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When is it time to throw in the towel?
Last week, Goldman Sach announced that it was replacing the sub-advisors at its flagship US multi-manager mutual fund (GSMMX) with strategies run by an internal quant team. Over the past ten years, this fund had returned 1.3% per annum after around 200 bps in fees and expenses.1
During the multi-manager gold rush of 2014, assets exploded to nearly $1.8bn, only to dwindle slowly to the current $138m.2 Presumably, this change will lower fees and (hopefully?) improve performance.
Remarkably, Goldman’s sister SICAV seems to have done worse. And in Europe, Goldman is not alone. Hedge fund luminaries like Blackstone and Franklin K2 have stumbled, as have most of the wealth managers that launched products for their own clients.
In fact, according to Kepler, the average multi-manager UCITS hedge fund product has returned less than 1% per annum over the past decade – after what appears to be, on average, at least 200 bps in fees and expenses.3
Something is wrong. Michael Weinberg and I raised serious concerns about the whole space early on. In 2014, we wrote a paper about the potential for systemic “performance drag” that would result from jamming unconstrained hedge fund strategies into regulated vehicles.
It was like asking a mixed martial artist to use only his feet. We had scant data, but what we had was damning. We predicted 200 bps of performance drag (net of fees) relative to hedge funds of funds: in essence, more alpha was lost due to constraints than was saved in fees.
Given that funds of hedge funds historically have delivered several hundred bps over cash, that’s a serious problem. Nearly ten years later, those conclusions look prescient.
The question today is, what can we learn from this debacle? How did so many smart allocators walk into this propeller? A few lessons:
First, be very wary of marketing pitches for new product ideas. Sometimes, the absence of a real track record itself is a marketing advantage. Lacking live numbers, many firms used hedge fund indices – sometimes data replete with selection bias back to the 1980s — to underscore the potential diversification benefits. Advisors bought the story and threw money at these funds.
Second, spot the marketing race to the bottom. While Goldman, to its credit, prudently set return expectations lower than hedge funds, more aggressive firms stretched the truth to ramp up sales.
One hedge fund of funds firm was telling potential investors that its mutual fund product could deliver 10% before fees, or 7.5% after fees and 2.5% more than an actual fund of hedge funds. Serious allocators stared at this page and wondered: when, pray tell, had this firm ever delivered cash plus 10% before fees?
Third, ask non-obvious questions. Our initial research was based on a simple question: which hedge funds had refused to manage sleeves within these new funds?
One top tier manager said that they were, at first, interested but then studied the impact of running their strategies within mutual fund constraints; his conclusion, “there are easier ways to earn LIBOR.”
We asked questions about overlap: few of one leading activist manager’s top ten positions were included in the mutual fund version. If a firm tells you about its hedge fund manager selection acumen, demand hard data to prove it.
So here’s a thought experiment. Imagine that you had asked those prestigious firms ten years ago, “what is the probability that you’ll return cash-like returns with far more risk over the next decade?” My guess is the answer would have been “zero.”
Which raises a troubling question: if these guys so badly overestimated the return potential back then, why should anyone believe claims today that returns will be better going forward?
Like Goldman, is it not time to recognise that the products have serious structural headwinds, even perhaps fatal flaws? And if we accept this, then shouldn’t allocators migrate to products that are better suited to perform within UCITS constraints?
Are you a fund manager or allocator? Have your say on this issue, or any other, by submitting a comment piece to AFI. Email firstname.lastname@example.org.
1: GSMMX share class. Bloomberg and DBi calculations. June 2014-May 2023.
2: Bloomberg data.
3: Kepler Absolute Hedge database. DBi calculations. Fees are estimated based on stated management and performance fees.
Opinions expressed reflect the author’s views and not Alternative Fund Insight, published by AFI Media Ltd.