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Why 90% of Crypto Funds will fail

Let’s start with a story. By now most should be familiar with the infamous $1M bet between Warren Buffett and Ted Seides from Protege Partners. If you’re not here’s a quick summary: “The Million-Dollar Bet — Warren Buffett’s 10-year wager that the S&P 500 would outperform a sampling of hedge funds — whereas Buffett is betting (with his own money, not Berkshire’s) on the stock market performance of an S&P 500 index fund while Seides and his partners at Protégé Partners, a New York money manager, is banking on five funds of hedge funds (the names of which have never been publicly disclosed) that Protégé carefully picked at the outset.

Through the first seven years of the ten year bet, Vanguard’s 500 index fund, as represented by its Admiral shares, were up 63.5%. That’s the portfolio carrying Buffett’s colors. Protégé’s five hedge funds of funds are, on the average were up an estimated 19.6%. Buffett officially “won” the wager; over the course of the bet the S&P 500 index fund returned 7.1% compounded annually, significantly more than the basket of funds selected by an asset manager at Protégé Partners. That basket only returned an average of 2.2%.

The Problem

There has been a lot of interesting analysis as to why hedge funds fail (approx 1000 closed in 2017) and fail to outperform, causing them to shut down. Howard Gold concluded in a column for MarketWatch that it’s mostly a problem of supply and demand.

“Essentially, the ability to consistently beat the market is a vanishingly rare talent. Investors who were early in the hedge fund game saw some distinct advantages, which only drew in more investors. The resulting flood of money, some $3 trillion in total, created demand for which there is no natural supply — managers who deliver repeatable, above-the-market returns after fees.”

Great — but how does that relate to crypto funds? Let’s dig a little, first by using another historical data point from traditional funds.

One in three funds fail

As John Lanchester wrote in the New Yorker most hedge funds fail: their average life span is about five years. Out of an estimated seventy-two hundred hedge funds in existence at the end of 2010, seven hundred and seventy-five failed or closed in 2011, as did eight hundred and seventy-three in 2012, and nine hundred and four in 2013. This implies that, within three years, around a third of all funds disappeared. The over-all number did not decrease, however, because hope springs eternal, and new funds are constantly being launched.

As we look to crypto funds we see that the growth in fund formation from 2016 to now has been dramatic.

Autonomous Next Research

According to Autonomous Next: “Our crypto ecosystem database contains 780 entries, of which over 500 are crypto funds, with $10–15 billion in assets under management. Using the historical reference of 30% failure rates of “traditional” funds one could speculate that approximately 150 funds would shutter in the next 6–12 months. As this is not yet a traditional asset class (*Morgan Stanley has recently mentioned crypto is now becoming an institutional asset) one could theoretically increase that failure rate to every two of three funds, or +60% of those in market now. That would get one to approximately 330 fund failures in the next 6–12 or 24 months.

To put things into perspective the total market cap of all cryptocurrencies in January 2016 was around $7 billion. By end of 2017, within just 2 years, the crypto market cap had increased to a whopping $760 billion. The resulting flood of money, like it did in traditional hedge funds, created demand for which there is no natural supply — managers who deliver repeatable, above-the-market returns after fees.”


Why? Let’s take a look at some factors such as AUM as it relates to liquidity risk, portfolio diversification & duplicity of offerings, perceived concentration risk from LP’s and more. .

AUM, Risk Management and Concentration Risk

Crypto Fund Research

As we see illustrated a majority of crypto funds in the market have $50M in AUM or less, with outliers like the recent raises from firms like Paradigm and a16z that have brought in significant amounts of capital ($400M and $300m respectively).

Some Ranges

Of the 300 funds in the $10M or less bucket it’s an assumption but based on observation I will say that 200 (~70%) of those are around $5M or less and that 100 (~30%) are closer to the $10M mark. Of the 188 in the $10M-50M range I think it’s also fair to assume that approximately 100 (~53%) are in a range more likely between $30–50M, whereas the remainder (47%) are in the $10–30M range. This is total would leave us around 288 funds that are straddling between $5–30M in AUM currently.

Risk Management

Let’s run a hypothetical based on some observations: fund ABC is sitting at $15M in AUM; the manager was a bit more aggressive, perhaps very bullish at the end of ’17 to the beginning of 2018 and ignored some more institutional traditional risk management processes. Instead of running a 10/30/60 book — whereas 30% of your AUM is put into active allocations and 60% is held for reserves and 10% into fees, you ran your book like this: 10/45/45 or 10/55/35.

At 55% out to market you’ve now allocated $8.25M, leaving $6.75M in reserve; if we used the Bitwise 10 Index as a marker you’d be down -68.55% or $5.6M with about $2.6M left, plus reserves, totalling $9.4M. If the fund manager would have applied more traditional risk management principles you would have exposed your fund to $4.5M, lossing ~$3M but maintaining $11.5M. Remember, to live another day you must deliver repeatable, above-the-market returns after fees; if you can’t do that then the next best thing is NOT losing a lot of your LP’s capital.

A quick side note here too: the tools used for professional portfolio management have just started coming to the crypto market; there are at least two that come to mind that will help newer managers with these problems.

Lock Up Periods

A quick note here — of the 500 funds in market right now not all play by the same standards; lock up periods are put in place essentially to help managers avoid liquidity problems while capital is put to work in investments. Of the more “liquid” funds I have seen have short lock up periods (1yr, sub 2yr); for more “liquid venture” I’ve seen more standard 2–3 year lock ups (or longer).

Education Gap

Sophisticated investors acknowledge traditional markets go up, markets go down — it’s been that way for a long time. Crypto, as discussed earlier, is not yet traditional, at least in the eyes of a majority of institutional investors. Rapid volatility, significant declines from the beginning of 2018, discussions of “forks” and other features of this asset class are still very fresh and new to this class of investor; the lack of research up until very recently, weekly and monthly insights and more needed to help educate these LP’s has been poor at best. As a fund manager it’s never a good day to lose LP’s money, but if you do you better not solely rely on your quarterly “newsletter” to let them know that. Herein I also account many managers will lose significant capital allocations and eventually shut down, not purely for a down market and poor performance, rather a combination of poor performance and poor management of expectations and knowledge transfer to LP’s. Those that weather “the winter”, that have smaller AUM, are the ones who will consistently provide high throughput to their LP’s and potential LP’s.

Risk Management + Lock Up + Education Gap = A Mess

Let’s take the notion that some funds out there have been overly aggressive and quite possibly not as well “versed” in standard risk management processes; in a recent study it was seen that a third of crypto investors are between 25 and 34; they were not investors during the dot com bubble nor Bear and Lehman collapsing. Compound that with lock up periods that may be coming up soon plus the overall lack of education and open communication with LP’s you have a recipe for capital being pulled and funds shutting down; potentially hitting that +60% mark discussed above.

Other Issues potentially affecting fund closures

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Asset Duplicity & Concentration Risk

A short story: someone I know at a sizable family office is tasked with their hedge fund portfolio; they had at least 50 LP allocations to some of the top quartile fund managers in the world. What this person is partially tasked with, in addition to fund diligence and allocating, is getting all the holdings (sometimes provided by managers on a monthly basis, sometimes leveraging good old 13F’s) and creating an allocation matrix to see what the total exposure to certain stocks are. Let’s take an example: a darling of the HF industry a few years ago was Equinix (ticker EQIX).

Say for example HF 1 has $100M AUM and 5% of the fund is in EQIX = $5M. In HF 2 they have $250M AUM and 3.5% of the fund is in EQIX = $8.75M. If a significant percentage (+40%) of the 50 total funds in this example all buy EQIX an investor is now looking at substantial concentration risk to a single name instead of what the stated goal of leveraging funds is for many institutional investors, i.e. diversification. Finra does a great job discussing concentration risk here.

Concentration Risk relative to crypto

Yes there are 2100 tokens in market right now but as we all know the majority of liquidity resides in the top 10–50 on CMC. I believe it’s fair to say that a majority of the 500 funds in market right now, hedge fund and liquid VC, all play in this particular sandbox.

You can not expect to raise a fund, charge 3 & 30 (and there’s a lot of those out there) while duplicating everyone else’s strategy. It’s a losing proposition.

As I observed in Feb ’18 a majority of the funds in market (at that point in time and to today) all suffer from duplicity:


Everyone has to start somewhere; those funds who have $5–10M in AUM can outpace those who have been able to raise $100M+ if they can be more contrarian, mindful and deploy risk management techniques to weather storms such as these and be hyper vigilant about educating their LP’s, in good times BUT especially in bad. It’s a lot of work and those that are doing it will be in the 10%.