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 is what is 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 with the type of companies that PE funds invest into… all of this is in the book. Fact and matter is that for many years, people kept on saying that PE funds outperformed the S&P 500 by 3-4% p.a. and that was great (see a related blog). Over the last 10-12 years 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 help by PE funds but MSCI world has the advantage of having low returns over the last decade.

To keep it simple and focused, let’s keep it to the 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, average PME 0.97 (median is 0.98), TVPI (total value and distributed compared to invested) of 1.46.

Of these funds 1518 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 not 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.

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 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 others) 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. And 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. The next five years, make if one third of that amount (very much a lower bound) and you are above $200 billion. And then you would need to add all the other fees and expenses.

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 end up with a precise estimate. With what I have, the above is the best I could do.