How Investors Can Avoid Making Bad Co-Investment Decisions

Co-Investments provide a layer of customization, flexibility, and advantageous fee structures that institutional investors gravitate towards. Often, their terms can be influenced by the amount invested, making it particularly lucrative for large asset allocators.

However, the associated risks aren’t solely based on picking managers with strong performance. Because Co-Investors rely on the investment manager to demonstrate proper due-diligence, there’s a hidden risk in conflating the historical performance of a fund with the fund’s demonstrated value-add in the target area of the co-investment.

Ignoring this fact, evaluating the risk/reward of a co-investment can be like flying in the dark. To tackle this problem, Novus clients leverage our analytics platform to perform skills-based analysis on prospective managers. We’ll walk through a hypothetical co-investment pitched by two activist investors’ public regulatory filings—Blue Harbour and Pershing Square—to show how a prospective co-investor can utilize the Novus platform and make better allocation decisions.

Understanding Core Competence

Imagine both of these funds pitch a co-investment idea with an identical deck. The idea represents each manager’s highest conviction idea, which will soon be their largest position. The positions are coincidentally both tech companies that the managers believe represent a significant value opportunity. Of course, neither fund is willing to disclose the underlying name prior to the co-investment agreement.

Novus arms investors with tools to accurately evaluate these identical propositions. The first: to measure the annualized return on invested capital that each fund has generated in their highest conviction positions. Second: to analyze the security selection alpha both funds have generated in their historical InfoTech securities. And third: to perform a cross dimensional analysis and provide tangible examples of the manager’s position-level track record. Using our platform, we’ll walk through these steps for both funds and decide which proposition is more lucrative.

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Blue Harbour

Analyzing position-sizing skill is essential for a prospective co-investor, since you have to know whether a manager has a track record of generating outsized return in high conviction positions. To start, we’ll bucket every position the manager has filed into position-size categories that are dynamically calculated over time. Next, we take the return on invested capital of the underlying securities across these different time periods to isolate the highest conviction names. The chart below demonstrates the 10-year capital allocation and track record for Blue Harbour across position size buckets:

An investor can quickly see that Blue Harbour has allocated meaningful capital over time to its highest conviction ideas (>10% of reported assets). In those positions, it has generated the highest annualized return of any position size bucket. This is a great thing for a prospective co-investor to see; a direct alignment of conviction and outperformance.

Next, an investor should look to sector skill to see if Blue Harbour has demonstrated competency in its historical Information Technology positions. Here, instead of simply looking at return on invested capital, you can look at security selection alpha as a measure of competency. That way, you can control for the way that various sectors have performed dynamically over time and truly strip out the beta associated with any investment.

The charts above demonstrate that Information Technology is a core portion of Blue Harbour’s capital allocation, and it represents the bulk of the security selection alpha it has generated across all of its publicly filed positions. Again, very positive signs for a prospective co-investor.

Finally, a quick analysis of high conviction positions in IT allows the investor to see that Blue Harbour generated significant alpha on high conviction technology stocks. Below, you’ll see that names like Rackspace Hostings, Savvis, and Brocade were terrific performers, while only CACI Int’l and WebMD detracted alpha. In fact, out of high conviction tech names, the fund has generated in excess of $665mm of simulated PnL, of which half can be attributed to security selection alpha:

Pershing Square

Going through the same exercise with Pershing Square, an investor can also deduce that Bill Ackman—like Cliff Robbins—has a strong record of outperformance in high-conviction positions. As you’ll see below, unlike Robbins, the lion’s share of his allocated capital falls into positions that represent greater than 10% of the fund’s reported assets:

While this is a good start in regard to evaluating Pershing’s conviction, when you look at sector competence below, you’ll see that outside of periods in 2006 and 2009, Pershing has not historically invested in Information Technology names. Perhaps more troubling, the fund has generated very little security selection alpha in these names:

As in the chart below, when looking across those high-conviction Information Technology names, you can see limited investments in high conviction tech securities like EMC, Ceridian, and Visa. You can further drill into a position such as EMC to see how the manager traded it over the period it was publicly filed:

Conclusion

Co-Investments are tricky, because their opacity makes it challenging to analyze the underlying product due to the confidential nature of disclosing the investment target. Investors often gravitate to a manager’s track record in evaluating a prospective co-investment. However, with detailed historical analysis, Novus clients can assess managers’ proficiency with historical context to make qualified judgments about risk and reward. On the surface, an esteemed fund like Pershing Square may seem like a prime-candidate for this hypothetical Co-Investment, but this example shows that Blue Harbour is the better choice. The devil is often in the details.

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