- A quality index can serve as a meaningful benchmark to evaluate performance when investing in active managers and hedge funds.
- However, over $4.5tn of global hedge fund capital is benchmarked against inaccurate and often misleading indices.
- Flawed indices negatively affect asset allocation models, decisions to add or redeem capital from a fund, and ability to assess manager performance.
- To determine index quality, investors should assess the underlying data, methodology of construction, presentation and insights offered.
Investors looking for quality hedge fund insights can review PivotalPath’s monthly Hedge Fund Insights report, presented in collaboration with Macro Hive. To get the first report direct to your inbox, sign up to Macro Hive Lite.
The Problem With Hedge Fund Indices
When evaluating hedge fund performance, a quality index can serve as a meaningful benchmark. The index you choose may help determine your overall asset allocation or be the difference between investing in or redeeming from a manager.
But quality indices have historically been few and far between, leaving allocators with a very limited and often misleading visibility into the returns different managers can generate. For example, recent research found that due to incomplete data, the actual size of the hedge fund industry is as much as 40% larger than most common estimates of $3.5-$4.2tn, and performance metrics are grossly understated.
Indeed, over $4.5tn of global hedge fund capital is benchmarked against inaccurate indices. But how did it get to that stage?
- Hedge funds lack incentive to participate. Many do not report at all, and the rest only do when it benefits them.
- Indices often fail to protect confidential manager data, selling to anyone willing to pay. This destroys manager trust.
- Managers choose strategy classifications, diminishing index quality.
- Inconsistent and incomplete fund representation leads to inadequate results.
It Is Like Buying a Car…
When you are looking to buy a car, you probably review several high-profile websites that contain listings of available makes and models that fit your search criteria. But what if these websites each omitted a significant portion of the total car market? And what if your limited data sample was itself not accurate and complete in terms of price and availability? And lastly, imagine if each website presented its information as comprehensive and accurate.
Would you buy a car based on flawed data? Unfortunately, this is a daily experience for institutional investors, especially hedge fund allocators.
Historically, the only thing an asset owner could do to address these shortcomings was to build indices or peer group benchmarks themselves. That requires substantial resources and technical knowhow. Other than a few sovereign wealth funds and large pension plans, few have even tried. Additionally, even with the best intentions, internal indices lack independence and incorporate biases of their own.
Evaluating a Benchmark Index
So, how can an investor determine whether an index is high quality and serves as a meaningful benchmark? Based on our experience, it comes down to four questions:
- What are the data that go into it?
- What is the methodology used to construct it?
- How is the information presented?
- Is there more to the index than just the average?
Data – Is It Complete?
To revisit the car analogy, say you wanted the best electric vehicle and used a leading car research app for your search. But as you dig in, you learn the app does not include Tesla Inc., Toyota Motor Corp., BMW Group or Honda Motor Co. – simply because those companies choose not to provide their information.
The analysis would be incomplete and missing many of the established industry leaders. As a result, your view of the electric vehicle market could be significantly distorted. Technically, there would also be a negative selection bias regarding companies that choose to provide their information. So not only are you missing the full market; you are also experiencing a bias toward companies that choose to provide their information versus those who do not.
Institutional allocators experience these same issues in the hedge fund industry every day. Trillions of dollars of hedge fund assets are often benchmarked to indices that not only have material gaps in their data but may also be missing many of the highest quality funds. Problematically, such indices likely create an artificially low bar and apples-to-oranges comparisons. Just like any poll or survey, if the sample is not representative of the population, it devalues the results.
Methodology – How Is the Index Constructed?
Let us examine just one major issue: data collection. Many hedge fund indices often rely on managers opting into their indices. However, such managers often disagree on when to provide their information. And many hedge fund marketers decide each month whether to post their returns to an index portal at all.
An extreme example would be March 2020, the height of the initial wave of COVID-19. Many hedge funds, especially those that suffered large losses, chose not to provide their return data to index providers on their regular schedule. Some waited weeks until after they communicated with their investors, while others waited months to see if their returns would rebound. Some stopped reporting altogether.
Monthly decisions by managers to withhold their data, especially during times of poor performance, can create a short-term survivorship bias. This bias artificially enhances and smooths performance in a way that is not representative of the index’s normal sample of reporting funds.
Meanwhile, an index may be constantly revised in the future because those who rebounded begin reporting again – some filling in their historical return gaps and others leaving gaping holes. This makes reconciling performance relative to indices that much harder, as they are in constant flux.
Also, these short-term irregularities in index performance, when combined with longer-term selection biases, can add up even for investors with long-term horizons, as their asset allocation models rely on accurate and representative monthly data.
Presentation – Are They Jumping the Gun?
Hedge fund performance is typically provided monthly. Accordingly, hedge fund indices usually follow the same monthly cadence. Based on the liquidity of the strategy, it is reasonable that hedge funds provide their previous month’s returns to index providers throughout the following month. The less liquid the strategy, the longer the returns usually take to report.
However, index providers often race to be the first to publish each month, regardless of whether their numbers are stable. Most hedge fund indices are sent out without reference to the number of funds, percentage of those likely to report, how much has already changed, and how much is likely to change. Consequently, indices fluctuate daily and throughout the month.
Without transparency into the stability of the number reported, it is just that: a number. And investors consequently lack confidence in the number to benchmark their managers and communicate performance to their clients or board/investment committee.
Insights – More Than Just the Average?
Averaging a large distribution hides the best performers among the rest. And the broader the index, the more the average hides.
For example, the mean return for a hedge fund composite index would obscure detail on the many unique sub-strategies included. It could generate sweeping conclusions about a fund or even the industry which, by design, would underestimate the value of its parts.
Remember that what is true in the aggregate tells you nothing about the distribution around the mean. An index that reports a return over a time horizon merely provides the average of all the fund returns that have been given to them at that point in time.
Being able to break performance down by cohort and quartiles with transparency at the constituent level helps you evaluate your hedge fund investments in the right context. It may even help you separate the best from the average.
The Bottom Line
Evaluating hedge fund performance is difficult. While indices can add important clarity, not all indices are created equally. That is why Macro Hive has teamed up with PivotalPath to offer readers access to high-quality hedge fund insights derived from industry-leading indices.
Every month, on behalf of over $250B in client hedge fund capital, PivotalPath tracks over 2,500 institutionally relevant hedge funds, spanning over $2.5tn of industry assets.
The monthly report contextualizes these data points, including analysis of hedge fund performance, as well as 12-month rolling alpha across high-level strategies. And it provides average monthly performance of funds within separate AUM bands.
You can sign up to Macro Hive Lite to receive the first report direct to your inbox.
PivotalPath is a trusted hedge fund industry expert. Harnessing its hedge fund research and analytics platform, PivotalPath consults exclusively with institutional investors whose hedge fund investments comprise over $250bn. By using PivotalPath, clients can leverage the industry’s most comprehensive set of hedge fund data, accurate indices, and robust analytics to evaluate, benchmark and monitor their hedge funds.
We have built significant trust and lasting relationships with hedge funds through transparency and by ensuring that allocators evaluate each manager in the right context. PivotalPath protects confidential manager information and only shares insights with its institutional investor clients.