Biggest Hedge Funds By Assets Under Management March 2017

This the March, 2017 post in my series on biggest hedge funds by regulatory assets under management. 14 firms on this list of 61 firms filed updates to their Form ADV since the previous post in this series. I delayed the posting by 2 weeks to ensure the freshest data. In addition, I have added in the $bn AUM figures from a year ago for comparison. I plan on making little variations each month to keep the post interesting.

When I published a link to the previous post on LinkedIn, it generated comments around a couple of interesting aspects of the data that I thought I might address here:

• The $AUM numbers are different from what you commonly see published. The numbers you usually see, and everyone talks about, are the fee-basis $AUM. The SEC defines $AUM differently: It is the market value of the manager’s portfolio and may include cash equivalents at the manager’s discretion. A highly leveraged strategy will report a higher (sometimes, much higher) $AUM than would be reported in the “league tables”. Contrary to what you might expect, a managed futures strategy (which will typically use notional funding in separately managed accounts) will tend to report lower $AUM than you would expect. Futures are not securities therefore the manager simply reports margin that investors have deposited which is typically smaller than nominal trading level.
• The employee numbers don’t reflect the use of sub-contract traders or sub-advisors. If you find two managers who you thought were similar yet one has far more employees per $AUM than the other, try to figure out what the data is telling you. There is information here about how the managers are implementing their strategies.
• Is the data “accurate”? My expectation, given the huge downside to reporting inaccurate data to the SEC, is that the data is meticulously accurate. Having said that, I have come across some obvious errors. The SEC specifies in detail how the numbers are to be calculated, and this specificity makes the data valuable. Once again, there is information in the differences between what you expect and what you see!

My intent with publishing this data is to show how you can explore competing business strategies in the hedge fund world using easily accessible data.

Check out your own firm’s Form ADV at the SEC’s Investment Advisor Public Depository website – you may be surprised at how much information is in there. Imagine how useful it would be to have all that information on your peers in a spreadsheet and to monitor how it evolves over time.

Contact me to discuss customized reports and analysis.

And the world’s biggest hedge funds by regulatory assets under management are …

This table covers the same 61 firms as the previous post. These are the standalone firms that are not part of an affiliated group with more than one active RIA. Some firms you expect to see will be missing and they are covered in the full file available for download. See Methodology below for more details.

Observations

Of note in the table below, we see the five managers whose regulatory AUM decreased the most at the fastest percentage rate:

• Tiger
• BTG Pactual
• Eminence
• Odey
• Bluecrest

And the five managers whose regulatory AUM increased the most at the fastest percentage rate:

• Trian
• CQS
• Tudor
• Carlson
• Balyasny

Once again, remember this may not mean they have gathered AUM or suffered redemptions, it may be that they have adjusted their leverage by a significant amount, or have undergone a corporate restructuring (I believe Bluecrest spun off Systematica).

Overall the change in total AUM was about -4%, but the average rate of change was very close to zero. This suggests the largest managers have reduced their portfolio sizes. Is this simply a change in leverage or are the smaller giants getting some love?

Note: click column headings to sort. Use drop-down to set number of rows per page.

The March file is no longer available. The button will deliver the current version.

Contact me to discuss customized reports and analysis.

Methodology

In order to complete the research for this post, I made use of a script in R using the RSelenium package. I have previously published a post about how to set up RSelenium using the latest version of Selenium, and an earlier post reviewing some of the most useful functions in the package. This package makes it possible to automate the collection of data from websites; the process is called web-scraping.

My starting point was Institutional Investor’s Alpha Hedge Fund 100 dating from May of 2016. I used each of the firms on the list as an entry point into the network of related firms that make up what I call an affiliated group, one or more of which will be a hedge fund.

Affiliated Groups

Ideally, after eliminating the inactive firms, brokers, and the Exempt Reporting Advisors (ERAs), from an affiliated group, one is left with the hedge fund firm you are looking for. This was the case for 61 of the original 100 firms. In this first post, I have excluded any firms for which there was more than one candidate firm (even when it was obvious which is the “hedge fund”). For example big groups like Blackrock, J.P. Morgan, Goldman Sachs, BNY Mellon, etc. and small ones like, Man Group, Paulson, Two Sigma, Winton, etc. have been excluded (for now).

Companion Post: Mining for Gold

I have published a companion post on the Form ADV and the information it provides for competitive analysis and benchmarking (Hedge Fund Competitor Intelligence: Mining for Gold in Form ADV). I also plan some posts focusing on specific areas of the ADV with some examples.

Image Source: Royalty-free image from Pixabay by “tpsdave”