Repeating Top-Quartile Performance Gets Tougher

The weight of academic research has been tilting in an unsettling direction, toward the notion that sponsors with top-quartile funds can’t repeat that performance the next time out at a higher rate than other firms. That is bad news for top performers banking on a sterling track record to carry them to fundraising success.

Using 1974-2010 deal-level data, mainly U.S. and European, collected from three managers of funds of funds, a new paper finds that about 34 percent of buyout firms with top-quartile funds, as synthesized by the authors, repeat in the top quartile based on investment multiple the next time out. At the same time, those in the bottom quartile wind up there again the next time out at a slightly higher frequency (about 36 percent of the time). Those findings are consistent with the peristence of performance the industry has been known for. However, the authors found top-quartile persistence disappearing when training their focus on just post-1998 vintage “synthetic funds.”

“Private equity has, therefore, conformed to the pattern found in most other asset classes where past performance is a poor predictor of the future,” the authors wrote. They added that the “drop in persistence is particularly pronounced among the top quartile more experienced fund managers.”

The paper, “How persistent is private equity performance? Evidence from deal-level data,” lends additional credibility to similar findings from earlier academic studies. This includes an April 2013 paper, “Has persistence persisted in private equity?”, based on actual fund data provided by Burgiss Group, a provider of portfolio management services to institutional investors. The latest paper is co-authored by Reiner Braun, professor at Friedrich-Alexander University, Erlangen-Nuremberg; Tim Jenkinson, professor at the Saïd Business School at the University of Oxford (also a co-author of the April 2013 paper); and Ingo Stoff, a PhD student at the Technical University in Munich.

The authors make a case that studying deal-level data—they look at cash-flow data for more than 10,000 portfolio companies managed by 236 sponsors—marks a step up in robustness from methodologies used in earlier studies on the subject. Past academic research has mainly focused on the performance of actual funds, a practice the authors call “problematic” in part because many funds include unrealized deals whose ultimate returns are unknown. Another problem has to do with the differing speeds with which actual funds are deployed. Is it fair, for example, to compare a vintage 2007 fund invested entirely in the pre-financial-crisis year of 2007 with one invested at a more leisurely pace over four or five years?

Deal-level data let the researchers side-step these problems. To avoid the corrupting influence of unrealized deals they zeroed in on the 6,195 fully-realized investments in the database. They also constructed what they call synthetic funds to improve the comparability of returns; each fund, consisting of eight deals, was assigned a vintage year based on an investment-size weighted average date of the eight investments. “In this way, when measuring the relative performance of GPs, we are able to control for the timing of investments in a much more precise way,” the authors wrote.