swamy2009selection

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This version of the Selection Supersedes Access paper was created for the students of Finc-190, Private Equity at Harvard University Extension School spring 2009. This

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PAGE 1Selection Supersedes Access

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1Footnote1: The past works includes experiments by Lerner et al that tried to establish the superior performance of endowments over pension funds(Smart Institutions, Foolish Choices) or the exploration of persistence by Kaplan, Schoar. However, no work ever examined the causality or reality of

persistence over a long time frame.

Private equity is one of the fastest growing yet most opaque industries today.From its inception in the early 50s to today, its been at the center of the some of

the most powerful entrepreneurial and wealth creation stories. Not only has theindustry created hundreds of millionaires in both investors and operators, but it

has also launched, nurtured and revived some of todays most successfulbusinesses.

According to PEI, Thompson and other sources, the PE equity market has beengrowing rapidly and reached $2.5 Trillion in 2008. About 60% of the allocation or

$1.5 Trillion is allocated to venture and buyout funds and the remainder isallocated to distressed, mezzanine and other funds. It is not just the sheer size ofthis market that is compelling but the growth rate is extraordinary as well. In a littleover a decade from 1980 and 1994, the amount of private equity outstanding

rose from less than $5 billion to $100 billion at CAGR of 23%. In the first quarter of2008 alone, U.S. private equity firms raised $58.5 billion up nearly 32% over the$44.3 billion in the first quarter of 2007.

Buyout funds alone now control over $900 Billion in capital not including leverage,and venture capital funds control another $350 Billion. Including the impact ofleverage, they have an aggregate buying power of $3 Trillion; thats enough tobuy more than 40 McDonalds, 10 GEs, and 500 General Motors. What were 296

VC and 40 buyout firms in 1985 has evolved to 741 VC firms and 588 Buyout firmsin 2007. Inspite of the industry growth, LPs are investing less and less in new firms.From 2002 to 2006, while the total number of funds have grown by a CAGR of

7.85% and the AUM have grown by 43.9%, the number of new funds have onlygrown by 1.34% and new fund AUM has only grown by 35%. Most of the newgrowth comes from new buyout funds; in the venture industry the total ventureAUM has grown at a CAGR of 30.7% as compared to new venture AUM at half

that rate or 16.2%. In the same period, the number of new venture funds hasshrunk at -2.6% as compared to the total number of venture funds that has grownat a CAGR of 3.58%.

The remaining private equity alternatives such as distressed and lending funds areemerging categories that show the same pattern of fragmentation. Thisfragmentation, coupled with the lack of transparency, makes it difficult for

investors to assess and compare funds. It has created an environment where

rumors run rife and facts are rarely consistent. While many1 such as Calpers, have

tried and somewhat succeeded at making private equity fund performance

more transparent and objective, they have not focused on debunking some ofthe myths surrounding funding behavior and investor selection.

Our aim has been to review and challenge the key myths that have historicallyguided and continue to guide investor selection behavior by analyzing the

industry-wide and investor-specific performance data that has only recentlybecome publicly available in the industry.

Introduction

Sections

1 Introduction2 Common Beliefs & Myths3 Analysis, Contention & Results4 Refuting Myths5 Conclusions

Note on FOIA

Both the US and UK government

freedom of information acts require

disclosure by government agencies

on performance of PE vehicles. The

US government FOIA, Title 5, 1966,

together with various state

legislations from 1980 through 2006,

provided us the means to obtain thesource data.

Selection Supersedes Access:

When does experience pay in Private Equity?Gitanjali Swamy, Bhavin Shah, Nitin Nohria, Daniel Bergstresser, Irina Zeltser


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One dominant myth that has become a crux of driving LP behavior is thatinvesting in successive funds of same firms or individuals is much safer, more

rewarding than investing in an emergingmanager. This is the focus of ourresearch. According to Northern Trust Global Investments (NTGA) while 40% ofreturns come from emerging managers, most LPs such as Calpers, NYCERSallocate 1% or less to emerging manager programs. A vast majority of pension

funds, endowments, institutions, etc. make it a policy not even to look at or investinemerging manager funds. In fact, this situation has been getting progressivelyworse; the NVCA reports that the percentage of new funds vs. follow-on fundsdecreased from 33% in 2002 to less than 21% in2007.We have been acting onone of those urban myths that cannotbe proven, but can easily be disproven.The aim of our exercise is to either prove or disprove the myth of persistence and

to start an exploration of the real causes of better performance in private equityfirms.

In order to research and analyze this myth, we identified and challenged anumber of supporting beliefs that drive investor behavior. Investors have

traditionally believed that

1. Historical returns are a predictor of future performance and Persistenceof performance will continue.

2. Experienced fund managers will be more successful (what aboutexperienced investors or operators?) (i.e., better deal flow, edge indeals, better financing, staff selection, etc.)

3. It is less risky to invest in tangential/new businesses founded byexperienced fund managers than to invest in emerging managers with

directly relevant skill sets

This is based on several fallacious myths that the industry believes. Firstly, theindustry believes that experienced firms will deliver better returns, perhaps due to

their experience in the industry, history of working together and network of

relationships in the industry. The industry believes that experienced managers in

an irrelevant old category are still better bets in a new category than anemerging manager with differentiable expertise in the same. E.g. a portfolio

manager would rather invest in a new India growth fund offered by an

experienced GP manager specializing in communications early-stage venture

investing in Boston than a new fund composed of a team with individual teammembers have 20 years experience in Indian private equity. The industry believes

that emerging managers teams will not have the source, operating and exit skill

set, network, experience to generate superior returns. Finally, LPs believe that

investing in emerging managers does not present rewards commensurate with

the risk being taken.

Thus, the structure of the alternative investment management industry is gearedtowards returning fund managers with a lot more obstacles, challenges and

straight-out refusals for emerging managers. In addition, the structure is inherited

biased towards a specialization model inherited from the public market investing,

which focuses only on financial specialization (small cap, mid cap, large cap)

and not optimized for private equity, which is as much about active portfolio

management with value add from industry, geography and financial expertise.

This mentality or approach is true with respect to type of investment fund (i.e.,

venture, buyout, PE, etc.), industry specialization offund (i.e., technology,industrials, healthcare, etc.) and size of fund (i.e., early-stage, lower middle-

market, middle-market, large-cap, etc.)

Common Beliefs and Myths

Note on Dataset

Our dataset included all publicly

disclosed pension and endowment data.

In particular, our dataset focused on 560

funds sponsored by 280 firms. 300 funds

had more than 1 successor and 132

funds had more than 3 successors. The

start years ranged from 1978 to 2000.

The funds were distributed 36% venture,

14% balanced, 29% buyouts. The funds

were predominantly in the US with over

90% centered there but had 4% in

Europe and 3% in Asia. The funds are

distributed equally among all industries

with Biotech, Medical, Communications,IT and Retail dominating. The mean (IRR)

of the data was 11.45%, median 8.45%

and standard deviation 33%.We made

almost no subjective assessments to

segment, classify, manipulate data. The

product, industry, geography

segmentation was collated from the LP

sources where disclosed and completed

with data from the companys own

website.


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2

2Footnote2: The correlation between the performance of N (N=1, 2, 3, 4.10) past funds and the next N+1th fund shows decreasing correlation as N is increased. In short, there

is limited persistence of performance. Contrarily, there is decreasing correlation and in some cases even an inverse (negative) correlation with increasing funds. A robust

regression which down-weighted the outliers showed an even more startling pattern that showed a monotonically decreasing and almost immediately negative correlation at

N=2 onwards. The correlation started at 0.009 and decreased monotonically through N=7 to -0.39. We used the Stata environment to perform multivariate regression analysis.

Our analysis adjusted for vintage variation in performance by creating an independent variable for each vintage year and using it as part of the regression analysis .

Analysis & ContentionThe private equity industry has grown up believing in fallacy of persistence ofperformance; good funds continue to do well and bad funds continue to badly.

We have been acting on one of those urban myths that cannot be proven, butcan easily be disproven. In fact, the traditional belief is actually completelywrong. Our results show that contrary to common perception, Net IRR (net of fees

and carry) actually shows a pattern of decreasing persistence beyond a smallwindow of 1-3 funds. From an LPs perspective Net IRR is a far more meaningfulmetric since it reflects eventual returns to the LP and not the GP.

On an anecdotal basis, there are examples of both lack of persistence andpersistence in performance. For example, A Partners (a top tier Hamilton lanerated firm) showed vintage 1998, 2000 returns of -17% and -26.8% respectively.These were in no way predicted by their 1989, 1993, 1996 funds with IRRs of 14.7%,

77.8% and 189% respectively. On an average, Funds in the top 10% (decile) inperformance showed a drop of more than 30% from Fund 1 to Fund 2 and Fund 3.The top decile showed a drop of more than 50% from Fund 4 to Fund 5 andFund6. Finally, among firms having 5 or more funds, 80% showed a decline of

more than 50% from the 5th fund to the 7th fund. But while anecdotal evidence

may suggest patterns, the real proof comes from a comprehensive statisticalanalysis.

The objective of our exercise was to successfully prove or disprove what makesbetter or worse private equity firms. The first step was to examine whether anypersistence existed; i.e. did good firms continue to do well and bad firms continue

to do badly. In order to see if past performance was in any way a determinant offuture, we conducted our experiments on nearly 600 closed funds from the publicdisclosures of the top pension funds. In particular the classifications we compareand correlate the (net of fees) performance of N successive funds of a GP with

the net performance of the N+1th fund. N was varied from 1 to 10. I f indeedpersistence held, the correlation coefficient would go up or stay constant butwould never go down. A negative correlation coefficient would indicate the

reverse of persistence.To summarize, our experiments show that in fact the performance of N+1th fund

does NOT directly track2 the performance of the prior N (N=1,2,3,4,.10) funds. In

short, good funds do not continue to do well and bad funds do not continue todo badly. In fact, our comprehensive analysis shows that persistence islimitedand at most restricted to a window of 3 funds. In general, there is decreasing

correlation between successive funds performances.In conclusion, the industry belief in the persistence of returns is a fallacy. The

analytical selection of new good managers overwhelmingly trumps theadvantages of relationship access to existing managers in good private equity

fund management.

Note on Analysis

A simple ordinary linear regression showed

an increasing positive correlation for values

of N varying from 1 to 3, going from 0.52 to

0.9. This clearly implied the persistence of

returns for the first 3 funds. However, after

fund 3, 4, the correlation changed direction

and became progressively smaller with N

going to 7. It started at 0.9 and decreased

monotonically to 0.22. Eventually it turned

negative.

A robust regression which down-weighted

the outliers showed an even more startling

pattern that showed a monotonically

decreasing and almost immediately

negative correlation at N=2 onwards. The

correlation started at 0.009 and decreased

monotonically through N=7 to -0.39.

The standard quantile regression showed

exactly the same pattern with a minor

flattening of the curve at N=1, 2. The

correlation started at 0.2 and decreased

monotonically to -0.3 at N=7. It turned

negative at N=5. A winsorized regression

that eliminated the outliers all together

showed a similar pattern with a slower rate

of increase through 1, 2 from 0.22 to 0.39

and flattening of the correlation through

3,4, followed by a rapid monotonic decrease

going from 0.39 down to -0.1.

Figure 1. Ordinary Linear Regression

Correlation Fund Performance vs. Prior FundPerformance.


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Refuting the Myths

In fact, our experiments and analysis of underlying data show that none of thecommon myths in private equity investing hold in reality.

Historical returns alone are NOT a predictor of future performance in privateequity firms and Persistence of performance will NOT continue. In fact, ourcomprehensive analysis shows that persistence is limited and at most restricted

to a window of 3 funds. In general, there is decreasing correlation betweensuccessive funds performances. A simple ordinary linear regression showed an

increasing positive correlation for values of N varying from 1 to 3, going from0.52 to 0.9. This clearly implied the persistence of returns for the first 3 funds.

However, after fund 3, 4, the correlation changed direction and becameprogressively smaller with N going to 7. I t started at 0.9 and decreasedmonotonically to 0.22. Eventually it turned negative. A robust regression which

down-weighted the outliers showed an even more startling pattern thatshowed a monotonically decreasing and almost immediately negativecorrelation at N=2 onwards. The correlation started at 0.009 and decreasedmonotonically through N=7 to -0.39. This result clearly implied that in general

persistence does not apply except for a small window and if the outliers wereless pivotal, persistence did not hold at all.Experienced fund managers will NOT always be more successful l. It is not just

the years of experience but the nature of experience. Moreover, experiencedfund managers tend to raise their fee/carry compensation. Thus, the net IRR orreturns to the investor actually does not show a superior return even when theperformance goes up. To illustrate this point, we looked at the top 10% (decile)

in our data set. We aggregated and averaged the performance data by fundnumbers. On an average, net IRR performance dropped 30% from Fund 2 toFund 3 and over 50% from Fund 5 to Fund 6 or Fund 7.

It is NOT less risky to invest in tangential/new businesses founded byexperienced fund managers than to invest in emerging managers with directlyrelevant skill set. Once again our correlation results disprove this myth. As

explained earlier, our comprehensive analysis shows that persistence is limited

and at most restricted to a window of 3 funds. In general, there is decreasingcorrelation between successive funds performances. We compared thecorrelation of ex

Figure 2. Data Extraction, Clean-up and Analysis Process

Figure 2. Robust Regression Correlation

Fund Performance vs. Prior Fund

Performance.

Note on Experiment

We adjusted for the impact of vintage in

all experiments by creating an extra set

of independent variables that reflected

the vintage. The correlation was run

using these independent variables and in

effect adjusting for the impact of

vintage. Some variables that we wish we

had access to but did not for this set of

experiment were, the Write-down,

Organizational Turnover and Fee/Carry

terms. These variables would allow us to

see the impact of and adjust for changes

in the fund team, the pinpoint the cause

of return as an overall portfolio vs. single

company impact. For instance Google

was singlehandedly responsible for the

returns of Kleiner vintage 1996 fund.

Fee/Carry terms would allow us to

determine whether the degradation in

persistence were due to a decrease in

the quality of the investment choices or

due to increase in compensation

demanded by a successful firm. We didnot adjust for management changes in

fund or subsequent significant fund size

changes by firm managements


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3 The same pattern was show by other statistical metrics such as mean+standard deviation, max etc. This data suggests that in fact, experiencedfund managers were NOT more successful.

ConclusionsIn conclusion, we found that persistence of returns is a fallacious argument tojustify LP investment choices in particular GPs. In reality, selection significantly

supersedes access and therefore investors must spend more time in finding newGPs with the right strategic, operational and financial attributes, rather thanassume that proprietary access to past top-performers will guarantee futurereturns.

We believe that this result may be attributable to several factors.

Impact of successful firms increasing fees/carry. The increases inperformance dont translate to increases in the returns to the LPinvestors because successful funds increase their share (fees/carry) ofthe returns. This phenomenon has been observed in many industriesincluding the mutual fund industry. This mis-alignment of manager

incentives and investor incentives results in poor returns to the investor.A good illustration of this came from the 2005 Mayfield XII, whichraised its fee to 2.5% and carry to 30% as compared to the industrystandard of 2%/20, on the grounds that the1995 Mayfield IX, their most

recent closed fund, returned a 49% IRR. The prior fund $1Bil, 2000Mayfield XI, wasnt closed and was only X% invested. LPs such as theKirsch foundation exited the fund with an IRR of -1.3%. Both Harvard

and MIT declined to participate because of extortionate fees butMayfield closed $325Mil irrespective through investors such as the

State of Alaska.

Impact of industry and macro economic cycles/changes. Thusexpertise, relationships in any particular industry or product are not

perpetually valuable. A good firm must be willing to continually re-invent itself and experienced fund managers with one specialization

do not guarantee future success either in the same industry or atangential one. Matrix Partners, one of the best east coast firmsreturned a 213% and 516% IRR for 1995 Matrix IV and 1998 Matrix Vfunds based on its investments and expertise in the communications

sector. In particular, the returns were very sensitive to the Cascadeand Sycamore investments both of which were communicationscompanies founded by a particular entrepreneur. By 2000, the

entrepreneur started funding his own companies and no longerworked with Matrix the communications sector collapsed and 2000

Matrix VI returned a dismal -8%.

Impact of GP staff turnover. The private equity organizationsthemselves change and with a new set of partners/investing

professionals; the firm is not the same. It cannot be reasonablyexpected that LPs will get the same returns. With the departure of

Luminaries such as Vinod Khosla, Kevin Compton, John Doerr was thesole remaining star at Kleiner Perkins. None of the almost brand new

stable of partners/principles all of whom were luminaries but notventure capitalists were able to provide returns. Since Doers 1999Google IPO, the firm has yet to demonstrate a killer IPO. The partner

and investment staff turnover didnt impact Kleiners ability to raisefunds, just its ability to deliver returns.

Figure 3. Percentage Num of First Funds vs.

Follow on Funds.

Note on Results

Most of the results are statistically

significant. But some data points should

be ignored. In the OLP, The significance

(P


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Impact of capital oversupply. The increasing amount of capital, increasing fund

size, and increasing number of funds are not balanced by a correspondingincrease in investment talent. Thus, firms can neither find high quality talent tosupport increased fund deployment nor do they have the time to develop talentin-house. In 2007, Blackstone raised $21.7 billion for the world's biggest private-

equity fund, just as a global credit crunch slowed leveraged buyouts. The fund wastriple the $6.45 billion pool that Blackstone raised five years ago. These funds wereraised over the year inspite of the catastrophic earnings, revenue and share price

collapse. Over the same year, Blackstones revenue fell 94 per cent from $1.23billion to $68.5 million, earnings collapsed from more than $1Bil to a net loss of

$255Mil and the stock fell from its post IPO price of $35/share to $12/share.

Impact of getting rich fat and happy when rewards independent of performance.Principals in a successful firm lose their incentive to perform after reaping inordinate

rewards that are not tied to performance. There is significant incentivemisalignment between fund managers that reap heavy rewards from

management fees alone and investors whose returns are determined byperformance. Stephen Schwarzman, chairman and cofounder of the

aforementioned Blackstone Group, owns 39% of Blackstone, which operatesleveraged buyout and real estate funds, and funds of funds. Last year Blackstone

earned $2.3 billion on an average of $62 billion in assets. Schwarzman took home:

$940 million. The real kicker is that he only paid 15% federal income tax on thatincome. That's the same tax bracket that a single worker is in if she earns between

$16,575 and $40,600 (assuming she claims the personal exemption and standarddeduction). A single worker earning between $40,600 and $85,850 is in a 25%

bracket. Net net, there is a limited motivation for an investment professionalrewarded in the aforementioned manner to perform.

The excessive focus on returning funds and lack of focus on emerging funds is neither

justified nor a safe strategy. It is not geared to generate the best returns for the corpus,investors, clients, etc. The best investment strategy is to re-invest in the same firms at most

within a small window of opportunity of about 3 funds/terms or about 7 years. Instead an LPmust continually seed new funds in order to continue to reap returns over the long run.

We recommend a 30-50% allocation for emerging managers as opposed to the minisculepercentage that LPs traditionally allocate. Coincidentally, that is strategy that Smart Lps

like Yale Endowment etc. also apply in practice.Sadly, the industry is doing just the opposite. From 2002 to 2006, the percentage of new firmsvs. old firm funds raised has dropped from almost 30% down to less than 22%. During that

time, while the total number of funds has grown by a CAGR of 7.85% and the AUM havegrown by 43.9%, the number of new firm funds have only grown by 1.34% and new fundAUM has only grown by 35%. Most of the new growth comes from new buyout funds; in theventure industry the total venture AUM has grown at a CAGR of 30.7% as compared to new

firm venture AUM at half that rate or 16.2%. In the same period, the number of new venturefirm funds has shrunk at -2.6% as compared to the total number of venture funds that has

grown at a CAGR of 3.58%.

In effect, the industry is creating an unstable situation that is progressively biasing theinvestment selection towards poorer returns. It is a myth that investing in experiencedmanagers guarantees predictable or above average returns. However, having disproven

this myth does not mean we have completely identified what makes a better manager.

We are still conducting our experiment and future publications will include.

- Market trends/shifts- Manager/partner departures- Spinoffs vs. truly new starts- Geography- Larger fund sizes vs. same fund sizes- Fee vs. carry trade-offs

Our next step is to expand the analysis to account for variations in industry, geography and

product focus. Following that, we would be able to do a detailed causal analysis thatdeduces which factor strategy, management, culture, diversity, vintage years, incentivesand needs (net worth), fund size, fee vs. carry trade-offs, motivations etc. actually determinethe performance.

Figure 4. First Time vs. Follow-on Venture

Funds

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