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Separating luck from judgement in private equity performance

Oliver Gottschalg, Associate Professor at HEC School of Management in Paris, discusses performance measurement in private equity, including why the industry needs to move on from Internal Rate of Return (IRR) and focus on measuring ‘alpha’ as a more meaningful metric, and how financial engineering distorts performance.

What does your research show are the most important performance measurement factors in private equity funds?

The important element here is that the industry is realising the traditional measurement factors for private equity funds - such as IRR and the simple multiple - is not enough to truly understand performance; particularly when it comes to anticipating future performance. It’s apparent that these measures overlook important aspects of performance and increasingly firms are looking towards the notion of performance measures on a relative basis using, for example, public market equivalent (PME) metrics where it’s possible to measure out-performance over time matched investments in broad equity markets.

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If a firm’s goal is to find sources of out-performance in the next cycle, you need to be able to find a measure that allows you to separate the luck component from the manager’s skill. If you look at the IRR or multiple, you have lots of drivers that boil down to luck. For instance, there could be macro tailwinds and the overall economic evolution that will push a fund into positive territory. That's basically luck, as it's randomly distributed.

However, there is an element of performance in private equity returns that is related to skill and that's the ability of the manager or GP to add value to transactions beyond the macro trend. This can be measured in a number of different ways, but it's essentially what I like to call alpha. It’s the annualised wealth creation above what the public markets have done at the same time. My research has found that this component of returns actually persists in a meaningful way over time. So if you want get insights into who is likely to win in the next cycle, you have to measure performance in alpha terms and not just in pure IRR terms.

Do you associate this alpha generation with the individual or the firm/strategy?

Distinguishing persistence from one individual or group of individuals within the firm from the magic of the firm, its reputation, its processes and the investment principles it brings to the table, was a focal point in my presentation at SuperReturn International this year. It’s a highly relevant question for investors as they're committing to funds with long lifespans, as decisions are made by teams and teams will naturally evolve over time.

It is still an industry characterised by human skill; who has done the deal really matters.

I've done some work to really get this level of granularity and disentangle these two facets using a unique database with a couple of thousands of deals where I can identify, not only the investing firm and fund family, but specifically the individual who is being named by the firm as responsible for that deal in the fundraising document. It’s obviously not perfect as you can argue that any one deal is not the result of a single decision-maker but, accepting these limitations, it’s possible to separate the performance of the individual from the fund family.

With this level of detail, it’s possible to take one individual and compare the average past performance of the firm and how well that predicts the performance of the next deal, versus the average past performance of all deals done by that individual and how well that predicts that individual's next deal performance. Using this statistical model, the role of the individual has a greater influence than the firm, confirming the intuition that it is still an industry characterised by human skill; who has done the deal really matters. To quantify this in ballpark terms, the impact of the individual is roughly twice as strong as that of the firm. The past performance of the individual is also more powerful in predicting the success or failure of their next deal than that of the firm.

This has implications for investors who need to be careful to monitor stability in teams. A firm may have a good track record, suggesting the next fund will also be good if you believe in persistence, but if the key people have left, that should ring alarm bells. On the flip side, with many groups spinning out of established franchises at the moment, if an investor can get a realistic sense of what they have done at their prior employer, it may ultimately help inform the decision as to whether that spin out might be a success or failure in the next cycle.

Research suggests that persistence of returns across private equity funds has gone down in the last decade. Is this consistent with your research?

Based on the traditional way of measuring returns that measures compound luck and skill, yes that is true. Performance persistence using the IRR as a measure is decreasing and essentially gone over the last decade or so of buyout funds.

But there is persistence when you look at alpha generation and focus on the skill of the manager. My research shows that by selecting managers based on alpha rather than IRR, you can expect meaningful performance improvement of up to 400bps in the next cycle. That should be a very strong reason for managers to do whatever they can to measure indicators of past skill rather than luck.

Is this alpha/skill component something that's increasingly being asked for by LPs?

It’s certainly becoming a bigger part of the conversation. The industry tends to move at a very slow pace and I don't think traditional measurement will ever be entirely replaced. IRR is a horrible performance measure but it's always been there and it's not going to go away. Incentives are tied to it, reporting is tied to it and CIOs are used to seeing it. For those reasons it's not going anywhere and it's not my objective to change that.

My objective is to provide another measure that makes it easier to find the next winner to maximise alpha and maximise IRR. Since making the measure freely available to ILPA members via a piece of spreadsheet based software, it’s gained around 160 users. From a membership of 400, that’s a pretty overwhelming uptake and makes it clear to me that there’s an appetite for this alpha measure in the industry.

Adoption is one thing, but the other component to establishing it is to shift industry benchmarks to include the measure as well. This is something we're making progress with. We already publish our own reports, but we’re in advanced conversations with a number of industry benchmark providers and at some point this year, I am confident that we'll see them added to one, if not several, standard benchmarks.

Private equity firms are increasingly using the likes of subscription credit lines. Are these distorting traditional measures of performance?

Absolutely. The IRR measure has a very inconvenient feature in the way the maths works, making it sensitive to what happens very early on in the stream of cash flow. If you have very extreme positive cash flows or outcomes early on, the IRR tends to be kind of locked in and you have a systematic upward bias to returns throughout the life of the fund. The same is true on the downside; if you get off to a bad start, it's very difficult for purely mathematical reasons for the IRR to catch up again.

Since benchmarks don’t distinguish between who’s been bridging and who’s been lucky with their bridging, it doesn’t really tell you anything about where the industry actually is.

Now, with this in mind, if you look at the impact of these fund subscription lines, you can easily see that if you enrich the cash flow and push back the first time the fund calls capital from the investors by 6, 9, 12 or even 18 months, that changes the cash flow pattern early in the life of the fund. It can trigger a bias in the performance outcome of the fund even when looking 8-10 years down the road. So there’s an element where financial engineering - irrespective of whether you think it’s a good or bad thing for investors - triggers a bias for those funds that have been lucky with an early extreme distribution.

Circling back to the point I made at the start about separating luck from skill, the use of bridge facilities basically dramatically amplifies the luck element, at least for a certain number of funds out there. This has implications for all kinds of things you want to do with performance. A fund may have a 50 percent IRR just because of this bias, but the fundamental performance could have been lousy; you could look at the 50 percent and think you have a superstar, but if you look at the actual dollars in your portfolio earned, it may not be so impressive. And that’s just the backward-looking measurement.

Of course, it also distorts benchmarking, since benchmarks don’t distinguish between who’s been bridging and who’s been lucky with their bridging; it doesn’t really tell you anything about where the industry actually is.

It has an even greater impact on forward-looking measures. What persists is skill and not luck. If the luck element is being amplified by the use of credit lines, it makes it impossible to find the next winner purely by looking at IRR. Measuring alpha isn’t perfect, but it's a fix that solves 60-80% of that problem.

Under the spotlight: Oliver Gottschalg

Oliver Gottschalg SuperReturn US EastProfessor Oliver Gottschalg is Head of Research at PERACS, a specialized advisory firm providing advanced private equity fund due diligence and benchmarking services. He is part of the Strategy Department at HEC School of Management, Paris. His current research focuses on the strategic logic and the performance determinants of private equity investments. 

Oliver Gottschalg will be speaking at SuperReturn US East 2018 in Boston. Find out more >>

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