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Financial Markets and Portfolio Management

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02.11.2017

Fueling the buyout machine: fundraising in private equity

verfasst von: Robert Loos, Bernhard Schwetzler

Erschienen in: Financial Markets and Portfolio Management | Ausgabe 4/2017

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Abstract

This paper analyzes the impact of performance, investment-firm-related, and macroeconomic variables on fundraising activities in private equity (PE). We use a novel, backward-looking approach to link current to preceding funds, which allows for including several parallel predecessor funds in our analysis. We employ logit and tobit models to a global sample of 1463 fundraising events observed between 2000 and 2010 in order to estimate the probability of raising and the volume of follow-on funds. Our results show that the average buyout duration of past transactions has a negative impact, whereas exits via an initial public offering (IPO) and deals without industry-style drift positively affect fundraising activities. Larger, industry-diversified, and independent PE firms exhibit a higher likelihood of fundraising and collect larger amounts.

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In the following, we use the terms “inception year” and “vintage year” interchangeably. More precisely, a fund’s vintage year is the year in which the first investment is made—inception year and vintage year frequently coincide, though.

For example, according to our sample, Apax Partners ran at least 10 predecessor funds in parallel across the entire firm when raising a new fund in 2005.

The authors also point at a potential endogeneity problem in this context as holding periods and deal performance might be co-determined.

Acquisitions/trade sales (and even secondary buyouts) could also be considered successful exit channels with satisfying returns. We control for this extended definition of a successful exit in Sect. 6.4.

Note that apart from industries, style consistency can be measured with regard to, e.g., investment stages, countries, and size buckets. Cumming et al. (2009) show that stage-style drifts in buyouts are more frequent for experienced investors and have a higher success probability. In the context of fundraising, however, we consider the industry dimension to be the most relevant, and it is one that can be measured with comparatively higher accuracy in our data.

In PE literature, the terms “size,” “experience,” and “reputation” are often used interchangeably in similar contexts as they are strongly related to each other (e.g., Hsu 2004, pp. 1820–1821; Nahata 2008, p. 131).

In accordance with our measure of industry-style consistency, we focus exclusively on the industry dimension of PE firm specialization.

The study reveals that only industry and geography specialization continue to have a significant impact when all three subvariables of specialization are controlled for at the same time.

This assumption is confirmed in our own sample. See Table 10 for the negative correlations of Industry Specialization and PEI 50 Sponsor, PE Firm Age, or Average Historical Fund Volume, respectively.

Examples of independent PE firms include KKR, CVC, and 3i. Note that some independent PE firms are private partnerships, whereas others are listed on a stock exchange.

Examples of captive PE firms include Intel Capital, Deutsche Bank private equity, and the Mubadala Investment Company.

These transactions are manually checked for correctness with regard to their exit status. The buyout-related variables provided by Zephyr (e.g., holding period or exit channel) are complemented by information on add-on acquisition activity for each transaction.

Per transaction, this can be up to 6 fund vehicles by the same PE firm investing in parallel.

This can be up to 10 co-investing PE firms per transaction.

Note that information on fund volume and target size is available only for a subset of all funds raised.

In our dataset, there are many funds raised in the 1990s; the first buyout entry (exit) occurs in 1997 (1998). We think that a gap of 3 years between first buyout entry and first follow-on fundraising is a reasonable minimum period in order to be able to relate follow-on fundraisings to the performance of buyouts in predecessor funds (see below).

As we observe the last buyout entries in our transaction database in the year of 2010, all fundraising events consequently also take place by 2010 the latest.

Ideally, PE firms start raising new funds after the committed capital of an existing fund is fully invested (usually after the “investing period” or during the “harvesting period,” both of which are approximately 5 years long). According to Kaplan and Schoar (2005, p. 1817) and Barber and Yasuda (2016, p. 9), fundraising takes place 3–6 years after the previous fundraising. Our chosen time window of 10 years relates to the distance between predecessor fundraisings and control group events and can be thought of as a maximum period. In Sect. 6.3, we adjust the time window for the installation of control group events downward to 8 and 6 years as a robustness check.

In line with our control group calculation mechanism, these are based on predecessor fundraisings in the years from 1990 to 2000 due to the addition of 10 years.

Note that with this approach we consciously exclude first-time funds from our investigation as different fundraising dynamics may apply to these compared to follow-on funds.

In contrast to our approach, other studies directly relate the last (Gejadze et al. 2015) or even second last predecessor fund (Kaplan and Schoar 2005) to a current fundraising event. Lee and Wahal (2004) use individual IPOs as the starting point and relate their performance to future fundraisings.

We check whether there is a match between the industry focus of a PE firm and the portfolio company’s industry of operation based on Fama and French’s 17-industries classification scheme.

This is based on the GDP growth in the PE firm’s headquarter country. Note that we do not take into account the GDP growth of target firms’ headquarter countries as fund vehicles usually invest across multiple geographies. If a fund has a single-country focus, PE firm and target firm headquarter country are usually the same.

We refrain from including inception year dummies in order to model time fixed effects given the sample size and number of other explaining variables. A boom period dummy has the same technical effect as inception year dummies, but at a more aggregate level.

There is a divergence from the total number of fundraisings (1463) of 325 funds, for which we do not possess information on the respective fund volumes.

This compares to, e.g., 866 USDm and 1465 USDm for predecessor and follow-on buyout funds, respectively, as shown by Chung et al. (2012, p. 3274). Barber and Yasuda (2016, p. 43) report an average buyout fund volume of 1532 USDm (948 USDm for mature funds) for the time period from 1993 to 2009.

Note that there are some PE firms that could be expected to appear on the list, but do not: 3i, for example, would be in the top 30 ranking by number of funds raised but Thomson ONE rarely discloses information on fund volumes for its individual funds.

This information is available for more than two–thirds of all funds raised by the top 30 PE firms shown in Table 3; data coverage therefore is clearly better than for the rest of the sample, which is likely due to increased disclosure requirements for larger GPs.

Note that we keep only those observations for which performance variables, which can be considered a major theoretical driver of fundraising activity, are available; see Sect. 3.1.

These were assessed in unreported contingency tables, which are available upon request.

Results on the more detailed Institutional Affiliation level with regard to follow-on fundraising outcome and volume are not reported, but available upon request.

See Hochberg et al. (2014), Kaplan and Schoar (2005) and Barber and Yasuda (2016), all of whom also use tobit models to predict the volume and growth of follow-on funds.

Control group events are technically set to a value of 0; all actually observed fund volumes are logarithmized (4 fundraising events with volumes below 1 USDm are excluded as the natural logarithm of these would be negative and thus below the left-censored events).

There may be several predecessor funds in parallel; see Sect. 4 for our rationale to not directly connect two consecutive fundraisings.

We take into account the consideration that larger PE firms typically raise larger funds than smaller PE firms by including proxies for PE firm size in our regression models.

Excepted from this is the correlation between PE Firm Age and Average Historical Fund Volume; however, these two experience/size variables are not included in any regression at the same time.

This again applies less when PE-firm-related variables are added, though.

Given the insignificant findings (see logit and tobit specifications 2 and 7, respectively), we exclude both variables from all following regression models.

Note that GDP Growth and MSCI Growth enter the estimations in basis points.

In contrast to our result, Gejadze et al. (2015) find that the amount of industry-wide capital raised (lagged by 1 year) increases the speed of follow-on fundraising for PE firms.

Consequently, we also exclude the Captive indicator from all model specifications.

In a second step, we extend the definition of a successful exit even further: except for receivership exits, all exit channels (i.e., IPOs, trade sales, and secondary/higher-round buyouts) are regarded as successful. Results look very similar to the ones reported in this robustness check and are available upon request.

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Titel: Fueling the buyout machine: fundraising in private equity
verfasst von: Robert Loos
Bernhard Schwetzler
Publikationsdatum: 02.11.2017
Verlag: Springer US
Erschienen in: Financial Markets and Portfolio Management / Ausgabe 4/2017
Print ISSN: 1934-4554
Elektronische ISSN: 2373-8529
DOI: https://doi.org/10.1007/s11408-017-0298-8

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