Burgiss is perceived as one of the most comprehensive and accurate database of private equity fund cash flows. Using their software (private iq) we can compute quickly some meaningful aggregate performance estimates. They just released the March 2018 data. Let’s look.

As you know (see chapter 11 of the book), NPV/PME measures are currently the best tool. You also know that the choice of the benchmark is important. Each index is an active trading strategy, hence different indices perform differently… the S&P 500 index is the most famous one but the type of stocks it holds and trades are not comparable to the type of companies that PE funds invest into… all of this is in the book. Anyway, for many years, people compared PE funds performance to that of the S&P 500, and the S&P 500 performance was not good and PE outperformed the S&P 500 by 3-4% p.a. Over the last 10-12 years, however, the S&P 500 has been doing well and now people tend to use other indices as benchmarks (e.g. MSCI world); this still has little to do with the type of companies held by PE funds but MSCI world has the advantage of having low returns over the last decade. Hence, the music is still playing: PE outperforms the MSCI world at any horizon.

To keep it simple and focused, let’s keep to tradition and compute PMEs with the S&P 500.

Next, let’s go on the positive side: eliminate vintage years 2016-2018 because these funds are young and as of now have a PME below 1 (i.e. underperform the S&P 500 index), eliminate debt funds, and keep only equity and real asset funds. These funds basically do either LBOs (be it applied to real estate, infra…) or venture capital no matter how they call it. We would think any of these investments has a beta above one hence the benchmark needs to be higher than the stock-market but we are on the positive side… hence ignore all that (just like liquidity issues etc.)… and select only western Europe and north America (they have the best performance)

Take ten vintage years, this brings us: vintage 2006 to 2015 and performance is as of March 2018. Total fund size $2.2 trillion, 2424 funds, TVPI (total value and distributed compared to invested) of 1.46, average PME of 0.97 (median is 0.98). Hence, slight under-performance of the S&P 500.

As a side note: Why are other data providers showing different statistics over past 10/15 years wrt S&P 500? Because they use a so-called end-to-end NAV internal rate of return. Hence the performance they report for the last 10 years, say, include funds raised in 2003-2007. The above analysis include only funds raised after 2006 and thus simulate the experience of an investor starting in 2006 who bought a representative set of funds. In addition, as you know (from the book and elsewhere) an internal rate of return is NOT a rate of return. Remember #IRRelevant.

Of these funds, 1518 funds already have an IRR above 8% and they have a total size of $1.52 trillion, and a TVPI of 1.64. Carried interest charged and latent (i.e. carry due on what is not exited yet) is unknown. We can proxy for it by saying that 1518 funds are above their hurdle, have a total size of 1.52T and carry due given their TVPI should be in the ballpark of 20%*0.64*1.52T= $195 billion.

It is a rough estimate, there are some implicit assumptions but nothing dramatic. Also, this is assuming that the funds not currently in-the-money have never been above 8% (hence have not charged any carry) and never will. It also takes the carry out of the reported net TVPI while carry is taken out of the gross TVPI (and is therefore higher)…

You can change sample construction, assumptions etc. this estimate is quite stable. For example, you could select only US LBO funds. PME for this subsample is better: 1.04 (i.e. about 1% outperformance of the S&P 500, p.a.), total size is $773 billion. Funds in the money have a total size of $567 billion and a TVPI of 1.67. Total carry would then be $76 billion.

In both cases (and in many other cases) the situation is the same: carry is about 10% of the amount of money raised and performance is about that of the S&P 500 index. Note also that the absolute amount of money we are talking about is large.

For other fees (management fees, portfolio company fees, expenses) it is a lot more difficult to have an estimate. But a management fee of 1.5% of fund size for five years is a lower bound, which means 5*.015*2.2T = $165 billion. For the next five years of a typical fund’s life, make if one third of that amount (very much a lower bound) and you are above $200 billion in total. And then you would need to add all the other fees and expenses… which brings us a bill of $400 billion (conservative estimate) and a performance (at best) close to that of the S&P 500 index (but, yes, better than that of the MSCI world index, and of some Russell indices).

If the PE industry finds the above unfair despite my best effort, it is welcome to make data on fees and expenses available to a group of diversified academics and I am sure we will manage to count and to end up with a precise estimate. With what I have, the above is the best I could do.

Merci pour la couverture de mon travail et pour votre travail de dissemination et d’education. C’est tres bien ecrit

Sorry, but for clarity are you saying that after fees the PE funds are underperforming? Or are you just highlighting that a lot of fees are paid in absolute $ terms?

Your prior posted on the link above calculates estimated % costs p.a. but linking that to the the gross returns on the respective asset classes yields the real answer. Are these returns in your book?

Thanks.

Jamie

Yes, the PME is after fees. It shows how much was paid to obtain this (after all fees). As I wrote on another post, this is also useful when thinking about the expected returns because gross all returns are expected to be lower, but most of the fees are fixed… which may create a bigger problem for net of fees returns.

And yes, the book has a much more comprehensive discussion of fees and returns gross and net