lbos from 1999 to 2009
TRANSCRIPT
LEVERAGED BUYOUTS FROM 1999-2009: IS BIGGER REALLY BETTER?
Roland Cornelius Südhof
TC 660H
Plan II Honors Program The University of Texas at Austin
May 1, 2010
Michael B. Clement, Ph.D. Department of Accounting
Supervising Professor
Jonathan Cohn, Ph.D.
Department of Finance Second Reader
2
ABSTRACT
Author: Roland Südhof
Title: Leveraged Buyouts from 1999-2009: Is Bigger Really Better?
Supervising Professor: Michael B. Clement, Ph.D.
As the amount of capital and credit available to private equity surged from 2000 to
2007, many private equity firms dramatically increased the size of their transactions, commonly
referred to as leveraged buyouts (LBOs). What was the rationale behind these increasingly large
LBOs? This paper presents the hypothesis that larger transactions opened up a new group of
potential targets and allowed private equity firms to acquire companies on more favorable
terms due to less competition from other financial buyers. Based on a study of 446 public-to-
private LBOs announced between 1999 and 2009, I conclude that the relationship between size
of the target (measured by the total transaction value of the LBO) and valuation (measured by
Enterprise Value to EBITDA) is different for small and large LBOs. For LBOs with transaction
value ranging from $100 million to around $5 billion, the LBO price tends to increase with the
size of the target. However, evidence suggests that once an LBO exceeds around $5 billion in
transaction value, price remains static as deal value increases. After exceeding $10 billion in
transaction value, price falls substantially with increases in deal size. This result supports my
hypothesis that private equity firms pursue larger deals in pursuit of better deal economics.
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Table of Contents Introduction .......................................................................................................................................... 4
Section 1: The Dynamic Transformation of Private Equity ................................................................ 9
1.1 Private Equity From 1980-1999 ................................................................................................. 9
1.2 Planting the Seeds of the Boom: 1995-2003 .......................................................................... 14
1.3 The Fundraising Boom of 2003-2007 ...................................................................................... 17
1.4 The Role of Credit in LBO Activity............................................................................................ 20
1.5 Capital and Credit Concentrated in Large Funds.................................................................... 22
1.6 The Institutionalization of Private Equity ............................................................................... 27
Section 2: A Survey of Academic Research on LBO Returns ............................................................ 30
2.1 Performance Drivers of LBOs................................................................................................... 30
2.2 Money Chasing Deals Phenomenon ....................................................................................... 33
2.3 Buyout Pricing ........................................................................................................................... 36
2.4 My Hypothesis .......................................................................................................................... 39
Section 3: Study of Public-to-Private LBOs 1999-2009 .................................................................... 41
3.1 Methodology ............................................................................................................................ 41
3.2 Composition of the Dataset ..................................................................................................... 45
3.3 Regression Results .................................................................................................................... 48
Conclusion ........................................................................................................................................... 63
Appendix A .......................................................................................................................................... 65
Appendix B .......................................................................................................................................... 67
Appendix C .......................................................................................................................................... 71
Appendix D .......................................................................................................................................... 73
Glossary ............................................................................................................................................... 77
Bibliography ........................................................................................................................................ 81
Acknowledgements ............................................................................................................................ 85
Biography ............................................................................................................................................ 86
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Introduction: From 1999 to 2009, the deal value of leveraged buyouts (LBOs)1 increased dramatically
from $39 billion to $518 billion in 2007, only to fall back to $76 billion in 2009.2 This period of
rapid private equity growth was characterized by one phenomenon above all others: steadily
increasing transaction sizes. In fact, average LBO size almost tripled from 1999 to 2007.3
Why did private equity firms dramatically increase the size of their LBOs during this period? In
this thesis, I present the hypothesis that the ability of a select group of private equity firms to
acquire larger companies opened up new targets that were previously unavailable for buyouts.
Because only a small handful of firms had the buying power to acquire these large targets, large
and established private equity firms faced less competition from other buyers.
The research presented in this thesis provides insight into the economics driving private
equity activity and contributes to the current literature on this topic with a unique and
unusually large dataset. Academia and the media tend to focus exclusively on the conditions
that make large transactions possible, while often overlooking private equity firms’ motivations
behind acquiring increasingly large LBO’s. This thesis gives a unique perspective on private
equity activity by focusing on the incentives driving the private equity firm.
Economic theory states that prices should rise when demand increases and supply stays
constant. There is reason to believe this supply and demand dynamic should apply to private
equity. Theoretically, as the amount of capital committed to private equity increases, so should
1 For a complete description of terms used in this paper, please see the glossary on page 77. 2 2008 Preqin Global Private Equity Review, p. 90 3 Data from Capital IQ, taken from Kaplan and Strömberg (2009)
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the competition for deals, thus driving down returns. This hypothesis was put forth by Gompers
and Lerner (2000) and is referred to in academic literature as the “money chasing deals”
phenomenon.4 If the money chasing deals hypothesis is valid for private equity, then the ability
to buy larger companies should open up a new group of LBO targets and decrease competition
from other private equity firms. According to this hypothesis, the overall favorability of large
deals should therefore be greater than smaller deals conducted during the same period. To
better understand the theoretical underpinnings of this hypothesis, it is necessary to establish a
clear conceptual understanding of how private equity and LBOs function.
Private equity firms gather capital commitments from investors for a specific fund. This
structure operates as a limited partnership, where private equity firms act as the General
Partner (GP) and investors act as the Limited Partner (LP). The mechanism by which investors
commit capital to private equity funds is especially significant. When a fund is raised, investors
do not provide cash to the GP. Investors sign a contract that they will provide a certain amount
of cash, called committed capital, when the GP has found a good investment opportunity.5 It is
very uncommon for a GP to leave committed capital un-invested. This tendency is largely a
result of the fee structure of private equity funds, which incentivize GPs to invest the capital,
even if the expected return is not very high (see Appendix C).
4 Gompers and Lerner (2000) study the money chasing deals phenomenon in venture capital firms. However, research from Ljungqvist, Richardson, and Wolfenzon (2007) and Kaplan and Strömberg (2009) indicate the money chasing deals hypothesis applies to buyout funds as well. 5 Private equity funds usually have a life of 10-13 years during which the GPs can continue to draw capital from
investors. The amount of capital that is committed to private equity funds but has not been invested is called “dry powder” (see Appendix B).
6
The private equity firm (also referred to as the GP in this paper) uses capital from
investors to invest in corporations following a variety of strategies.6 The most prevalent
strategy employed by private equity firms is the Leveraged Buyout (LBO). This strategy consists
of investing capital by buying corporations or divisions of corporations using large amounts of
leverage (usually 60-80 percent of the capital structure). The largest and most prominent LBOs
in recent years have been “public-to-private” LBOs, where a private equity firm acquires a large
public corporation and then takes the corporation private. Public-to-private LBOs make up the
overwhelming majority of all LBOs by deal value. In addition, public-to-private LBOs have the
best data available. For these two reasons, I will focus on public-to-private LBOs in this thesis.
Private equity funds usually have strong covenants restricting what type of investments
the GP can make. If a private equity firm does not find any good investment opportunities for
an LBO, it cannot choose a different way to invest the capital. Therefore, given the strong
financial incentive to invest all the capital committed to a private equity fund, it is likely that
private equity firms will continue to execute LBOs even when the transactions are not favorable
to the buyers. Furthermore, there are a limited number of targets because only a few
corporations are good LBO targets.7
It is plausible therefore, that a private equity firm might seek to escape the inevitable
decrease in general deal favorability when LBO activity increases by acquiring larger targets.
These transactions face less competition from other private equity firms and should be less
affected by the increased competition from other buyers.
6 More information about these strategies can be found in the Glossary under “Private Equity Firm.”
7 A good LBO target has very stable cash flows, low debt, growth opportunities, operational inefficiencies, and a
strong asset base.
7
I directly test this hypothesis through a study of 446 public-to-private LBOs announced
between 1999 and 2009 in the United States and Western Europe. My study focuses on two key
variables of an LBO: size, which refers to the total transaction value of the buyout, and price,
which refers to deal favorability and is independent of size. Price is measured by the valuation
multiple Enterprise Value to EBITDA. My study shows that there is no significant linear
relationship between LBO size and price. The price of LBOs with transaction values from $100
million to around $5 billion increases with the size of the transaction. However, after this point,
price is stable and eventually decreases as transactions get larger, indicating that larger
transactions are more favorable than smaller ones. This result is robust across a variety of
changes to the dataset. However, this study is not meant to be the last word on this subject
because the study only tests pricing and not the ultimate returns of each LBO. At this point,
these LBOs are too recent to make conclusions on their returns.
This research is significant because it presents a new perspective for studying LBOs and
private equity. Past research has largely focused on what made large transactions possible, thus
leading to an emphasis on changes in credit conditions and capital allocation. This thesis
addresses not how the LBO boom was possible but why private equity firms chased the size
that characterized the LBO boom.
The rest of this thesis is organized as follows. Section 1 gives a detailed history of private
equity, drawing heavily on academic research and industry data from Preqin, the alternative
asset research and consulting firm. I use this data to show that private equity has changed
dramatically over the last decade as a tremendous amount of credit and capital was made
available to the largest and most experienced GPs. I argue that these changes have made
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certain private equity firms Wall Street institutions rather than mere investment vehicles, and
that their newfound clout is inextricably related to the size of funds and transactions.
Section 2 takes a deeper look at recent research from academia on private equity
performance and valuation. Section 2 establishes the increased role of investment selection
and timing in delivering returns for LBOs, as well as discussing the effect that an increase in
capital committed to private equity has on returns (the so-called “money chasing deals” effect).
Section 2 concludes with a discussion of previous research on LBO pricing.
Section 3 presents my research on the determinants of LBO pricing from a dataset of
446 public-to-private LBOs announced between 1999 and 2009 in the United States and
Western Europe. My analysis concludes that larger LBOs were priced more favorably than
smaller LBOs and that pricing became especially favorable past the $25 billion mark.
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Section 1: The Dynamic Transformation of Private Equity
This section gives a brief history of private equity activity since 1980. The history of
private equity is usually divided into two booms: 1986-1989 and 2004-2007. In this section, I
aim to go beyond this distinction by describing how private equity activity adapts to changes in
credit conditions and investor sentiment. This section is organized as follows. First, I discuss
trends in the types of transactions completed by private equity. Then, I outline the underlying
macroeconomic drivers of private equity activity and describe what drove the large increase in
private equity activity from 1999-2009. This discussion is important because it demonstrates
the enormous changes that have occurred in private equity over the last decade and informs
the reader on the historical significance of these changes. This understanding is necessary for
an appreciation of the increased importance of private equity on “Wall Street” as well as the
magnitude of the money chasing deals effect. Beyond this section, Section 2 discusses how
recent academic literature shows that price is an important determinant of LBO returns and
reviews previous research on LBO pricing. Section 3 presents the results of my analysis.
1.1 Private Equity From 1980-1999
The following discussion describes how private equity evolved from the boom of the
late 1980s to a more subdued 1990s.
Michael Jensen’s seminal 1989 paper, “The Eclipse of the Modern Corporation,”
captures the attitude of private equity during the 1980s. Jensen argues the publicly held
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corporation has “outlived its usefulness” and that a new type of corporation, privately held with
empowered management and a leveraged capital structure, will inevitably replace publicly held
corporations because they will deliver better returns. These returns are a result of better
governance due to ownership concentration and leverage constraints. Jensen argued the
benefits of this new form of governance are undeniable and will result in organizations
following this governance structure long-term. As reflected in Jensen’s paper, private equity
during this period was seen as a way to arbitrage differences in management and capital
structure.
A year later, Jensen’s claims of a new long-term organizational structure seemed
increasingly doubtful as the number of buyouts plunged after the crash of the high yield bond
market. Furthermore, Kaplan (1991) showed the median time for private ownership of LBO
companies was 6.8 years, giving evidence that the LBO structure is not as sustainable over the
long-term as Jensen predicted. But Jensen’s argument contained a kernel of truth. Though LBOs
never became a long-term corporate structure, the values and management ideas
demonstrated in his work predated a revolution in corporate strategy and management over
the next two decades.
Academic research on this period emphasizes three key drivers of LBO returns: financial,
governance, and operational engineering (Kaplan and Strömberg, 2009). Jensen (1989) focuses
on the financial and governance changes private equity firms bring to their portfolio companies.
He argues that increased management ownership, as well as the illiquidity of this ownership,
gives management incentive to perform. Leverage is also valuable because it reduces what
Jensen calls the “free cash flow” problem, in which companies with excess cash allocate capital
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inefficiently rather than returning it to shareholders. Operational engineering is also a
fundamental driver of value in an LBO. Today, most large private equity firms employ industry
specialists to enhance operational improvements (Kaplan and Strömberg, 2009). However,
academic research suggests LBOs during the 1980s still benefited from operational
improvements. Kaplan (1989) found that operating income to sales increased by 10 to 20
percent, suggesting significant cost improvements in portfolio companies. Similarly, Lichtenberg
and Siegel (1990) found from a study of 1,100 post-LBO manufacturing plants that total factor
productivity growth is significantly higher in LBO plants than productivity growth in other plants
in the same industry.
The collapse of the high-yield bond market brought large public-to-private LBOs to an
abrupt halt in 1989. But by some measures, overall private equity growth continued. The
number of LBOs from 1990 to 1994 was actually greater than from 1985-1989, though the total
enterprise value of deals was significantly lower (see Figure 1.1).
There is little that suggests the rationale behind private equity from 1990-1999 was
different from before. Private equity turned away from large public-to-private deals and
embraced smaller, less public, and less leveraged acquisitions, focusing on LBOs of private
companies or divisions of public companies (see Figure 1.1). Kester and Luehrman’s study of
Clayton, Dublier, & Rice (1995) as well as Baker and Smith’s book on Kohlberg Kravis Roberts
(1998) suggest private equity was operating as it had in the 1980s, though deals were smaller
and less highly leveraged. The momentous growth of private-to-private deals from 1995 to
1999 shown in Figure 1.1 reflects the increasingly blurry line between venture capital and
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private equity during this period as private equity firms increased their activity in the rapidly
growing technology, media, and telecom (TMT) space.
Fig. 1.1: Private Equity Activity 1985-19998
1985–1989 1990–1994 1995–1999
All $257,214 $148,614 $553,852
Public-to-Private $126,035 $13,375 $83,078
Transaction Type9 Private-to-Private $79,736 $80,252 $243,695
(Enterprise Value,
in millions USD)
Divisional $43,726 $46,070 $149,540
Secondary $5,144 $8,917 $72,001
Distressed $0 $1,486 $5,539
In retrospect, Kester and Luehrman’s (1995) argument that the leveraged buyout was
due for a comeback turned out to be remarkably prescient as the number of LBOs surged after
1995 (see Figure 1.2). As evident in Figure 1.2, public-to-private deals account for a small
percentage of the total number of private equity deals but a very large percentage of the total
value of private equity deals. 1995-1999 also saw a renewed interest in pursuing larger targets.
8 Data from Capital IQ
9 For a thorough discussion of the different transaction types, please see the Glossary.
13
Fig. 1.2: Growth of LBO Transaction Types 1980-200710
Public-to-private LBOs were rehabilitated in the late 1990s after having lost their
popularity on Wall Street after the 1980s. Main Street had an especially negative view of LBOs,
associating private equity buyout activity with layoffs and liquidation. These views are reflected
in mainstream business articles such as Susan Faludi’s Pulitzer Prize winning article in the Wall
Street Journal, “The Reckoning: LBO Yields Vast Profits but Exacts a Heavy Human Toll.” But
even academic criticism of LBOs picked up after the end of the boom. Rappaport (1990) argued
LBOs are “shock-therapy” that put inefficient firms under intense stress to bring about quick
and not necessarily lasting change, much in line with the Main Street argument that private
equity is the same as “flipping houses.”
10 Data from Strömberg (2008)
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The 1980-1999 period provides a few clear takeaways on the behavior of private equity.
Private equity activity is highly cyclical, especially in the kind of deals that get done. This
cyclicality is grounded in private equity’s ability to quickly adapt to market conditions. Cheap
credit made public-to-private deals especially lucrative in the late 1980s. Enormous growth in
the TMT space during the 1990s fueled a surge in private transactions. It is common to
distinguish private equity into two booms: 1986-1989 and 2004-2007. But this classification
ignores the less public booms that occurred in industries and transaction types. Taken as a
whole, private equity has proven to be incredibly adaptive and persistent. The fundamental
drivers of the business are constantly in flux and range from tax laws to macroeconomic trends
and management theory.
1.2 Planting the Seeds of the Boom: 1995-2003
The late 1990s and early 2000s were important in restoring interest in large public-to-
private LBOs and thus planted the seeds of the 2004-2007 boom. As public-to-private deals
picked up in 1995, reputational differences in the industry started to emerge. Large,
experienced funds received increased attention by the press due to the size of these funds’
transactions. By 2003, there was a perception among investors that large funds outperformed
smaller ones. This perception is reflected in an industry newsletter commending the
outperformance of a select group of these large funds from 1995-2000.11 This perception is also
11 Preqin PE Spotlight May 2006
15
evident in the Yale Endowment manager’s (David Swensen) highly influential book on portfolio
management, which recommends investing in private equity funds with experienced GPs.12
The late 1990s set a precedent that drove private equity fundraising through the rest of
the decade. The heightened reputation of a group of large and experienced buyout firms during
this period was not just perception, but rooted in actual performance. The outperformance of
larger funds from 1995-2003 is supported by a study on LBO performance by Kaplan and Schoar
(2005) as well as data from Preqin (Figure 1.3). Figure 1.3 depicts the average return for a given
vintage year and clearly illustrates the outperformance of the largest private equity firms.
Vintage year refers to the year a private equity fund is created. For example, the average return
of a fund started in mid-1995 is 10 percent for both large and small funds.
Fig. 1.3: Largest Third of Funds vs. All Other Funds13
12
David Swensen, Pioneering Portfolio Management 13 Preqin PE Spotlight June 2007
16
The outperformance of larger funds from 1995-2003 coincided with an increased
interest in private equity as a viable asset class and investment vehicle. An innovation in
investment management theory (specifically Modern Portfolio Theory) during this time set the
stage for massive increases in private equity fundraising from institutional investors. This
innovation was that increasing allocation to private equity would increase a portfolio’s risk-
adjusted return because private equity returns are historically not strongly correlated with the
returns of other asset classes. The pervasiveness of this new fund management strategy is
reflected by the popularity of Yale University endowment manager David Swenson’s “Yale
Model.” Swenson achieved an annual return of 16.3 percent from June 1998 to June 2008
(during which the S&P 500 returned 2.9 percent annually), partially by increasing his fund’s
stake in private equity from 3.2 percent to 20.2 percent.14 Swensen championed his approach
in speeches and a successful book, Pioneering Portfolio Management (2000). Other
endowments followed suit and either emulated Swensen’s strategy or hired his employees. By
2007, 42 percent of endowments were allocated to alternative investments compared to 23
percent in 2000.15
Other institutional investors have also followed the Yale Model. According to the
European Private Equity & Venture Capital Association, pension funds took the lead as the main
source of capital for private equity deals in 2006, representing 25 percent of the total funds
raised.16 Private equity allocation by pension funds has continued to rise at an astronomical
pace. The Private Equity Analyst reports that by the beginning of 2008, the top four investors in
14 Golden, Daniel. "Cash Me If You Can." Portfolio Magazine, March 18, 2009. 15 Commonfund, “Sources of Endowment Growth at Colleges and Universities.” www.commonfund.org 16 Gilmore, William. “Pension Funds Warm to Private Equity.” Global Investor; May2007, Issue 202, p46-47
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private equity were CalPERS (California Public Employees’ Retirement System), CalSTERS
(California State Teachers’ Retirement System), PSERS (Pennsylvania Public School Employees’
Retirement System), and the Washington State Investment Board.17
1.3 The Fundraising Boom of 2003-2007
The prevalence of the Yale Model among institutional investors brought capital flooding
into private equity. As illustrated in Figure 1.4 below, private equity fundraising grew at an
dramatic rate from 2003-2007, although by the fourth quarter of 2009 quarterly fundraising
had returned to 2003 levels.
Fig 1.4: Quarterly Private Equity Fundraising 2003-200918
17 Private Equity Analyst. 2008. 2007 Review and 2008 Outlook. New York: Dow Jones. 18 Preqin Private Equity Spotlight Jan 2010, Vol 6 Issue 1
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The growth in private equity assets under management from 2003-2007 far outstrips
any other period in the history of the asset class. By 2007, private equity firms managed more
than $2 trillion in assets.19 The number of LBOs grew from 1,334 in 2004 to 2,556 in 2007.20 But
far greater than the growth in the number of deals is the growth in deal value, reflecting the
trend in private equity to pursue larger targets. The total LBO deal value in 2007 was $579.7
billion. A decade earlier, total LBO deal value was only $39.3 billion, implying an annual growth
rate of 138 percent.21
Capital raised by private equity has increased from $98 billion in 1997 to $518 billion in
2007, growing 43 percent annually.22 The number of funds raised annually during this period
also increased from 382 to 779, for an annual growth rate of 10 percent.23 The stark differences
between the growth rates of deal value, capital raised, and number of funds (138 percent, 43
percent, and 10 percent, respectively) underscores recent trends in private equity. Deal value
has grown more than capital raised because leverage used in transactions has increased
considerably. The amount of capital raised annually has increased more than the number of
funds because private equity funds have become larger. The difference between the growth in
the number of deals and the value of deals from 1999 to 2009 shown in Figure 1.5 highlights
the trend of increasing transaction values.
19 2008 Preqin Global Private Equity Review, p. 12 20 2008 Preqin Global Private Equity Review, p. 90 21
2008 Preqin Global Private Equity Review, p. 90 22
2008 Preqin Global Private Equity Review, fig. 3.5, p. 36 23 2008 Preqin Global Private Equity Review, fig. 3.5, p. 36
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Fig 1.5: The Number and Value of Deals by Year24
As suggested earlier, capital committed to private equity firms were not allocated
evenly across fund sizes. As shown in Figure 1.6, the growth of mega buyout funds was
significantly greater than the growth of middle-market funds. Mega buyout funds25 raised only
$20 billion in the first half of 2004 but raised more than $100 billion in the first half of 2007,
implying an annual growth rate of 133 percent. Middle market funds26 raised about $10 billion
in the first half of 2004 and $20 billion in the first half of 2007, for an annual growth rate of only
33 percent.27
24 Private Equity Spotlight Jan 2010, Vol 6 Issue 1 25 For 2005-2008, mega buyout fund refers to funds larger than $4,500 million. Due to the smaller fund sizes before 2005, mega buyout refers to funds larger than $2,000 million for the years 1997 to 2004. This classification is made by Preqin. 26 For 2005-2008, a middle market fund is classified as a fund between $501-1,500 million assets under management. For 1997 to 2004, the middle market classification is applied to funds with assets under management of $301-750 million. Again, this distinction is made by Preqin. 27
The fundraising of small and large buyout funds reflect the same trends of mega and middle-market fundraising. From 2005-2008, Preqin distinguishes small and large buyout as funds with assets under management less than $500 million and between $1,501-4,500 million, respectively. From 1997-2004, small buyouts refer to funds with
20
Fig. 1.6: Fundraising for Different Sized Funds 2004-200728
Mega Buyout Fundraising Mid-Market Fundraising
1.4 The Role of Credit in LBO Activity
Capital clearly flooded into private equity at unprecedented rates in the 2000s and
favored larger funds. However, capital is only one half of the story. Equally important is the
dramatic increase in the availability of credit. This section describes the role of credit in driving
LBO activity during the late 1980s and 2000s.
Kaplan and Stein (1993) show that cheap debt from high-yield (junk) bonds contributed
to higher leverage and transaction multiples (price to cash flow) during the late 1980s, which
culminated in a significant default rate for LBOs executed in the latter half of the 1980s.29
Axelson et al. (2008) show that Kaplan’s conclusions on the effect of cheap financing on LBOs
apply to the recent boom as well. Analogous to the 1980s, cheap debt caused more leverage
less than $300 million under management and large buyouts refer to funds with between $751-2,000 million under management. 28
Preqin Spotlight Aug 2007, Vol 3 Issue 8 29 See Appendix A: Private Equity and Financial Distress
21
and higher transaction prices during the 2000s LBO boom. Axelson et al. (2008) also find that
leverage for their sample of deals from 2004-2006 was 73%, almost as high as their estimate for
1986-1989 (77%). However, it should be noted Kaplan and Stein’s (1993) estimate for leverage
during the late 1980s is notably higher (86%).
An especially interesting study on the impact of credit on LBOs comes from Shivdasani
and Wang (2009), who describe how the “explosion” of structured credit, specifically
Collateralized Debt Obligations (CDOs), increased the supply of bank loans for LBOs. Shivdasani
and Wang found a strong negative correlation between the changes in LBO loan volumes and
the changes in credit spreads of tranches in which CLO vehicles invest, supporting the view that
positive shocks in the supply of credit drove the LBO boom. Figure 1.7 illustrates the strong
correlation between the uses of structured credit and LBO activity.
Fig. 1.7: CDO Issuance vs. LBO Volume30
30 Chart from Shivdasani and Wang (2009)
22
Shivdasani and Wang (2009) also argue CDO funding lowered the cost of debt and
loosened covenants, concluding that an increase of 1 in the standard deviation of CDO funding
of the lead LBO lending bank leads to a 17-20 basis point lower spread on an LBO’s leveraged
loan as well as a 5-12 percent increase in the probability that the LBO debt will have a covenant
light tranche. Shivdasani and Wang convincingly argue that the explosion of structured finance
(and specifically the ability of CDOs to take loans of banks’ books) is intimately related to the
LBO boom. In this sense, credit caused both public-to-private LBO booms, that of the late 1980s
and the mid-2000s. Also, in both booms, availability of credit expanded because LBO debt was
made available to new investors through financial innovation. In the 1980s, LBO debt was
opened up to insurance companies, mutual funds, and other investors through high-yield
bonds. In the 2000s, structured credit allowed these same entities to invest in leveraged loans.
The financial innovation came not from syndicating these loans to other investors, but through
the ability to turn low rated debt to AAA debt through the financial technology of CDOs.
However, Shivdasani and Wang (2009) make an important distinction between the two booms.
They argue increased access to credit did not lead to riskier deals as it did in the late 1980s.31
1.5 Capital and Credit Concentrated in Large Funds
The enormous resources that flooded into private equity in the 2000s were unequally
distributed, favoring large and experienced private equity firms. This section describes the flow
of capital into private equity during that time period. As shown in Figure 1.6, capital has
31 This argument will be explored in more detail in Part 2.
23
disproportionately flooded into a select group of mega buyout funds. To a certain extent, this
consolidation can be viewed as a Darwinian process, with successful funds attracting more
capital and thus growing larger. However, since large funds have historically outperformed
smaller funds, there is a fair degree of endogeneity in this relationship.
Private equity is unique among investment vehicles in that the firms that have
performed well in the past are significantly more likely to perform well in the future. In
contrast, numerous academic papers have shown that mutual fund and hedge fund
outperformance is generally not sustainable and that past performance is not a good indicator
of future success.32
Kaplan and Schoar (2005) found from a dataset of 746 funds (from the private equity
database Thomson Venture Economics) that a 1 percent increase in past performance is
associated with a 54 basis point increase in performance in subsequent funds. However, his
dataset includes Venture Capital as well as buyout funds. For only buyout funds, a 1 percent
increase in past performance is associated with a 17 basis point increase in the subsequent
fund. Not surprisingly, Kaplan and Schoar (2005) also find that better performing partnerships
are more likely to raise follow-on funds and larger funds.
The results of Kaplan and Schoar (2005) are supported by the work of Diller and Kaserer
(2009), who found from a study of 200 funds from 1980 to 2003 (also from Thomson Venture
Economics) that a 1 percent increase in past performance translates to an increase of 40 to 70
basis points in the subsequent fund.
32
For examples, see Carhart (1997) or, more recently, Kazemi, Schneeweis, and Pancholi (2003) for research on the persistence of mutual fund returns. See Kat and Menexe (2002) and Edwards and Cagalyan (2001) for research on the consistency of hedge fund returns.
24
Furthermore, Aigner et al. (2008) found from a study of 104 funds (with data from a
large European private equity fund-of-funds) that a top-quartile fund manager has a 33.3 to
41.7 percent probability to place in the top quartile with the manager’s next fund, depending
on the performance measure. Aigner et al.’s findings on subsequent performance of private
equity firms, using PME (Public Market Equivalent) as a performance measure, are presented in
Figure 1.8. Figure 1.8 demonstrates the performance persistence of successful funds.
Fig. 1.8: Return Persistence Statistics by Quartile33
Succeeding Quartile
1st 2nd 3rd 4th
Pre
ced
ent
Fun
d
1st 36.40% 18.20% 18.20% 27.30%
2nd 27.80% 33.30% 16.70% 22.20%
3rd 14.30% 35.70% 42.90% 7.10%
4th 0.00% 38.50% 30.80% 30.80%
The results of Kaplan and Schoar (2005), Diller and Kaserer (2009), and Aigner et al.
(2008)34 are significant, though there are some drawbacks to applying their results to the recent
LBO boom. For one, the returns of recent private equity funds are often impossible to measure,
meaning the authors had to rely on older funds. Also, the funds studied include buyout, venture
capital, and mixed funds, while my focus is only on buyout funds. Aigner et al.’s dataset has a
33
Data from Aigner et al. (2008) 34
One notable contribution to the study of private equity return persistence unmentioned here is Phalippou and Gottschalg (2007), whose results are largely in line with those of the authors presented above.
25
notably higher percentage of buyout funds (58.69 percent) than the databases of Kaplan and
Schoar (22 percent) and Diller and Kaserer (41 percent).
The performance consistency of private equity is clearly reflected in industry trends and
Limited Partner (LP) behavior. As shown in Figure 1.9, LPs have preferred to put their capital in
larger, more prominent buyout funds that have a proven track record. As a result, the percent
of new private equity fund managers to total fund managers has declined from 30 percent in
1990 to 13 percent in 2002 to 7 percent in 2008.35 Also, Figure 1.9 clearly demonstrates how
less capital was allocated to new GPs compared to existing GPs (from 20 percent in 2003 to 10
percent in 2009).
Fig. 1.9: Private Equity Capital Raised for New vs. Existing GPs36
35
Preqin Employment Report, Sept. 20, 2009. 36 Preqin Employment Report, Sept. 20, 2009
26
It is clear from the academic literature on performance persistence as well as Figures 1.6
and 1.9 that large, experienced private equity firms possessed an advantage in attracting capital
for their funds. However, recent academic work shows these funds enjoyed advantages in
raising debt as well. Demiroglu and James (2010) showed that high reputation private equity
groups (which are coincidentally also shown to be the largest and most experienced GPs) paid
narrower loan spreads, had looser covenants, and borrowed more and at a lower cost from
institutional loan markets.37
The results of Demiroglu and James are supported by Shivdasani and Wang (2009). High
reputation private equity firms clearly enjoyed preferential access to LBO lenders, who were
also some of the largest CDO underwriters. Shivdasani and Wang (2009) find stark differences
in leverage and cost of debt between CDO-funded deals and non-CDO-funded deals. Not
surprisingly, it was high reputation private equity firms who had access to these CDO-funded
deals. Though not explicitly stated in Shivdasani and Wang’s analysis, this relationship is clearly
apparent in the make-up of their data.38 Demiroglu and James (2010) even go so far as to
suggest that the dramatic increase in leverage and covenant light from 2004-2007 is applicable
mostly to experienced private equity firms conducting the biggest LBOs, thus distorting the
statistics on leverage for private equity as a whole.
37 Institutional loans are a great example of the differences in credit available to the mega-buyout firms and smaller firms. Institutional loans funded 60% of LBO debt during the LBO boom, compared with 44% beforehand. The largest LBOs also had the greatest proportion of institutional tranches, thus demonstrating the preferential access of high reputation firms. 38
The median funding need for a non-CDO deal was $186 million while the median funding need for a CDO deal was $1.26 billion.
27
1.6 The Institutionalization of Private Equity
In the following analysis, I will show how the unequal capital and credit allocation of the
2000s has affected the dynamic of the industry within the greater asset management industry.
This section is relevant to my research question because it describes some of the more subtle
implications of the growth of private equity. It is important that the reader understands the
relationship between private equity firms and their stakeholders—the community of
investment banks, other asset management vehicles, and finance professionals, collectively
referred to as “Wall Street” throughout the rest of this paper.
Due to changes in the behavior of institutional investors as well as structured credit
innovations, capital and credit flooded into private equity during the 2000s, causing the sizes of
funds and buyouts to reach new highs. However, the capital and credit flowing into private
equity was clearly not distributed equally. The dominance of existing, established GPs in recent
years has made private equity a more stable industry in the sense that it has discouraged new
entrants and ensured virtually limitless access to capital. As a result, reputation has become a
major barrier of entry into private equity.39
Large and experienced private equity groups have evolved significantly as firms. Large
buyout firms such as Blackstone have completed initial public offerings and now have shares
that are publicly traded on major stock exchanges. Furthermore, their operations have evolved
from traditional private equity to providing investment banking, capital markets, and asset
39 This effect is especially evident in the work of Ljungqvist, Richardson, and Wolfenzon (2007), who show younger GPs are more likely to invest in riskier buyouts. After a few periods of good performance, these young GPs become more conservative. Unfortunately, Ljungqvist et al.’s study only covers buyouts through 2000. It would be useful to conduct this study on a more recent dataset. I would expect the trend to have strengthened given the increased barriers to entry.
28
management services. These large private equity groups have gone from “paper
entrepreneurs” to Wall Street institutions.
Ultimately, the importance of private equity firms on Wall Street depends on their
ability to drive deal activity through large transactions. This relationship was reflected in former
Citigroup CEO Charles Prince’s testimony before the Financial Industry Inquiry Commission.40
Prince famously told the Financial Times in July 2007 regarding a possible end to the buyout
boom, “When the music stops, in terms of liquidity, things will be complicated. But as long as
the music is playing, you’ve got to get up and dance. We’re still dancing.”41 Prince was referring
to Citigroup’s role in continuing to provide credit for leveraged buyouts. In his April 2010
testimony, Prince clarified this statement, arguing, “This business [Citigroup] cannot unilaterally
withdraw from the business [lending to LBOs] and maintain its ability to conduct business in the
future … if you are not engaged in business, people leave the institution.”42
Prince’s statements reflect the commonly held idea on Wall Street during the boom that
a firm had to do business with large private equity firms in order to stay competitive. With
private equity deals accounting for 20 percent of global M&A activity in 2007 (compared to 3.1
percent in 2000) and dominating leveraged capital markets activity, which incidentally pays
significantly higher fees than investment grade issues, an investment bank needed to do
business with private equity to be competitive in overall investment banking fees as reflected in
the “League Tables”, a key source of prestige on Wall Street that measures the market share of
40
Financial Industry Inquiry Commission Testimony of Charles Price and Robert Rubin, April 8, 2010 41
Financial Times, “Citigroup Chief Stays Bullish on Buyouts,” July 9, 2007, online. 42 Sanati, Cyrus. “Prince Finally Explains His Dancing Comment.” The New York Times. April 8, 2010.
29
investment banks.43 As reflected in Prince’s statement, poor performance in the League Tables
ultimately makes an investment bank a less desirable place to work, hence why firms such as
Goldman Sachs and Morgan Stanley have generally been among the most attractive
employment opportunities for an investment banker. Stronger deal flow means more fees and
higher bonuses for investment bankers.
In the first half of 2006, LBOs reached $500 billion, or 5 percent of the US stock market
and 1.4 percent of global GDP.44 From a certain perspective, the future of private equity can be
linked to its size, because its size determines its clout on Wall Street, which is simultaneously
related to capital inflows and credit availability. From this perspective, size of transaction value
is a key determinant of the prominence and profitability of private equity firms. This idea is
explored in more detail in the Conclusion.
In the rest of this thesis, I will continue to investigate the importance of transaction size
in LBOs. Section 2 gives a detailed review of academic research on private equity returns and
shows that size and pricing should theoretically be closely related. Section 3 contains the results
of my study of 446 public-to-private LBOs from 1999 to 2009.
43 Financial Times, January 25, 2007, p. 5. 44 Archarya, Franks, and Servaes (2007)
30
Section 2: A Survey of Academic Research on LBO Returns
Section 1 gave a brief history of private equity activity since 1980 and emphasized the
enormous changes that have occurred in the industry in the last ten years. The next section,
Section 2, lays the theoretical foundation of my hypothesis. Section 2.1 concludes from
academic research on the drivers of LBO performance that the price paid during an LBO is
increasingly important to delivering returns. This conclusion justifies using price to evaluate the
favorability of an LBO. Section 2.2 summarizes results from previous studies on the money
chasing deals phenomenon, concluding that there is substantial evidence that an increase in
capital committed to private equity leads to lower returns. This conclusion supports the idea
that private equity firms would seek to escape this effect with larger transactions. Section 2.3
describes previous research on the determinants on LBO pricing and illustrates the differences
between these studies and my study. After Section 2, Section 3 discusses the results of my
analysis.
2.1 Performance Drivers of LBOs
In this section I review prior academic research on private equity returns and conclude
that pricing has become increasingly important to generating a significant return from an LBO.
Kaplan and Strömberg (2009) identify three general lines of thought in academic literature on
the drivers of returns in LBOs: financial, governance, and operational engineering; tax breaks
and asymmetric information; and market timing. Different studies support a variety of
31
arguments on the fundamental drivers of LBO returns. From the research, it is safe to conclude
that the performance drivers of LBOs are not static and are at least marginally different for each
period in the history of private equity.
The financial, governance, and operational engineering theory is best demonstrated in
the work of Jensen (1989) and contends that management incentives, leverage constraints on
free cash flows, and closer oversight and governance produce a superior organizational
structure. The studies that show the strongest evidence for this theory are Kaplan (1989),
Jensen (1986), Jensen (1989), and Lichtenberg and Siegel (1990). However, these studies all
focus on 1980s LBOs. Studies after 1990 are much less conclusive and include theories of LBO
drivers beyond financial, governance, and operational engineering.
Guo, Hotchkiss, and Song (2009) performed an important study of 192 public-to-private
buyouts from 1990 to 2006. They find that gains from better operating performance are smaller
than the 1980s and that increases in industry valuation and tax benefits are as important in
generating returns as operating improvements. Guo et al. show the virtues of LBOs as expelled
by Jensen (1989) are valid, but not strong enough themselves to drive the substantial returns
required by private equity (the so-called “hurdle rate.” They suggest successful LBOs ultimately
depend on favorable pricing trends and credit availability.
Several studies support Guo et al.’s findings. Cressy, Munari, and Mallipiero (2007) find
from tracking the performance of 122 UK buyouts from 1995-2002 with non-LBO comparables
that operating profitability of PE-backed firms is 4.5 percent greater than comparables.
However, Cressy ,Munari, and Mallipiero also found that a major determinant of profitability
for buyouts is profitability in the year of the buyout, suggesting “investment selection and
32
financial engineering techniques may play a more important role than managerial incentives in
raising performance.” Another study on UK public-to-private buyouts by Archarya and Kehoe
(2009) also found only modest improvements in operating performance.
Also consistent with Guo et al.’s findings is the argument found in Kaplan (1997). Kaplan
argues U.S. corporate governance has fundamentally changed since the 1980s, making 1980s
style LBOs and corporate raiders unpractical.45 Corporations have embraced many of the
advantages of LBOs and instilled them into their companies with new management structures.
Kaplan (1997) stresses the importance of such changes as cost of capital based project analysis,
equity compensation, and more active boards and shareholders, which can conceivably be seen
as having taken away much of the low-hanging fruit private equity enjoyed in the 1980s.46
Leslie and Oyer (2008) also strongly support Guo et al.’s research with a fascinating
study of the performance of 144 private equity backed companies after going public. Leslie and
Oyer find no substantial proof that ex-LBO companies are more profitable or operationally
efficient, concluding that private equity firms do not “create value” as much as they “capture
value.”
The academic literature described above overwhelmingly shows that private equity
increases operational efficiency but not enough to justify 10-40 percent returns to investors.
Operational improvements, governance gains, and tax benefits can easily be negated by the
impact of fees, which are estimated by Metrick and Yasuda (2007) to equal 19 percent of a
fund’s assets under management. The timing of investments, or in other words, the pricing and
45 Fitting with my conclusions on the views of the drivers of LBO returns in the 1980s, Kaplan describes the 1980s takeover wave as capital markets asserting their ascendancy over corporate managers to eliminate waste. 46
It is reasonable to assume the trend described in Kaplan (1997) has increased over the past decade with the continued increases in activist investors and management consultants. Brav, Jiang, Partnoy, and Thomas (forthcoming) describe the substantial increase in shareholder and hedge fund activism.
33
selection of LBO targets, appears to have become the most important incremental driver of
returns in private equity.
2.2 Money Chasing Deals Phenomenon
The previous section, Section 2.1, established the significance of pricing for LBO returns.
This section builds on this understanding of pricing to describe how competition bids up prices
and thus decreases returns for private equity firms.
Economic theory suggests that as the number of buyers for a product increases, the
price of the product should rise. Since there is a set limit of attractive private equity targets, an
increase in capital to private equity should result in higher prices. Gompers and Lerner (2000)
illustrate this effect, the “money chasing deals” phenomenon, holds true in the venture capital
industry, studying over 4000 venture capital investments from 1987 to 1995. Their research
concludes that a doubling of inflows into venture capital led to a 7-21 percent increase in
valuations.47 Diller and Kaserer (2009), using a dataset of 777 private equity and venture capital
funds from 1980 to 2003 (dataset is 41 percent buyout funds), have similar results. The “money
chasing deals” hypothesis rests on the assumptions that there are a limited number of
attractive investments, that funds committed to private equity are “sticky” meaning they
cannot be easily retracted, and that funds must invest in private equity (i.e. they are
47
Conversely, the relationship between valuation and capital inflows could be that improved expectations cause both valuations and committed capital to rise.
34
“segmented”). Theoretically, when these assumptions are stronger, the money chasing deals
phenomenon should be stronger as well.
Subsequent research has shown the money chasing deals phenomenon holds true for
buyouts as well as venture capital.48 For example, Aigner et al. (2008) found evidence that the
amount of capital committed to private equity in a given year was negatively related to a fund’s
PME and IRR. The most compelling evidence that the money chasing deals phenomenon applies
to buyouts comes from Ljungqvist, Richardson, and Wolfenzon (2007). These authors show the
investment behavior of a GP depends on the state of the market (cost of debt and competition
for targets). When credit conditions improve or the competition for deals declines, GPs increase
their investments. These investments also have higher returns. Ljungqvist et al. demonstrate
this by using the number of new firms in an industry as a proxy for the investment
opportunities in that industry. Then they show that the number of new firms in an industry is
inversely related with the amount of time it takes to return a given multiple of committed
capital to the LP. Also, the greater the inflow of money into buyout funds, the longer it takes to
return a given multiple of committed capital to the LP, thus implying lower returns in
accordance with the money chasing deals hypothesis.
Although other studies such as Phalippou and Gottschalg (2007) and Diller and Kaserer
(2009) do not completely support the relevance of money chasing deals to buyout firms, the
study of Ljungqvist et al. should be given heightened importance because of the completeness
of their dataset, which covers 35 percent of all buyout capital from 1981 to 2000. While other
48
Diller and Kaserer (2009) argue that venture capital should exhibit the money chasing deals phenomenon more than buyout funds because venture capital is thought to be more segmented and stickier. Their research shows the money chasing deals phenomenon is statistically significant for venture funds but not buyout funds.
35
studies rely on self-reporting databases such as Thomson Venture Economics, Ljungqvist et al.
obtained their data from one of the largest institutional investors in private equity. This source
means their data is free from self-reporting bias and, more importantly, gives precise
information on the timing of cash flows on over 2,274 portfolio companies by 207 different
private equity funds.
Data on the timing of cash flows allows Ljungqvist to calculate investor behavior, which
is centrally important to testing the money chasing deals hypothesis. Other studies using IRR or
other profitability metrics do not take into account the timing of gains. Studies like Phalippou
and Gottschlag (2007) focus on fund returns while Ljungqvist et al.’s unique dataset allows
them to calculate returns on a portfolio company basis.49 This allows Ljungqvist et al. to truly
isolate the money chasing deals component from the greater picture. For example, suppose a
fund, raised during a time when there is much competition for deals, holds off on committing
much of its capital until in a few years when it sees better opportunities.50 This fund will likely
have higher returns. However, the fact that the fund waited to invest would not be reflected in
the results of Phalippou and Gottschlag (2007) and Diller and Kaserer (2009). Furthermore,
Kaplan and Strömberg (2009) conducted a study very similar to Phalippou and Gottschlag
(2007) and Diller and Kaserer (2009) in which they used data from fund returns drawn from
Thomson Venture Economics (the same database used by the previously mentioned authors) to
show there is a strong negative relationship between fundraising and subsequent returns for a
49
Phalippou and Gottschlag (2007) have cash flow data (amount and timing) only between investors and funds. 50
Data suggests this was the case in 2003-2009. See Appendix B for a depiction of private equity’s un-deployed capital, called “dry powder”.
36
given year.51 I consider the results of Kaplan and Strömberg (2009) more relevant to my
research than comparable studies because their study is more recent and focuses only on
buyout funds.
2.3 Buyout Pricing
Sections 2 and 3 described the importance of pricing for LBO returns and the theoretical
relationship between private equity competition and pricing. This section discusses previous
research on LBO pricing. Previous studies indicate that LBO pricing is cyclical and dependent on
changing business and credit conditions. There is also substantial evidence that the money
chasing deals effect applies to LBO pricing.
My conclusion from surveying academic research is that buyout selection and pricing
has become the primary driver of value in an LBO.52 In the context of the money chasing deals
hypothesis, an increase in capital commitments to private equity funds should significantly
decrease the returns of LBOs by driving up prices and limiting opportunities. This effect should
be especially pronounced for public-to-private transactions since the publicity of takeovers
increases the competition for deals, thus amplifying the money chasing deals effect.
One hypothesis for why deal sizes spiraled to new highs in 2006 and 2007 is that private
equity firms were trying to escape the money chasing deals effect by buying targets out of the
reach of other funds. Larger fund sizes and cheap credit opens up a new group of LBO targets.
51
The dataset of Kaplan and Strömberg (2009) studies returns of US buyout funds from 1984 to 2004. 52
This conclusion is analogous to the conclusion of Kaplan and Strömberg (2009) that private equity firms make returns by buying low and selling high.
37
Since these resources are only available to experienced firms with a strong track record, some
firms are able to buy targets without much competition from other funds. I intend to test this
hypothesis by determining the relationship between transaction size and the valuation of the
target. Another relevant development is the increased use of “club deals”, where multiple
private equity firms put themselves together to buy one company, especially in larger
transactions.
Academic research suggests the most important driver of LBO pricing is credit
conditions. Kaplan and Strömberg (2009) estimate a 250 basis point mispricing of debt would
allow a private equity firm to pay an additional 10 percent for a target in an LBO. Kaplan and
Stein (1993) note that cheap debt in the 1980s caused transaction prices to rise to 7-8 times
EBITDA, only to drop to 5-6 times EBITDA when the credit markets collapsed.
Axelson, Jenkinson, Stromberg, and Weisbach (2008) find the conclusions of Kaplan and
Stein (1993) about the 1980s buyout boom relate to the recent boom as well. The cost of
leveraged loans and high-yield debt is strongly correlated with higher leverage and higher
prices.53 Buyout prices also have a strong relationship with overall M&A prices. Axelson et al.
find that transaction value to EBITDA averaged 9.3. Interestingly, Axelson finds that club deals
are actually priced higher than other deals. This finding is in line with the GAO’s 2008 study of
LBOs, which found by analyzing 325 public-to-private LBOs from 1998 through 2007 that there
was no indication club deals paid lower or higher prices. Meuleman and Wright (2007) make
the same conclusion on the effect of club deals on pricing as the GAO report.
53
Axelson et al. (2009) have two possible explanations for the relationship between the cost of debt and buyout prices. 1) LBO funds create value by taking on cheap debt while the cost of equity stays the same. 2) GPs have an option-like stake in the fund with no downside because they get 20% of the returns but lose no capital themselves.
38
Axelson et al.’s study does not provide evidence on the money chasing deals effect in
the sense that LBO prices did not decouple from broader M&A prices in the mid-2000s. There
are a few reasons to be skeptical about Axelson et al.’s results in this respect. For one, their
dataset excludes most of the large deals of the 2003-2007 boom. Furthermore, they use only
the transactions of five large and highly reputable private equity firms (153 buyouts, only 16%
of which are public-to-private LBOs).
The results of Demiroglu and James (2010) are more relevant to my research question.
The dataset of these authors consists of 181 public-to-private buyouts conducted between
1997 and 2007, 54 of which occurred in 2006 and 2007. Demiroglu and James find that
transaction prices increased in the late 1990s, dipped in the early 2000s, and rose again in 2003.
Unlike the findings of Axelson et al. (2008), Demiroglu and James find that buyout prices after
2003 actually decoupled from market (S&P 500) valuations, suggesting a money chasing deals
effect did occur in the 2000s. Also, prices are shown to be correlated with the number of
buyouts and the reputation of the acquiring private equity group.
An issue with the study of Demiroglu and James is their emphasis on private equity firm
reputation, a subjective quality that is hard to quantify. It would have been more conclusive to
use a more easily observable metric, especially since private equity group reputation seems to
be almost perfectly correlated with size. Demiroglu and James’ conclusions on the high
reputation private equity firms are essentially the same as the conclusions made for large
private equity groups by other authors, such as Kaplan and Stein (1993) and Shivdasani and
39
Wang (2009).54 Therefore, Demiroglu and James’ conclusion that reputation does not have a
substantial effect on deal valuation is very relevant to this study and consistent with my results.
The results of Shivdasani and Wang (2009) are also relevant to my research. These
authors find that structured credit may have driven the size and number of LBOs but did not
result in higher prices or “overheating,” inconsistent with Demiroglu and James (2010) and
Axelson et al. (2008). Shivdasani and Wang posit that prices stayed reasonable amidst such an
increase in activity because structured credit allowed larger buyouts, which opened up a new
group of desirable targets. My results on the favorability of larger buyouts versus smaller ones
contradict this hypothesis.
2.4 My Hypothesis
Academic research on LBO returns suggests that acquiring a company at a good price is
crucial to delivering returns from the transaction. There is also considerably evidence that
competition among private equity firms drives down returns. These two findings are intricately
related. In fact, the period of lowest historical LBO returns (the late 1980s) is also the period
when prices and transaction sizes were at a historical peak. The infamous 1988 RJR Nabisco
buyout that marked the peak of the 1980s buyout boom was not a bad deal. RJR Nabisco was a
good target. The problem was that the acquiring private equity firm overpaid due to
competition from other financial buyers. The acquiring private equity firm paid a premium of
54
For example, Demirgolu’s finding that reputation is closely related to buyout leverage and the cost of debt, meaning high reputation firms use more leverage and have cheaper access to debt.
40
$10 billion dollars for the company, effectively transferring its return to shareholders (Kaplan
and Strömberg, 2009). The price paid for a transaction can therefore be a good indication of the
likely return.
My hypothesis is that larger transactions were more favorable than comparable smaller
transactions because larger buyouts had less competition from other private equity firms. I test
this hypothesis in section 3 using regression analysis on a large sample of public-to-private
LBOs. In addressing this hypothesis, I hope to shed light on why private equity firms chose to
use the massive amounts of resources made available to them from 1999 to 2009 to buy
increasingly larger companies.
41
Section 3: Study of Public-to-Private LBOs 1999-2009
Section 1 gave a brief history of private equity activity since 1980 to illustrate how
changes in the allocation of capital and credit transformed the asset class. Section 2 discussed
the relationship between LBO returns and pricing and built the conceptual framework for the
hypothesis that larger deals should be more favorable than smaller ones. This section, Section
3, presents the results of my analysis of a large dataset of public-to-private LBOs from 1999-
2009. Section 3.1 describes how the dataset was compiled and defines the variables used in the
analysis. Section 3.2 provides information on the landscape of the dataset and includes detailed
information on how many deals were announced each year and how valuations changed
overtime. Section 3.3 presents the results of four regressions run on this dataset. Model 1 uses
EV/EBITDA as the price metric. Model 2 uses Premium as the price metric. Model 3 uses
EV/EBITDA as the price metric and looks specifically at the role of club deals and reputation in
LBO pricing. Finally, Model 4 looks at the difference between the pricing of small and large
LBOs. Model 4 concludes that the relationship between size and price is positive for small LBOs
and negative for large LBOs.
3.1 Methodology
The goal of my study is to assess whether larger transactions are priced more favorably
than smaller ones in a competitive private equity environment. If larger transactions are priced
more favorably, then increasing transaction size of an LBO should result in a lower price. My
42
hypothesis is that prices decline as transaction size increases, thus making mega-buyouts
especially attractive. My research will also contribute to the academic literature on the
determinants of LBO pricing.
To construct my dataset, I took all announced public-to-private deals over $100 million
in transaction value in the Capital IQ database (1,597 LBOs). I focused on public-to-private deals
because they have the best data available. Also, it is difficult to construct a representative
dataset of all LBOs because Capital IQ classifies some LBOs as private placements or ordinary
M&A. Public-to-private LBOs should also theoretically exhibit the money chasing deals
phenomenon more than other transactions (see section 2.2). Lastly, the mega buyouts from
2004-2007 were all public-to-private transactions.
Next, I removed all transactions not announced between 1999 and 2009. Capital IQ was
founded in 1999 and the retroactively added data seems to be more incomplete (Strömberg,
2008). I chose to use the following variables in my analysis:
Fig. 3.11: Definitions of Variables Used in the Analysis
Variable Description
Club Deal A dummy variable used to denote whether the LBO is a club deal.
EBTIDA Growth
Earnings Before Interest, Taxes, and Amortization historical three year growth
calculated from historical EBITDA data. EBITDA growth is calculated on a per-company
basis and adjusted to exclude outliers. Using historical EBITDA growth differs from
Demiroglu and James (2010)’s treatment of growth, who uses management’s three
year growth projections from the merger proxy statement. However, given historical
growth is usually used as projected growth when modeling a firm’s performance, the
43
difference should not be great.
Enterprise Value (EV)
A measure of firm value that reflects the market value of the whole business
regardless of capital structure. EV is calculated as Market Capitalization + Preferred
Stock + Market Value of Debt + Minority Interest - Cash and Cash Equivalents.
Enterprise Value / EBIT
Calculated as enterprise value at the time of acquisition divided by the last twelve
months (LTM) Earnings before Interest and Taxes
Enterprise Value / EBITDA
Calculated as enterprise value at the time of acquisition divided by the LTM Earnings
before Interest, Taxes, Depreciation, and Amortization
EVEG This metric adjusts EV/EBITDA for growth much like the PEG ratio does this for P/E by
dividing the EV/EBITDA multiple by EBITDA growth. A higher EVEG ratio indicates
more was paid for 1 percent of growth than transactions with lower EVEG ratios.
Leverage before the Acquisition
Calculated as Net Debt/Transaction Value. Net Debt is calculated by subtracting the
market capitalization from the transaction value
Mega Buyout An LBO with a transaction value greater than $10 billion. Used as a dummy variable in
the regression analysis.
Net Income Growth
Calculated from historical Net Income growth and adjusted for outliers similarly to
EBITDA growth
P/E Gives the price/earnings multiple, calculated by dividing equity value by net income
Premium Calculated as (Price per share - Target's closing price 30 trading days prior to
announcement / Target's closing price 30 trading days prior to announcement)
Reputation of General Partner (GP)
Reputation is assessed on a yes-or-no basis as a dummy variable. Though this is
significantly different from the methodology of Demiroglu and James (2010), there is
some similarity because reputation is determined by the size of the private equity
firm’s assets under management. The top 10 private equity firms are given the high
44
reputation distinction.55
Riskiness of EBITDA Growth
Used to assess riskiness of cash flows by taking the standard deviation of EBITDA
growth over a 5 year period.
Riskiness of Net Income Growth
Used to assess riskiness of cash flows by taking the standard deviation of Net Income
growth over a 5 year period.
Sector Describes the target’s sector and consists of Information Technology, Consumer
Discretionary, Consumer Staples, Materials, Industrials, Financials, Healthcare,
Utilities, Telecommunications, and Energy.
Transaction Status
Gives whether the transaction is announced, canceled, or completed
Transaction Value
The sum of the total buyout, which equals the total amount of cash and stock being
paid or the target’s equity and net debt. The transaction value equals the enterprise
value of the target.
After purging the dataset of outliers and transactions with insufficient data, I was left
with a dataset of 446 public-to-private LBOs from 1999 to 2009, which is almost three times as
large as previous studies on pricing by Demiroglu and James (2010) and Axelson et al. (2008).
My dataset is exceptionally large because I included all announced deals rather than only
completed deals. I included announced deals because these deals still give an indication of
pricing by private equity for LBOs. Transactions that were cancelled because a better offer
arose from another private equity firm were eliminated. I also test for differences between
announced and completed deals with no substantial changes in my results.
55
Size of the private equity firm is taken from Private Equity International’s annual ranking of the world’s 50 largest private equity firms 2008
45
To make sure my results are robust and are not the product of a bias inherent in the
data from Capital IQ, I performed the same study on a dataset from FactSet. After removing
outliers and transactions with insufficient data, I was left with 371 completed public-to-private
LBOs. My results from the FactSet database were not substantially different from the results of
my Capital IQ dataset.
3.2 Composition of the Dataset
Figure 3.12 illustrates the changes in LBO valuations over time. The number of deals and
total transaction values reflect the LBO boom from 1999 to 2007 as well as the subsequent
decline. Not surprisingly, the average transaction value peaked in 2007 at $3.9 billion compared
to an average of $479 million in 1999. The average premium paid for LBOs seems to be
inversely related to valuation multiples. When multiples such as EV/EBITDA are low, the
average premium paid in an LBO tends to be high. This result is not surprising and reflects
corporations demanding higher premiums in face of depressed public valuations. The rising
EV/EBITDA multiples reflect the overheating of the LBO market as well as rising M&A
valuations. There is a very strong correlation (.79) between EV/EBITDA and LBO volume,
supporting the money chasing deals hypothesis.
46
Fig. 3.12: LBO Valuation Metrics by Year
Total TV (Billion USD)
Number of Deals
AVG TV (Million USD)
AVG Premium (%)
EV/ EBIT
P/E EV/ EBITDA
EBITDA Growth (%)
EVEG Global M&A EV/EBITDA
56
2009
23.8
19
1,252
73
22.4
28.5
8.0
6.96
1.15
12.9
2008
32.7
36
907
27
17.5
36.1
11.0
5.55
1.97
14.7
2007
452.5
116
3,901
18
21.9
31.4
12.8
9.68
1.33
15.3
2006
391.9
106
3,697
22
20.0
29.1
11.1
8.34
1.33
14.6
2005
128.1
52
2,464
20
20.9
26.4
9.7
7.06
1.37
16.9
2004
26.9
22
1,223
17
15.5
32.6
9.3
3.90
2.39
14.8
2003
20.4
26
785
20
12.8
29.7
7.6
4.21
1.81
12.5
2002
4.3
9
473
33
23.1
20.2
8.0
4.58
1.75
12.5
2001
3.5
8
434
95
53.2
18.5
8.7
13.68
0.64
12.5
2000
4.3
9
478
36
9.9
12.2
6.1
3.86
1.58
15.6
1999
3.8
8
479
29
11.7
25.8
8.5
6.45
1.32
15.9
Figure 3.13 sorts the data by transaction size and gives further insight into pricing during
this period. The data is divided to reflect the varying degrees of reach for private equity firms
according to the designation of mega, large, middle-market, and small as defined in Section 1.3.
Fig. 3.13: LBO Valuation Metrics by Deal Size
Transaction Size (USD)
Number of Deals
AVG Premium (%)
AVG EV/EBIT AVG EV/EBITDA AVG Mean EBITDA Growth (%)
AVG EBITDA Growth STDEV
EVEG
40B - 10B 28 22.1 23.2 12.9 8.6 32.4 2.0
10B - 3B 61 24.75 19.2 11.8 9.6 33.3 1.9
3B - 1B 115 19.7 19.4 10.9 8.9 56.0 1.9
1B - 500M 67 18.1 19.7 10.4 4.5 73.4 2.3
500M -100M 174 31.5 20.2 9.5 6.2 50.0 1.6
56 This data is from FactSet MergerStat. The values were computed by taking all non-private equity M&A from 1999 to 2009 and winsorizing the EV/EBITDA multiples for these transactions by 5%. These multiples include deals from around the world and therefore are not great for direct comparison with LBO multiples. However, they do reflect worldwide valuation trends.
47
Figure 3.13 shows EV/EBITDA and EV/EBIT was on average higher for LBOs larger than
$10 billion than smaller LBOs. Small transactions (less than $500 million) had on average the
lowest valuations. The average standard deviation of EBITDA growth is significantly smaller for
larger transactions than smaller ones, indicating a preference of more stable cash flows for
larger transactions. The increase in EV/EBITDA multiples from 2004-2007 is evident in Figure
3.14. Note that EV/EBITDA multiples increased across the board during this period. Larger
transactions were clearly not isolated from the increases in valuation during this time,
consistent with the results of the regression analysis presented below in Section 3.3.
Fig. 3.14: EV/EBITDA and Number of Deals by Buyout Size
Tran
sact
ion
Siz
e
EV/EBITDA Number of Deals
2005
2006
2007
2005
2006
2007
40B - 10B
11.21
13.75
13.54
3
11
7
10B - 5B
8.98
11.13
13.25
4
9
12
5B - 3B
10.89
11.05
14.91
4
8
10
3B - 1B
10.34
10.24
12.08
15
30
43
1B - 500M
10.08
10.88
14.77
8
12
16
500M -100M
8.34
10.99
11.59
17
36
25
48
3.3 Regression Results
Out of the three valuation multiples present in the dataset, EV/EBITDA is the most
comprehensive estimate of firm value because EBITDA is the best estimate of free cash flow.
Price/Earnings and to a lesser extent, EV/EBIT, have other inputs, such as capital structure and
depreciation, that distort the metric. This quality is evident in Figure 3.12, which shows that
EV/EBITDA is the most consistent and predictable measure of firm value. Using EV/EBITDA as
the dependent variable in the regression is consistent with the studies of Demiroglu et al. and
Acharya and Kehoe. The dependent variables in the regression were EBITDA growth and
standard deviation, sector, announcement year, and transaction size. The following equation
describes Model 1:
(EV/EBITDA) = β0 + β1 (Transaction Value) + β2 (EBITDA Growth) + β3 (1999) + β4
(2000) + β 5 (2001) + β6 (2002) + β7 (2003) + β8 (2004) + β9 (2005) + β10 (2006) +
β1 1 (2007) + β12 (2008) + β13 (Consumer Discretionary) + β14 (Consumer Staples)
+ β15 (Materials) + β16 (Industrials) + β17 (Financials) + β18 (Healthcare) + β19
(Telecommunications) + β20 (Energy) + β21 (EBITDA STDEV)
My hypothesis is that larger transaction sizes should result in a lower EV/EBITDA after
adjusting for growth, year, and sector. If my hypothesis is correct, then the regression
coefficient of transaction value (β1) should be negative, indicating that a higher transaction size
(1)
49
lowers the EV/EBITDA. Transaction size should also be a statistically significant explanatory
variable, indicating a p-value less than .05.
The regression results do not support this hypothesis. As indicated in Figure 3.15, the
coefficient of transaction value (β1) is positive and not statistically significant. This result
suggests that transaction value does not have a negative, linear relationship to EV/EBITDA. In
fact, the results suggest the opposite—that larger transaction values indicate higher multiples
paid. The positive coefficient of transaction value is consistent with the trends for EV/EBITDA
shown in Figures 3.12 and 3.13. The entire regression results are presented below in Figure
3.15. The R-square and adjusted R-square of the regression is .3990 and .3664, respectively.
Fig. 3.15: Regression Results for Model 1
Variables Coefficient Standard Error p-Value
Total Regression
3.97 < 0.0001
Constant 7.36 1.68 < 0.0001
Transaction Value 5.8E-05 3.7E-05 0.115
Year = 1999 0.86 1.91 0.654
Year = 2000 -2.06 1.71 0.227
Year = 2001 1.03 1.72 0.550
Year = 2002 -0.01 1.42 0.994
Year = 2003 -0.37 1.21 0.760
Year = 2004 1.71 1.26 0.176
Year = 2005 1.48 1.11 0.181
Year = 2006 2.34 1.04 0.024
Year = 2007 3.75 1.02 0.000
Year = 2008 2.87 1.16 0.014
Consumer Discretionary -0.70 1.40 0.616
Consumer Staples -1.49 1.56 0.339
Energy 0.80 1.86 0.666
Financials 2.01 1.51 0.183
Healthcare -1.48 1.53 0.334
Industrials -0.67 1.44 0.644
Information Technology -0.18 1.47 0.902
Materials -1.22 1.61 0.448
Telecommunication Services -2.99 1.88 0.112
EBITDA Growth 0.19 0.02 < 0.0001
EBITDA STDEV 9.7E-04 1.8E-03 0.586
50
The regression results of Model 1 also provide valuable insight into the determinants of
LBO pricing. Consider the coefficients and p-values for the peak of the boom—years 2006 and
2007. The regression coefficients of these two years are statistically significant at the .05 level
and reflect the increasing EV/EBITDA multiples during these years, as shown in Figure 3.12.
Another notable result of this regression is the coefficient of EBITDA Growth: 0.19 (P-value
<.0001). This result indicates that a 1 percent increase in growth by the target company
increases the EV/EBITDA multiple by .19. This result is remarkably robust, staying in the .18-.25
range across many changes to the dataset.
The money chasing deals phenomenon could also be reflected in the premium paid over
the stock price 30 days before the LBO announcement. If a private equity firm faces significant
competition it should end up paying a higher premium for the target. Larger transactions
should therefore have lower premiums because they face less competition from other financial
buyers. If this hypothesis is valid, the regression coefficient of transaction value should be
negative, indicating that an increase in size decreases the premium paid.
(Premium) = β0 + β1 (Transaction Value) + β2 (Transaction Status) + β3 (1999) +
β4 (2000) + β 5 (2001) + β6 (2002) + β7 (2003) + β8 (2004) + β9 (2005) + β10 (2006)
+ β1 1 (2007) + β12 (2008) + β13 (Consumer Discretionary) + β14 (Consumer
Staples) + β15 (Materials) + β16 (Industrials) + β17 (Financials) + β18 (Healthcare) +
β19 (Telecommunications) + β20 (Energy)
(2)
51
The regression results presented in Figure 3.16 for Model 2 are very similar to the
results of the Model 1 regression. The coefficient of transaction value (β1) is positive and
statistically insignificant, indicating there is no strong linear relationship between transaction
value and premium paid. The regression returned an R-square of .2161 an adjusted R-square of
.1716.
Fig. 3.16: Regression Results for Model 2
Variables Coefficient Standard Error p-Value
Total Regression
31.24 < 0.0001
Constant 67.66 16.34 < 0.0001
Transaction Value 1.3E-04 3.0E-04 0.676
Transaction Status = Cancelled 3.43 11.84 0.772
Transaction Status = Closed 7.41 11.63 0.524
Year = 1999 -42.41 13.51 0.002
Year = 2000 -36.92 12.96 0.005
Year = 2001 20.71 13.36 0.122
Year = 2002 -36.53 13.00 0.005
Year = 2003 -51.83 9.76 < 0.0001
Year = 2004 -53.93 10.09 < 0.0001
Year = 2005 -51.43 8.77 < 0.0001
Year = 2006 -50.24 8.16 < 0.0001
Year = 2007 -54.73 8.05 < 0.0001
Year = 2008 -45.05 9.16 < 0.0001
Consumer Discretionary -3.49 11.01 0.751
Consumer Staples -12.16 12.40 0.327
Energy 0.34 15.32 0.982
Financials -6.57 11.87 0.580
Healthcare 2.00 12.10 0.869
Industrials 2.09 11.35 0.854
Information Technology -1.44 11.46 0.900
Materials 4.58 12.57 0.716
Telecommunication Services 2.10 16.71 0.900
The results for Model 2 in Figure 3.16 indicate that the strongest determinant of
premium paid is the announcement year. Other potential factors such as transaction value,
52
sector, and transaction status have a negligible and statistically insignificant impact on
premium. Therefore, there is no evidence that larger LBOs enjoy lower premiums.
I also investigated the effect of reputation and club deals on pricing. Figure 3.17
presents the valuation metrics for LBOs done by high reputation firms versus normal reputation
firms and club deals versus non-club deals (as defined in Figure 3.11). Not surprisingly, the
average and median transaction value of high reputation and club deals is much larger than the
mean. The median and average EV/EBITDA paid in these deals is not substantially different
from the mean.
Fig. 3.17: LBO Valuation Metrics for High Reputation and Club Deals
AVG TV (in USD
millions)
Number of
Deals
Median TV AVG EV/EBITDA Median
EV/EBITDA
High Reputation
6,311
120
2,790
10.7
10.4
Normal Reputation 1,303 325 479 10.5 9.5
Total 2,654 445 797 10.5 9.7
Club Deal 4,240 61 1,600 9.8 9.7
No Club Deal 1,704 295 491 11.3 10.1
Total 2,138 356 658 11.0 10.0
The relationship between GP reputation, club deals, and pricing was tested in Model 3
below. The regression results are listed in Figure 3.18. The regression again used EV/EBITDA as
the dependent variable.
53
(EV/EBITDA) = β0 + β1 (High Reputation) + β2 (Club Deal) + β3 (1999) + β4 (2000)
+ β 5 (2001) + β6 (2002) + β7 (2003) + β8 (2004) + β9 (2005) + β10 (2006)
+ β11 (2007) + β12 (2008) + β13 (Transaction Value)
The R-square and Adjusted R-square were .1044 and .0731, respectively. A negative
value of β1 indicates that higher reputation private equity firms paid lower prices for LBOs. A
negative value of β2 indicates that club deals were also priced lower than similar transactions.
In this example, the relevant coefficients (β1 and β2) were negative, as shown in Figure 3.18.
However, the result of high reputation firms is statistically insignificant. The coefficient of club
deals, on the other hand, is statistically significant, with a p-value of .0183. This finding
indicates that private equity firms can decrease the price paid for a company by teaming up
with other private equity firms. This result is significant because it contradicts the previous
research done on the impact of club deals on prices by Meuleman and Wright (2007) as well as
the Government Accountability Office and indicates the need for more research in this area.
Also, the result that club deals are priced lower even though they are on average three times
larger than other LBOs seems strange given the regression results of Model 1.
(3)
54
Fig. 3.18: Regression Results for Model 3
Variables Coefficient Standard Error p-Value
Total Regression
6.17 0.0001
Constant 10.44 1.50 < 0.0001
High Reputation -0.06 0.87 0.9413
Club Deal = Yes -2.13 0.90 0.0183
Year = 1999 -3.87 2.33 0.0974
Year = 2000 -3.39 2.23 0.1295
Year = 2001 -0.18 2.65 0.9464
Year = 2002 -2.35 2.19 0.2843
Year = 2003 -1.20 2.12 0.5724
Year = 2004 -1.30 2.07 0.5307
Year = 2005 0.13 1.80 0.9440
Year = 2006 2.57 1.67 0.1250
Year = 2007 2.66 1.63 0.1025
Year = 2008 1.50 1.81 0.4092
Transaction Value 7.83 7.62 0.9183
The results shown in Figures 3.15, 3.16, and 3.18 indicate there is not a clear linear
relationship between transaction size and price. However, this result does not necessarily
disprove my hypothesis. There is no reason to believe that the relationship between price and
transaction size is linear. Figure 3.19 charts EV/EBITDA by transaction value for the LBOs in my
sample.
55
The non-linear relationship between price and size suggested in Figure 3.19 also gives a
new explanation for the results of Model 3. Model 3 indicated that club deals are priced
substantially lower than other LBOs. This result was statistically significant at the .05 level. One
explanation for the lower prices of club deals is they decrease competitive bidding by
aggregating private equity firms into one buyer. However, an equally plausible explanation is
that the difference in price between club deals and ordinary deals is a result of the dramatic
difference in size between club deals and ordinary deals — club deals are generally at least 3
times larger than other LBOs (see Figure 3.17).
Figure 3.19 suggests the relationship between price and size is different for smaller and
larger deals. To isolate the relationship of larger deals from smaller deals, the final model of this
paper introduces two new variables: a dummy variable for “Mega Buyouts” and an interaction
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
45.00
0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
EV /
EB
ITD
A
Transaction Value (Billion USD)
Fig. 3.19: Transaction Value vs. Price
56
term “Mega Buyout × TV.” The Mega Buyout dummy applies to any LBO above a certain
threshold. Due to subjectivity of this threshold, three different values are tested for the
classification of a mega buyout: $5 billion, $10 billion, and $12.5 billion. Mega Buyout × TV is an
interaction term which reflects the difference in the slope coefficients for large and small deals.
These variables will differentiate the slope of larger transactions from the smaller transactions.
(EV/EBITDA) = β0 + β1 (Transaction Value) + β2 (EBITDA Growth) + β3 (1999) + β4
(2000) + β 5 (2001) + β6 (2002) + β7 (2003) + β8 (2004) + β9 (2005) + β10 (2006) + β1
1 (2007) + β12 (2008) + β13 (Consumer Discretionary) + β14 (Consumer Staples) + β15
(Materials) + β16 (Industrials) + β17 (Financials) + β18 (Healthcare) + β19
(Telecommunications) + β20 (Energy) + β21 (EBITDA STDEV) + β22 (Mega Buyout
Dummy) + β23 (Mega Buyout × TV)
There are three regressions using Model 4. Figure 3.20 presents the regression results
using $5 billion as the threshold for a Mega Buyout. This regression returned an R-square and
adjusted R-square of .4018 and .3663. Figures 3.22 and 3.24 present the regression results
using a Mega Buyout threshold of $10 billion and $12.5 billion, respectively.
Fig. 3.20: Model 4 Regression with Mega Buyout > $5B
Variables Coefficient Standard Error p-Value
Total Regression
3.98 < 0.0001
Constant 7.04 1.72 0.318
Transaction Value 0.0002 0.0002 < 0.0001
EBITDA GROWTH 0.19 0.02 0.527
EBITDA STDEV 0.001 0.002 0.603
(4)
57
Year = 1999 0.99 1.91 0.256
Year = 2000 -1.94 1.71 0.517
Year = 2001 1.11 1.72 0.969
Year = 2002 0.06 1.42 0.810
Year = 2003 -0.29 1.22 0.181
Year = 2004 1.69 1.26 0.193
Year = 2005 1.44 1.11 0.027
Year = 2006 2.31 1.04 0.000
Year = 2007 3.72 1.02 0.011
Year = 2008 2.98 1.16 0.661
Consumer Discretionary -0.62 1.41 0.394
Consumer Staples -1.34 1.57 0.601
Energy 0.97 1.86 0.162
Financials 2.12 1.52 0.360
Healthcare -1.41 1.54 0.716
Industrials -0.53 1.46 0.960
Information Technology -0.07 1.49 0.513
Materials -1.06 1.62 0.119
Telecommunication Services -2.94 1.88 0.345
Mega Buyout × TV -0.0002 0.0002 0.186
Mega Buyout Dummy 1.28 0.97 < 0.0001
The incremental slope of larger transactions almost completely negates the positive
slope of Transaction Value, thus indicating that price is independent of size after exceeding $5
billion.
Small y = 7.04 + .0002X Incremental y = 1.28 – .0002X Large y = 8.32
This result indicates pricing or large and small LBOs is substantially different. The
relationship between transaction values and price is depicted in Figure 3.21.
58
Fig. 3.21: Relationship between Price and Transaction Value Using $5B as the Mega Buyout Value
This relationship implies that pricing becomes more favorable after transaction value
exceeds $6.115 billion. After this point, pricing of large deals is steady and independent of
transaction value. It is likely that a private equity firm still has an incentive to increase deal
value due to economies of scale (see Appendix C), even without a discount for size. However, it
should be noted that this relationship is only marginally statistically significant at the .20 level.
Figure 3.22 contains the regression results of Model 4 using $10 billion as the threshold
for a Mega Buyout. This regression returned an R-square and adjusted R-square of .4088 and
.3737, respectively.
0
2
4
6
8
10
12
14
16
18
0 10 20 30 40 50
EV /
EB
ITD
A
Transaction Value (Billion USD)
Small LBOs
Large LBOs
59
Fig. 3.22: Model 4 Regression with Mega Buyout > $10B
Variables Coefficient Standard Error p-Value
Total Regression
3.96 < 0.0001
Constant 7.43 1.69 < 0.0001
Transaction Value 0.0001 0.00 0.390
EBITDA GROWTH 0.19 0.02 < 0.0001
EBITDA STDEV 0.00 0.00 0.536
Year = 1999 0.86 1.90 0.652
Year = 2000 -2.05 1.70 0.228
Year = 2001 0.99 1.71 0.561
Year = 2002 0.00 1.41 1.000
Year = 2003 -0.46 1.21 0.701
Year = 2004 1.66 1.25 0.184
Year = 2005 1.30 1.10 0.240
Year = 2006 2.20 1.03 0.034
Year = 2007 3.76 1.02 0.000
Year = 2008 2.80 1.16 0.016
Consumer Discretionary -0.82 1.39 0.558
Consumer Staples -1.67 1.56 0.286
Energy 0.87 1.85 0.640
Financials 1.88 1.50 0.211
Healthcare -1.64 1.53 0.286
Industrials -0.73 1.44 0.612
Information Technology -0.28 1.46 0.846
Materials -1.28 1.60 0.425
Telecommunication Services -2.84 1.87 0.129
Mega Buyout × TV -0.0002 0.00 0.089
Mega Buyout Dummy 4.99 1.93 0.010
The incremental slope of large transactions is almost exactly the same for Figures 3.22
and 3.20. However, the resulting relationship is substantially different:
Small y = 7.43 + .0001X Incremental y = 4.99 – .0002X Large y = 12.42 – .0001X
This relationship is depicted graphically in Figure 3.23.
60
Fig. 3.23: Relationship between Price and Transaction Value Using $10 as the Mega Buyout Value
This relationship indicates that pricing becomes favorable after exceeding $27.55 billion.
After this point, LBOs become dramatically favorable with increases in transaction size. A $1
billion increase in size results in a .133 decrease of EV/EBITDA. The slope of pricing for large
transactions is statistically significant at the .1 level.
Figure 3.24 contains the results for Model 4 using $12.5 billion as the threshold for a
Mega Buyout. The regression returned an R-square of .4102 and an adjusted R-square of .3752.
Fig. 3.24: Model 4 with Mega Buyout > $12.5B
Variables Coefficient Standard Error p-Value
Total Regression
3.56 < 0.0001
Constant 7.72 1.70 < 0.0001
Transaction Value 0.0001 0.0001 0.165
EBITDA GROWTH 0.19 0.02 < 0.0001
EBITDA STDEV 0.00 0.00 0.521
Year = 1999 0.84 1.89 0.657
Year = 2000 -2.01 1.69 0.236
0
2
4
6
8
10
12
14
16
0 10 20 30 40 50 60
EV /
EB
ITD
A
Transaction Value (Billion USD)
Small LBOs
Large LBOs
61
Year = 2001 1.02 1.70 0.549
Year = 2002 0.03 1.41 0.985
Year = 2003 -0.38 1.21 0.756
Year = 2004 1.66 1.25 0.185
Year = 2005 1.35 1.10 0.222
Year = 2006 2.17 1.03 0.036
Year = 2007 3.73 1.01 0.000
Year = 2008 2.88 1.15 0.013
Consumer Discretionary -1.16 1.41 0.412
Consumer Staples -2.06 1.58 0.194
Energy 0.56 1.86 0.765
Financials 1.59 1.51 0.294
Healthcare -1.91 1.54 0.215
Industrials -1.08 1.46 0.458
Information Technology -0.60 1.48 0.686
Materials -1.61 1.62 0.321
Telecommunication Services -3.21 1.87 0.088
Mega Buyout × TV -0.0003 0.0001 0.015
Mega Buyout Dummy 7.05 2.63 0.008
Similar to the results using $5B and $10B as the mega buyout value, the incremental
slope of larger transactions is negative and statistically significant. The relationship between
size and price for larger firms is the following:
Small y = 7.72 + .0001X Incremental y = 7.05 – .0003X Large y = 14.77 – .0002X
This relationship is depicted graphically in Figure 3.25.
62
Fig. 3.25: Relationship between Price and Transaction Value Using $12.5B as the Mega Buyout Value
The slope of large LBO pricing is greatest using $12.5B as the mega buyout threshold.
This slope is -.0002 and indicates a .2 decrease in EV/EBITDA for every $1 billion increase in
transaction value. This slope is also the most statistically significant of the three with a p-value
of .015. This result indicates that deal favorability increases most dramatically with size for
deals exceeding $12.5 billion in transaction value.
Models 1, 2, and 3 clearly show there is no direct linear relationship between
transaction value and price using a variety of metrics and explanatory variables. However,
Model 4 shows the relationship between LBO size and price differs for large and small LBOs.
There is especially strong evidence that the relationship between size and price for large LBOs is
negative. The regression results of Model 4 support my hypothesis and suggest that very large
buyouts enjoy lower prices and become especially favorable after the $25 Billion mark.
0
2
4
6
8
10
12
14
16
18
20
0 10 20 30 40 50
EV /
EB
ITD
A
Transaction Value (Billion USD)
Small LBOs
Large LBOs
63
Conclusion
My analysis of my dataset of 446 public-to-private LBOs announced from 1999 to 2009
shows that there is no clear linear relationship between transaction size and deal favorability
(also referred to as price). This result indicates the relationship between size and price is not
static across transaction values. For smaller transactions, ranging from $100 million to $5 billion
in value, larger transactions are generally priced higher. However, evidence suggests that once
the size of an LBO exceeds somewhere around $5 billion, this relationship changes and price
stays constant with increases in size. After transaction value exceeds around $10 billion, price
declines as transaction value increases. The rate of change is about a 0.1 to 0.2 decrease in
EV/EBITDA for every $1 billion increase in transaction value. The inverse relationship between
size and price is statistically significant.
This result also explains why club deals—LBOs where private equity firms act in
consortium—were found to be priced lower than other LBOs. Club deals are on average three
times the size of other LBOs and thus benefit from the lower prices of larger deals.
The results of my study support my hypothesis. Regression analysis showed that after a
certain point, larger transactions become more favorable than smaller ones. This result was
statistically significant at the .05 level and robust across three changes to the classification of a
“mega buyout.”
While this study does not prove private equity pursued larger deals because of better
pricing, this study shows there are economic reasons for private equity to pursue larger
transactions. This study shows the relationship between prize and size is different for small and
large LBOs. From the perspective of a private equity firm, a larger transaction will be more
64
favorable as size increases, thus propelling private equity to increase the size of LBOs. Two
alternate explanations for the increase in transaction size by private equity—fee structure and
clout with lenders, advisors, and employees—are explored in Appendix D.
This study suffers from several limitations that might be addressed in further research.
First, studying price rather than returns is an inherently flawed way to study deal favorability.
There is no way of knowing the returns of the LBOs of the mid-2000s this soon after the
completion of the transactions. Deals that seem favorable from their valuation may still deliver
low returns. There are also a number of intangibles, such as management performance, that
are not included in my analysis of pricing. That being said, there are strong reasons to believe
that price is a good proxy for evaluating the favorability of an LBO. As discussed in detail in
Section 2.1, price has become an increasingly important determinant of LBO returns. Second,
this study includes LBOs that were announced but later cancelled.57 Lastly, in compiling the
dataset, certain transactions were excluded due to data limitations. There might be a bias in
excluding these transactions that mask the true relationship between price and size.
57
It should be noted that I found no significant difference in results after removing all cancelled deals from the dataset.
65
Appendix A
Private Equity and Financial Distress
Financial distress rates for LBOs vary substantially over time. Andrade and Kaplan (1998)
found that 29 percent of their dataset (LBOs from 1985 to 1989) had defaulted by 1995. Kaplan
and Stein (1993) attribute this high default rate on transactions using less bank debt and fewer
covenants. Guo, Hotchkiss, and Song found a 12 percent financial distress rate for their dataset
of 192 buyouts from 1990 to 2006. Kaplan and Strömberg (2009) found a 7 percent financial
distress rate for his dataset of 17,171 deals from 1970 to 2007.
The high default rate of the late 1980s indicates trouble for LBOs from 2003-2007, when
leverage and pricing peaked similarly to the 1980s (Axelson et al., 2008). Guo, Hotchkiss, and
Song (2007) found that post-buyout performance is positively related to bank financing. This
conclusion is theoretically consistent with past research. Berlin and Mester (1992) and Smith
and Warner (1979) show that the concentration of bank debt makes it easier to negotiate.
Research suggests that ease of negotiating then lowers financial distress costs (Gilson, John and
Lang (1990)).
However, this benefit of bank financing that decreases financial distress has largely been
eliminated in the recent boom due to the role of structured credit. 87 percent of CDOs from
2003 to 2007 were arbitrage CDOs, meaning they were sold off banks’ balance sheets
(Shivdasani and Wang, 2009). The large role of these structures in financing bank loans to
private equity from 2003-2007 implies much of LBO bank debt has been distributed to financial
institutions around the world. Therefore, even though bank debt grew to 81.3 percent of non-
66
equity financing for LBOs during the LBO boom (Axelson et al., 2008), financial distress is likely
to increase similarly to the 1980s boom. This position contrasts with that of Kaplan and
Strömberg (2009), who argue higher coverage ratios and looser debt covenants will keep
defaults significantly below those of the 1980s. Kaplan and Strömberg’s point is that covenant
light debt will cause less defaults because borrowers will actually have to run out of money
before they can default. However, this claim is contradicted by the work of Demiroglu and
James (2010), who find that buyouts financed by loans with more financial covenants are less
likely to experience financial distress.
I find it strange that Kaplan would underestimate the significance of negotiations for
default rates, especially since Kaplan and Stein (1993) argue that one of the reasons the
majority of LBO defaults in the 1980s ended up in court was due to the difficulty of conducting
private workouts when the debt is widely dispersed. Acharya, Franks, and Servaes (2007) take
an opposing position, arguing coordination problems with hedge funds and other institutions
should be easier. Ultimately, coordination depends on the total dispersion of the syndicated
and securitized debt, which is very difficult to trace.
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Appendix B
Mega Buyout Funds: The Next Five Years
Mega buyout funds were hit especially hard by the 2008 credit crisis and ensuing
recession. The disproportionate declines in net asset values (NAV) of mega buyout funds
compared to smaller funds is due to the greater size and increased leverage of mega buyouts.
Fig. B.1: Change In NAV by Buyout Fund Size58
But even on a proportional basis, the returns of mega buyout funds plunged significantly.
58 Preqin PE Spotlight Jan 2010, Vol 6 Issue 1
68
Fig. B.2: Median Buyout Horizon IRRs by Fund Size59
The decreased performance of mega buyouts in recent years could significantly impact
the clout of established private equity institutions on Wall Street if investors reallocate capital
to smaller funds. Lower capital going to mega-buyout funds would mean smaller LBOs, less
M&A fees, and less influence on LBO lenders. A January 2010 survey of LPs indicates investors
are indeed re-evaluating their private equity investments.
59 Preqin PE Spotlight Jan 2010, Vol 6 Issue 1
69
Fig. B.3: LP’s Views of Fund Types as of Jan 201060
However, I think the LP’s renewed interest in small and mid-market buyouts is
transitory. Mega LBOs have been hit especially hard by the recent crisis because of their high
leverage. Once the economic situation improves, mega buyouts will recover a significant
portion of their value. Furthermore, much of the capital raised from 2003-2007 has not been
invested yet, as evident in Figure B.4). These funds will likely be invested in better priced deals
than the 2003-2007 buyouts and should therefore provide substantial returns to investors. 61
60 Preqin PE Spotlight Jan 2010, Vol 6 Issue 1 61
It will be many years, probably a decade, before anyone can make strong conclusions on the return of private equity from 2003-2007. This is illustrated in Kaplan and Stromberg’s (2009) dataset. Out of 17,171 transactions going back all the way to 1970, less than 50% had exited.
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Fig. B.4: Private Equity Assets Under Management as of June 200862
Figure B.4 only depicts deployed capital and dry powder as of June 2008. However,
given that buyout activity has been severely constrained since June 2008, the amount of dry
powder depicted in this chart still applies to the beginning of 2010.
62 Preqin PE Fundraising Spotlight 2008
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Appendix C
Private Equity Fee Structure
The fee structure of private equity traditionally consists of an annual 2 percent
management fee of all assets currently held and managed by the private equity firm and a 20
percent performance fee consisting of 20 percent of the gross profit earned when a portfolio
company is sold. Over time, these fees can add up to substantial amounts. Metrick and Yasuda
(2007) estimate fees to equal 19 cents out of every 1 dollar invested in private equity. Not
surprisingly, fees tend to adjust as the negotiating power of firms and investors fluctuates.
Figure C.1, gives management fees by fund size from 2000-2009. Larger funds tend to have
slightly smaller management fees.
Fig. C.1: Trends in Management Fees by Fund Size and Vintage Year63
63 Preqin PE Spotlight Nov 2009, Vol 5 Issue 11
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Recently, as the bargaining power of LPs has increased, fees have again become a point
of debate. One of the key new principles of the International Limited Partner Association is
that, “management fees should cover normal operating costs for the firm and its principals and
should not be excessive.”64 This statement reflects the problem with having management fees
constant across fund sizes. Management fees are supposed to be enough to “keep the lights
on,” but with economies of scale, a large fund can earn a substantial profit merely from the
management fees.
64 “Private Equity Principles,” Institutional Limited Partners Association, 2009. www.ilpa.org
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Appendix D
Two Alternate Theories of the Rationale behind Mega Buyouts
I recognize two alternate theories on why private equity firms embrace size: fee
structure and clout with lenders, advisors, and employees (collectively referred to as Wall
Street). Both of these theories provide alternate explanations for why private equity firms
embraced size over the last decade.
Under the current fee structure of private equity, a GP will earn significantly more from
a larger transaction than a smaller one, even if the larger one is significantly less profitable. 65
From a private equity firm’s perspective, a 10 percent return on a $40 billion LBO is better than
a 40 percent return on a $10 billion LBO.66 The private equity group will make $800 million on
both LBOs from carried interest. However, management fees will be much greater for the $40
billion LBO.67 Management fees are supposed to cover operating expenses of the GP, however,
for very large transactions, management fees have become a significant source of profit
because of economies of scale. An example of these economies of scale is the average staff per
assets under management. As depicted in Figure C.1 below, a private equity firm with more
than $10 billion assets under management (AUM) needs almost half as much staff per $1 billion
of AUM as a private equity firm with $1-2.5 billion AUM.
65 For more information on the fee structure of private equity, refer to Appendix C. 66 Assuming the firm is using the standard fee structure: 2% management and 20% carried interest 67
The $40 billion LBO will make $800 million from management fees versus $200 million for the $10 billion LBO. Even if the management fee is only 1.5 percent, which is true for some large funds, fees from a large LBO are $400 million higher than the smaller one.
74
Fig. C.1: Average Number of Staff per Firm by Value of AUM68
Therefore, even though a large target might not be as favorable as a smaller one, a
private equity firm still has an incentive to pursue the larger deal.
The second alternate hypothesis on why private equity firms have incentive to pursue
size is that it increases their clout with Wall Street, which in this case refers to the network of
financial institutions (most importantly, large investment banks) and the professionals at these
firms that control large amounts of capital. Private equity’s new clout on Wall Street is a result
of private equity’s ability to drive deal activity. This idea is well represented in the infamous
statement of Citigroup CEO Chuck Prince that “When the music plays, we’re still dancing.” As
described in detail in Section 1.6, investment banks have a strong incentive to lend to private
68 Preqin Employment Report, Sept. 20, 2009.
75
equity firms. In fact, Prince’s statement suggests this incentive is so strong that investment
banks are actually worse off if they choose not to participate. It is not surprising that research
from Demiroglu and James (2010) shows that high reputation firms enjoy preferential access to
lenders, resulting in lower rates and less covenants (see Section 1.5).
Empirical evidence also suggests that executing the biggest deal is prestigious and
desirable for a private equity firm. The timing of the mega LBOs during the buyout boom
supports this theory.69 According to data from Capital IQ described below in Figure C.2, the
announcement of the five biggest announced LBOs came in a very gradual manner, with 3-4
months separating each subsequently bigger announcement.
Fig. C.2: Timing of the Five Largest Announced LBOs70
Announcement Date Target Transaction Value Private Equity Sponsors
06/29/2007 BCE, Inc. 46,340.85 Merrill Lynch; Madison Dearborn; Providence
Equity Partners; Teachers' Private Capital
02/25/2007 TXU Corp. 45,236.53 Goldman Sachs; TPG; KKR
11/19/2006 Equity Office Properties 36,924.63 The Blackstone Group
07/24/2006 HCA, Inc. 33,436.11 Merrill Lynch; KKR; Bain Capital
05/28/2006 Kinder Morgan, Inc. 30,456.27 Riverstone; The Carlyle Group; AIG; Goldman Sachs
There is clearly an allure for a private equity firm to execute the largest deal. The almost
rhythmic rise in transaction values could signify a fundamental misalignment of incentives
somewhere in the private equity investment structure. There is reason to believe this
69
This buildup of transaction value over time is also evident in the 1980s boom, which peaked with the LBO of RJR Nabisco in 1988. 70 Data from Capital IQ
76
misaligned incentive is the GP fee structure, which was not designed with large funds in mind.
As Jensen (1989) presciently warned, “I look with discomfort on the dangerous tendency of LBO
partnerships, bolstered by their success, to take more of their compensation in front-end fees
rather than in back-end profits earned through increased equity value.” There is a strong
argument to be made that the fee structure of private equity misaligns incentives. However,
given the results of my research—that mega buyouts are indeed priced more favorably than
smaller transactions—this incentive for size is not necessarily bad for the Limited Partners.
77
Glossary
Definition: Description:
Carried Interest The share of profits given to the General Partner as compensation to
incentivize good performance (usually 20 percent).
Club Deal A buyout where a number of private equity firms pool their resources to
execute the transaction as a consortium.
Collateralized Debt Obligation (CDO)
A bundle of fixed-income asset-backed securities that is divided into
tranches of varying seniority by investment banks and sold to investors.
Collateralized Loan Obligations (CLO)
A CDO where the underlying securities are loans, most commonly
leveraged loans. Arbitrage CLOs are CLOs that are sold off the books of the
underwriting banks to other investors.
Covenant light (Cov-lite) Bank loans that do not carry the usual covenants that restrain risk-taking
by borrowers. The emergence of cov-lite is generally traced back to the
explosion of the structured credit market in the mid-2000s, which made
banks less watchful of covenants since many loans were syndicated or
securitized.
Distressed Investments Investments in securities that are deeply discounted because the issuers
are in financial distress.
Divisional Buyout An LBO of a division of a larger corporation.
Dry Powder Capital committed to a private equity fund that has not been called up by
the GP.
Financial Sponsor See private equity firm
General Partner (GP) See private equity firm
Institutional Loan Loans that do not amortize over time, indicating they have bullet
78
maturities. The converse of institutional loans is pro-rata loans, which
consist of revolving credit facilities and amortizing term loans.
Leveraged Buyout (LBO) An acquisition usually conducted by a financial sponsor where a significant
portion of the purchase price, often 75%, is financed by debt. The target of
an LBO is usually a mature company with steady cash flows, a strong asset
base, low debt, and undervalued equity.
Leveraged Loan Loans extended to significantly leveraged companies at higher rates than
other loans and often used to fund LBOs.
Limited Partner (LP) The investors in private equity funds.
Management Fees An annual fee charged by the General Partner to cover the administrative
and operational costs of the private equity firm.
Mezzanine Investments An investment in preferred stock or subordinated debt that is senior only
to common stock. The junior position within the capital structure means
mezzanine debt is more risky and delivers higher returns than other debt.
Money Chasing Deals Effect
Hypothesis put forth by Gompers and Lerner (2000) that argues returns
from private equity should be negatively related to capital committed to
private equity because increased competition for deals increases prices
thus diminishing returns.
Portfolio Company A company held and managed by a private equity firm after a buyout.
Private Equity Firm Partnerships or limited liability corporations that make money by investing
and managing capital from investors through leveraged buyouts, venture
capital, and distressed and mezzanine investments. Though firms that
invest in venture capital and distressed and mezzanine opportunities are
often considered private equity firms, for the purposes of this thesis,
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private equity firms refers exclusively to firms conducting buyouts. The
capital managed by buyout private equity funds dwarfs the capital
managed by the other forms of private equity. Private equity firms raise
and manage private equity funds.
Private Equity Fund Pools of capital with a fixed life of 10-13 years that are raised and managed
by private equity firms. Private equity funds are organized as limited
partnerships in which the investors are limited partners and the private
equity firm is the general partner. A private equity firm raises multiple
funds over time, depending on how fast it is investing the capital
committed to each fund. Private equity funds are generally closed-end,
meaning funds committed by investors cannot be withdrawn later.
Investors do not provide the capital until the GP finds a suitable
investment. Funds usually have covenants that restrict the possible
investments of the GP.
Private-to-Private LBO A leveraged buyout of a private company. Private companies are usually
smaller than public companies so the transaction values of these deals
tend to be small and are considered middle-market.
Public Market Equivalent Compares private equity returns with the returns of the public market
(introduced by Diller and Kaserer (2004). PME is the ratio of what the
investor receives from an investment in a private equity fund over what
the investor would have earned from an equal investment in the public
market.
Public-to-private LBO An LBO of a public company that results in the financial sponsor taking the
company private.
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Secondary Buyout The acquisition of a portfolio company by another private equity firm.
Venture Capital An investment vehicle that invests capital in young companies with high
growth potential.
Vintage Year The year in which a private equity fund is raised by a financial sponsor.
Wall Street This term refers to high finance institutions and the culture of the
professionals at these institutions. Wall Street is dominated by the ability
to generate returns. In this paper, Wall Street generally refers to large
investment banks providing underwriting and advisory services to
corporations.
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Bibliography
Acharya, Viral, and Conor Kehoe, 2008. “Corporate Governance and Value Creation Evidence from Private Equity.” (February 17, 2010). Available at SSRN: http://ssrn.com/abstract=1324016 Acharya, Viral, Julian Franks, and Henri Servaes, 2007. “Private Equity—Boom or Bust.” Journal of Applied Corporate Finance, 19(4): 44–53. Aigner, Philipp, Stefan Albrecht, Georg Beyschlag, Tim Friederich, Markus Kalepky, and Rudi Zagst, 2008. “What Drives PE? Analyses of Success Factors for Private Equity Funds.” Journal of Private Equity, 11(4): 63-85. Andrade, Gregor, and Steven N. Kaplan, 1998. “How Costly is Financial (Not Economic Distress)? Evidence from Highly Leveraged Transactions That Became Distressed.” Journal of Finance, 53(5): 1443–94. Axelson, Ulf, Tim Jenkinson, Per Stromberg, and Michael Weisbach, 2008. “Leverage and Pricing in Buyouts: An Empirical Analysis.” http://papers.ssrn.com/sol3/papers.cfm?abstract_id_1027127. Berlin, Mitchell, and Loretta J. Mester, 1992. “Debt Covenants and Renegotiation.” Journal of Financial Intermediation, Vol. 2, No. 2, (Jun., 1992), pp. 95-133. Brav, Alon, Wei Jiang, Frank Partnoy, and Randall S. Thomas, 2008. “The Returns to Hedge Fund Activism” (March 2008). ECGI - Law Working Paper No. 098/2008. Available at SSRN: http://ssrn.com/abstract=1111778 Carhart, M.M, 1997. "On Persistence in Mutual Fund Performance." Journal of Finance, Vol. 52, No. 1 (1997), pp. 57-8 Cressy, Robert Clive, Federico Munari, and Alessandro Malipiero, (2007). “Playing to their Strengths? Evidence that Specialization in the Private Equity Industry Confers Competitive Advantage” (February 2007). Available at SSRN: http://ssrn.com/abstract=964367 Cumming, Douglas, Donald Siegel, and Mike Wright, 2007. “Private Equity, Leveraged Buyouts and Governance.” Journal of Corporate Finance, 13(4): 439–60. Edwards, Franklin, and Mustafa Cagalyan, 2001. “Hedge fund performance and manager skill”, Working paper, Columbia University.
82
Demiroglu, Cem and James, Christopher M., 2010. “The Role of Private Equity Group Reputation in LBO Financing (March 5, 2010). Journal of Financial Economics, 96(2), 306-330 Diller, Christian and Christoph Kaserer, 2009. “What Drives Private Equity Returns? Fund Inflows, Skilled GPs, and/or Risk?” European Financial Management, 15(3): 643-675. Faludi, Susan. "The Reckoning: Safeway LBO Yields Vast Profts but Exacts Human Toll." The Wall Street Journal 16 May 1990: A1. Print. Gilson, Stuart C., Kose John, and Larry H. P. Lang, 1990. “Troubled Debt Restructurings: An Empirical Analysis of Private Reorganization of Firms in Default,”s Journal of Financial Economics, Vol. 27,No. 2, (Oct., 1990), pp. 315-353. Golden, Daniel. "Cash Me If You Can." Portfolio 18 Mar. 2009. Web. <http://www.portfolio.com/executives/2009/03/18/David-Swensen-and-the-Yale- Model/>. Gompers, Paul, and Josh Lerner. 2000. “Money Chasing Deals? The Impact of Fund Inflows on Private Equity Valuations.” Journal of Financial Economics, 55(2): 281–325. Guo, Shourun, Hotchkiss, Edith S. and Song, Weihong, 2009. “Do Buyouts (Still) Create Value”. Journal of Finance, Forthcoming. Available at SSRN: http://ssrn.com/abstract=1009281` Jensen, Michael C., 1986. “Agency Costs of Free Cash Flow, Corporate Finance and Takeovers.” American Economic Review, 76, 323-329. Jensen, Michael, 1989. “Eclipse of the Public Corporation.” Harvard Business Review, 67(5): 61–74. Jensen, Michael C., 1989b. “Active Investors, LBOs, and the Privatization of Bankruptcy,” Journal of Applied Corporate Finance 2, 35-44. Kaplan, Steven, 1989, “The effects of management buyouts on operating performance and value,” Journal of Financial Economics 24, 217-254. Kaplan, Steven, 1991. “The staying power of leveraged buyouts”, Journal of Financial Economics 29, 287–313. Kaplan, Steven, 1997. “The Evolution of U.S. Corporate Governance: We Are All Henry Kravis Now.” Journal of Private Equity, 1(1): 7–14. Kaplan, Steven N., and Jeremy Stein. 1993. “The Evolution of Buyout Pricing and Financial Structure in the 1980s.” Quarterly Journal of Economics, 108(2): 313–57.
83
Kaplan, Steven N., and Antoinette Schoar, 2005. “Private Equity Returns: Persistence and Capital Flows.” Journal of Finance, 60(4): 1791–1823. Kaplan, Steven N and Strömberg, Per, 2009. Journal of Economic Perspectives, Winter2009, Vol. 23 Issue 1, p121-146, 26p, 3 Charts, 5 Graphs; DOI: 10.1257/jep.23.1.121 Kat, Harry M. and Faye Menexe, 2002. “Persistence in Hedge Fund Performance: The True Value of a Track Record” (May 6, 2002). Cass Business School Research Paper. Available at SSRN: http://ssrn.com/abstract=311041 or doi:10.2139/ssrn.311041 Kazemi, H., T. Schneeweis, and D. Pancholi, 2003. "Performance Persistence for Mutual Funds: Academic Evidence." Isenberg School of Management, University of Massachusetts. Kester, W. C., and T. A. Luehrman, 1995. "Rehabilitating the Leveraged Buyout: A Look at Clayton, Dubilier and Rice." Harvard Business Review 73, no. 3 (May-June 1995): 119- 130. Leslie, Phillip and Paul Oyer, 2008. “Managerial Incentives and Value Creation: Evidence from Private Equity” (September 2008). Rock Center for Corporate Governance Working Paper No. 21. Available at SSRN: http://ssrn.com/abstract=1341295 Lichtenberg, Frank R., and Donald Siegel. 1990. “The Effects of Leveraged Buyouts on Productivity and Related Aspects of Firm Behavior.” Journal of Financial Economics, 27(1): 165–194. Ljungqvist, Alexander, Matthew Richardson, and Daniel Wolfenzon. 2007. “The Investment Behavior of Buyout Funds: Theory and evidence.” http://papers.ssrn.com/sol3/papers.cfm?abstract_id_972640. Metrick, Andrew and Ayako Yasuda, 2009. “The Economics of Private Equity Funds” (June 9, 2009). Swedish Institute for Financial Research Conference on The Economics of the Private Equity Market; Review of Financial Studies, Forthcoming; Swedish Institute for Financial Research Conference on The Economics of the Private Equity Market. Available at SSRN: http://ssrn.com/abstract=996334 Meuleman, M., Wright, M., 2007. Industry Concentration, Syndication Networks and Competition in the UK Private Equity Market. CMBOR Occasional Paper. Rappaport, A., 1990, “The staying power of the public corporation”, Harvard Business Review 1, 96–104.
84
Renneboog, L.D.R., T. Simons, M. Wright, 2007. “Why do public firms go private in the UK? The impact of private equity investors, incentive realignment and undervaluation.” Journal of Corporate Finance 13, 591–628. Shivdasani, Anil and Yihui Wang, 2009. “Did Structured Credit Fuel the LBO Boom?” (April 24, 2009). AFA 2010 Atlanta Meetings Paper. Available at SSRN: http://ssrn.com/abstract=1285058 Smith, Clifford W., and Jerold B. Warner, 1979. “On Financial Contracting: An Analysis of Bond Covenants,” Journal of Financial Economics, Vol. 7, No. 2, (Jun., 1979), pp. 117-161. Strömberg, Per, 2008. “The New Demography of Private Equity,” The Global Economic Impact of Private Equity Report 2008, World Economic Forum, January 2008. Swensen, David. 2000. Pioneering Portfolio Management: An Unconventional Approach to Institutional Investment. New York: Free Press.
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Acknowledgements
I am heartily thankful to my supervisor, Michael Clement, whose guidance and support
was instrumental to the completion of this thesis. His willingness to entertain my musings and
ability to focus my efforts is greatly appreciated. I am also thankful to my second reader,
Jonathan Cohn, and the other faculty members at the McCombs School of Business who
assisted me in my research. Lastly, I am grateful to my parents for their financial support.
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Biography
Roland C. Südhof grew up in Dallas, Texas where he attended the Episcopal School of Dallas. In 2006, he enrolled in the Plan II Honors Program and Business Honors Program at The University of Texas at Austin, where he also pursued a Masters in Professional Accounting. Roland first became interested in private equity in the summer of 2009, when he was introduced to the LBO capital structure while interning in the corporate finance group at Energy Future Holdings (the $45 billion TXU buyout conducted by KKR, TPG, and Goldman Sachs). After graduation, Roland will work as an analyst at a bulge-bracket investment bank in New York.