1,00

HFRI -0,15 -0,33 -0,22 0,07 -0,10 -0,25 0,01 -0,21 -0,06 1,00

LPX VC 0,63 0,58 0,73 -0,04 -0,25 -0,28 0,12 0,55 0,32 -0,18 1,00

LPX BO 0,47 0,75 0,85 -0,08 -0,29 -0,33 0,16 0,72 0,39 -0,17 0,82 1,00

PE BO 0,05 0,04 0,03 -0,06 0,01 -0,05 0,05 0,05 -0,05 -0,04 -0,05 0,06 1,00

PE VC 0,03 0,07 0,14 -0,13 -0,15 -0,15 0,04 0,07 -0,05 -0,02 0,05 0,17 0,85 1,00

SPAC 0,37 0,50 0,63 -0,25 -0,44 -0,39 -0,06 0,47 0,42 -0,15 0,55 0,62 0,02 0,03

Zeitraum: September 2003-Dezember 2009

Efficient Multi-Asset Portfolios




Denis Schweizer

Portfolio weights forPrivate equity indices

Mean Standarddeviation

LPM CVaR VaR MaxDD Sharpe-Ratio

Minimum-variance portfolio

without PE7,26% 3,04%*** 0,00% -0,66%*** -0,37%*** 1,12%*** 1,73***

Minimum-variance portfolio

with PE7,30% 2,11%*** 0,00% -0,26%*** -0,08%*** 0,52%*** 2,51***

Average-variance portfolio

without PE

8,64% 3,90%*** 0,00% -0,90%*** -0,53%*** 1,61%*** 1,71***

Average-variance portfolio

with PE8,65% 3,57%*** 0,00% -0,69%*** -0,45%*** 1,21%*** 1,86***

Maximum yield portfolio

without PE10,01% 6,43%*** 0,01% -1,81%*** -1,33%*** 3,25%*** 1,26***

Maximum yield portfolio

with PE9,97% 5,65%*** 0,01% -1,44%*** -1,04%*** 2,50%*** 1,41***

***, **, And * indicate statistical significance at the 1%, 5%, and 10% levels for a different average return, standard

deviation, LPM, CVaR, VaR, and MaxDD for a portfolio without private equity in comparison to one with private equity.For the Sharpe ratio it is tested whether it is greater for the portfolio of private equity compared to the portfolio withoutprivate equity.

Optimization result of the multi-asset portfolios

Efficient Multi-Asset-Portfolios (1/3)




Denis Schweizer

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%20%

5.60% 5.80% 6.00% 6.20% 6.40% 6.60%0%

2%

4%

6%

8%

10%

12%

P r i v a t e E q u i t y P o r t f o l i o W e i g h t

Expected Portfolio Return

V o l a t i

l i t y

Minimum-Variance-Optimization

Efficient Frontier (VentureCapital Appraisal Value BasedBenchmark)

Efficient Frontier (LPX)

Efficient Frontier (Venture

Capital Appraisal Value BasedPrivate Equity Index)

Venture Capital Appraisal ValueBased Benchmark Portfolio Weight

LPX Portfolio Weight

Venture Capital Appraisal ValueBased Private Equity IndexPortfolio Weight





Denis Schweizer

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%20%

5.60% 5.80% 6.00% 6.20% 6.40% 6.60%0%

1%

2%

3%

4%

5%

6%

7%

8%

P r i v a t e E q u i t y P o r t f o l i o W e i g h t


L o w e r P a r t i a l M o m e n t 2

LPM-Optimization












Denis Schweizer

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%20%

5.60% 5.80% 6.00% 6.20% 6.40% 6.60%0%

2%

4%

6%

8%

10%

12%

14%

16%

P r i v a t e E q u i t y P

o r t f o l i o W e i g h t


C o n d i t i o n a l V a l u e a t R i s k

CVaR-Optimization








Portfolio-Risk in Correspondence to ChosenPrivate Equity Proxies




Denis Schweizer

0

100

200

300

400

500

600

700

800

900

- 1 4 . 4 7 1 %

- 1 2 . 9 9 0 %

- 1 2 . 0 0 2 %

- 1 1 . 0 1 4 %

- 1 0 . 0 2 6 %

- 9 . 0 3 8 %

- 8 . 0 5 1 %

- 7 . 0 6 3 %

- 6 . 0 7 5 %

- 5 . 0 8 7 %

- 4 . 0 9 9 %

- 3 . 1 1 1 %

- 2 . 1 2 4 %

- 1 . 1 3 6 %

- 0 . 1 4 8 %

0 . 8 4 0 %

F r e q u e n c y

CVaR

20% Private Equity

LPX

Venture Capital Appraisal Value Based Benchmark

Buy Out Appraisal Value Based Benchmark

0

100

200

300

400

500

600

700

800

900

- 1 3 . 7 6 7 %

- 1 2 . 3 5 7 %

- 1 1 . 4 1 7 %

- 1 0 . 4 7 7 %

- 9 . 5 3 8 %

- 8 . 5 9 8 %

- 7 . 6 5 8 %

- 6 . 7 1 8 %

- 5 . 7 7 8 %

- 4 . 8 3 8 %

- 3 . 8 9 8 %

- 2 . 9 5 9 %

- 2 . 0 1 9 %

- 1 . 0 7 9 %

- 0 . 1 3 9 %

0 . 8 0 1 %

F

r e q u e n c y

CVaR

10% Private Equity

LPX

Venture Capital Appraisal Value Based Benchmark

Buy Out Appraisal Value Based Benchmark

Technical Appendix: De-Smoothing Method byGetmansky, Lo and Makarov (2004)




Denis Schweizer

Statistical Details (1/6)




Denis Schweizer

is the true return of a private equity segment like venture capital and satisfies thefollowing one-factor model:

Λ

,

0,

Λ,

~

,

≡

However, the true return is not observable, but only the reported return in t which ismodeled as follows: − .. . − ,

∈ 0,1 , 0, … , , and

1 .. .

The following statistical properties are derived from the above described smoothingprocess:

∙

≤

≡ ∙ ≥ ≡

(continued)





Denis Schweizer

, − +−= 0 ≤ ≤ ,0 > ,

whereas

≡ .. .

≡ .. .

≡ 1 .. .

, ≡ . It can be derived from the statistical properties of the observable returns that the expected

returned is not changed, but the variance is lower therefore the Sharpe ratio is increased bythe factor





Denis Schweizer

Estimation procedure (Maximum Likelihood) for a general form of smoothing. Whereas stands for the mean-adjusted return-generating process , with the following properties for

:

−.. .− 1 .. .

~ 0 , , from the previous it is obvious that

is a moving-average-process of order k or a MA( k ).





Denis Schweizer

For given observations ≡ ⋯ ′ one can write the following Likelihood-function

ℒ , 2 − − ′− with ≡ ′ , whereas ≡ ⋯ ′ and the co-variance matrix is a function of the parameter and. It can be shown that ℒ , ℒ , and therefore a further identification is

not necessary

Brockwell and Davis (1991) show that we can re-formulate the Likelihood-function to

ℒ , 2 − ⋯ − − 12 −= ,

whereas ⋯ ′, 0, , … , − , ≥ 2 and

+ +

is the so called one-step-ahead-estimator, and is calculated recursive for 1 , … ,





Denis Schweizer

For given observations

≡ ⋯ ′ one can write the following Likelihood-function

ℒ , 2 − − ′− w ith ≡ ′ , whereas ≡ ⋯ ′ and the co-variance-matrix is a function of the parameter and. It can be shown that ℒ , ℒ , and therefore a further identification is

not necessary

Brockwell and Davis (1991) show that we can re-formulate the Likelihood-function to

ℒ , 2 − ⋯ − − 12 −= ,

whereas ⋯ ′, 0, , … , − , ≥ 2 and

+ +

is the so called one-step-ahead-estimator, and is calculated recursive for 1 , … ,


Af i l diff i i f h Lik lih d f i i h i i b i h




Denis Schweizer

After partial differentiation of the Likelihood-function with respect to it is obvious that

the Maximum-Likelihood-estimator for

is given by

− −= , which results in

ℒ log − −= .

This Likelihood-function can be minimized in

, subject to its side constraints. Under

above given specification is invertible for the set: 1 , < 1 2 , < 1 2 and the Maximum-Likelihood-estimator

for satisfies the following conditions:1 ,

~ 0 , , 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 2 .

Agenda




Denis Schweizer





Appendix B - Are Private Equity Investors Boon or Bane for an

Economy?

Appendix B - Are Private Equity Investors Boonor Bane for an Economy?




Denis Schweizer

In 2011 Private Equity and Hedge Funds AreRegulated on EU Level

Financial market crisis and the so called „Heuschreckendebatte“ have lead to a demand for a more




Denis Schweizer

Structure of the new RegulationImplications for Private Equity

Reasons for Regulation

Prevention of debt overload and „Asset

Stripping“ of portfolio companies

Increasing transparency of private equity fundsfor the investors and potential target companies

Regulation Procedure

Control of debt volume for portfoliocompanies (e.g. LBOs)

Extensive duty to supply information for

investors regarding the strategic intentions within acquisitions of publicly listed companies

with more than 250 employees

Distribution of equity and special reserves are

not possible with two years after the acquisition

Source: Bundesfinanzministerium, Financial Times Deutschland

„

intensive regulation since the industry was regulated on a low level only

The new regulation was passed at November 11, 2010 on EU level and has to be implemented in

national law until 2013 for all member states

ESMA (EU-supervision

of securities)

ESRB (European

Systemic Risk Board)

National controlling

institution

EU-FundsFunds from Third

Country

Funds report:

Leverage level

Self given leverage restrictionFive main creditors Target markets / concentration risk Further involved managers

2013 2018Issue of a

EU-wide

accreditation

Issue

„EU-Pass-port“

Development of technicalstandards

Handle of a central register

Connect between nationalregulation authorities

Consolidated considerationof the controllinginstitutions

Evaluation of systematicrisk

Literature




Denis Schweizer

Brockwell, Peter J., and Richard A. Davis, 1991, Time Series: Theory and Methods (2nd

Edition, Springer, New York).

Cumming, Douglas, Lars Helge Haß and Denis Schweizer (2013): Portfolio Optimization with Private Equity, Journal of Banking & Finance 37 , 3515-3528 .

Getmansky, Mila, Andrew W. Lo., and Igor Makarov, 2004, An Econometric Model ofSerial Correlation and Illiquidity in Hedge Fund Returns, Journal of Financial Economics 74,

529-609.

Geltner, David M., 1991, Smoothing in Appraisal-Based Returns, Journal of Real Estate

Finance & Economics 4, 327-345.

Gompers, Paul A., and Josh Lerner, 1997, Risk and Reward in Private Equity Investments: The Challenge of Performance Assessment, Journal of Private Equity 1, 5-12.

Gompers. Paul A., and Josh Lerner, 1998, What Drives Venture Capital Fundraising?,Brookings Papers on Economic Activity-Microeconomics (July), 149-92.

Motivation Literature Research approach Results Model Summary/outlook



Are Private Equity Investors Boon or Bane for anEconomy? – A Theoretical Analysis

Sebastian Ernst Christian Koziol Denis Schweizer

WHU – Otto Beisheim School of Management

59th Annual Meeting of the Midwest Finance Association

Las Vegas, February 24-27, 2010

Sebastian Ernst/Christian Koziol/Denis Schweizer Are Private Equity Investors Boon or Bane for an Economy? 1


Motivation

http://find/



Too high leverage

Short-term profits

”Locusts”

Typical criticism:

at the cost of

long-term investments

Private Equity (LBO)

Source of financing

New, superior

better monitoring

Arguments for PE:

management concept

Lower agency costs,

for companies



Literature

http://find/



• Empirical studies do not document negative impact of PE:

Significant increase in productivity and operating profit(Kaplan (1989), Lichtenberg/Siegel (1990), Muscarella/Vetsuypens

(1990), Smith (1990), Harris et al. (2005))

No significant negative effect on employment and investment(Amess/Wright (2007), Davis et al. (2008))

• Limitations of empirical studies:

Comparison to situation without PE acquisition not possible

No identification of reasons for potential negative impact

=⇒ Model-theoretic analysis required



Research approach

http://find/



• PE investor negative for economy if:

Takeover of a target company

Inefficient investment decisions (in comparison to standard investor)

• Goal of the paper:

Modeling of both acquisition and investment decisions

Identification of characteristics that cause inefficient behavior



Results

http://find/



• Characteristics of PE that do not result in inefficient behavior:

Higher target return

Operational improvements/productivity increases

Lower risk aversion

Shorter investment horizon

• Characteristics of PE that may result in inefficient behavior:

Higher leverage

Better information about target company


http://find/

http://goback/




Model: basic structure



• Investors identical except that P has higher target return: r S < r P

• Investors are risk-neutral with objective function:

OF i = E(Πi ) = O (x i ) − (x i + p i ) · (1 + r i ), i ∈ {S ,P }

• Goal: comparison of acquisition price p i and investment volume x ∗i

• Allocation inefficient if

i x := arg maxi ∈{S ,P }

x ∗i = i p := arg maxi ∈{S ,P }

p i



Results

http://find/



• Characteristics of PE that do not result in inefficient behavior: Higher target return


Lower risk aversion



Higher leverage




Model: higher target return (base case)

• Optimal investment volume x∗ implicitly given by:

http://find/



• Optimal investment volume x i implicitly given by:

O (x ∗i ) = 1 + r i , i ∈ {S ,P }

• Maximum acquisition price p i :

p i = O (x ∗i )

O (x ∗i

) − x ∗i , i ∈ {S ,P }

• Result: S pays higher acquisition price and invests more than P

=⇒ Allocation efficient

=⇒ PE investor does not take part in the market



Results

http://find/





Lower risk aversion



Higher leverage




Model: differences in risk aversion

http://find/

http://goback/



• Investor S becomes risk averse with preference function:

OF S = E(ΠS ) − b · V(ΠS )

• Optimal investment volume x ∗S implicitly given by:

1 + r S = O (x ∗S ) · 1 − 2 · b · σ2 · O (x ∗S )

• Maximum acquisition price p S :

p S = O (x ∗S )O (x ∗S )

· 1 − b · σ2 · O (x ∗S )1 − 2 · b · σ2 · O (x ∗S )

− x ∗S



Model: differences in risk aversion

p i σ =

r P −r S

2·b ·O (x ∗S

)·(1+r P )

http://find/



σ

pi

p P

p S

σσ

x ∗S > x ∗P x ∗S < x ∗P

(S

) ( + P )

σ = (1+r

P )·((1+r

S )·(x ∗

P −x ∗

S )+O (x ∗

S ))−(1+r

S )·O (x ∗

P )

b ·(1+r P )·O (x ∗

S )2

=⇒ Situation possible where S acquires the companybut P would invest more

=⇒ No negative impact of PE investor



Results

http://find/





Lower risk aversion



Higher leverage




Model: leverage

http://find/



• P can take on debt with volume D , r D < r P

• Result: P takes over companies when debt volume and spreadr P − r D is high

• Investment volume of P does not change

=⇒ Leverage increases maximum acquisition price of P without changing its investment behavior

=⇒ Inefficiency caused by P possible



Results

http://find/

http://goback/





Lower risk aversion



Higher leverage




Model: informational asymmetries about target company• Uncertainty about quality (µ) of target company for S :

http://find/



After acquisition/before investmentBefore acquisition

z

µ = z G ⇒ Good firm

µ = z B ⇒ Bad firm

π

1 − π

• P has no information problem

• Result: S invests more and acquires bad firms

• P acquires good firms if uncertainty ( z G

z B ) is high and successprobability (π) small

=⇒ Inefficiency caused by P possible



Summary/outlook

http://find/



• Theoretical foundation of the debate about the economic impact of

private equity transactions

• Identification of reasons for inefficient behavior:

High leverage

Informational asymmetries

• Separation between relevant and plausible but non-relevant reasons

• Political implications:

Debt restrictions Enhancement of transparency


http://goforward/

http://find/

http://goback/

3. private equity

Documents