Understanding crypto fund drawdowns: how bad can it get?
Understanding crypto fund drawdowns: how bad can it get?
Bitcoin has drawn down 70%+ multiple times. Crypto hedge funds are supposed to do better. Some do. Some do not. Here’s what 303 fund drawdown histories actually show, and what they mean for allocators sizing their exposure.
(all funds, SI)
(quant funds, SI)
(long-only funds, SI)
max drawdown (SI)
- ✓Maximum drawdown measures the largest peak-to-trough decline a fund has experienced. It answers the question: “What is the most I could have lost?”
- ✓The median since-inception max drawdown across 303 funds in our database is -35.4%. That means the typical crypto fund has, at some point in its life, lost more than a third of its peak value.
- ✓Strategy matters enormously. The median quant fund drawdown is -20.7%. The median long-only drawdown is -71.5%. Fund of funds have the shallowest median drawdown at -18.1%.
- ✓The worst fund in the database lost 96.4% of its peak value. 409 “dead” funds are tracked separately, many of which went to zero.
- ✓A 50% drawdown requires a 100% gain to recover. A 75% drawdown requires a 300% gain. This asymmetry is why drawdown management is more important than return generation for long-term compounding.
- ✓The 2022 bear market and the 2025 Q4 selloff both confirmed that drawdown profiles are predictive: funds with historically low drawdowns tended to protect capital, while those with high historical drawdowns experienced them again.
What max drawdown measures
Maximum drawdown (MDD) is the largest peak-to-trough decline in a fund’s NAV over a given period. It tells you the worst-case experience an investor could have had if they invested at the peak and held through the trough. It is the single most important backward-looking risk metric for allocators.
Why does MDD matter more than volatility? Because volatility is symmetric: it counts upside moves the same as downside moves. Drawdown is purely about loss. Nobody loses sleep over upside volatility. They lose sleep over how much of their capital disappeared during the worst stretch.
There is also a behavioral component. Investors who experience a 50% drawdown often redeem before the recovery. They lock in the loss. So the max drawdown is not just a risk measure. It is a measure of the maximum amount of pain an investor might actually experience, because many investors will exit at the bottom.
Drawdowns by strategy
The gap between strategies on drawdown data is the widest of any risk metric. It’s even wider than the gap on Sharpe ratios. This chart tells you more about what each strategy actually is than any marketing deck.
The difference between the top and bottom of this chart is stark. The median fund of funds has lost 18.1% at worst. The median index/tracker has lost 78.7%. That is a 4x difference in worst-case experience, driven entirely by strategy design.
Fund of funds (-18.1% median MDD). The shallowest drawdowns of any category, which may surprise people given that FoFs were the worst-performing category on 2025 returns (-13.0%). The diversification across multiple managers genuinely dampens peak-to-trough declines, even though it does not prevent losses. The tradeoff: smoother but lower net returns due to the double fee layer.
Quant funds (-20.7% median MDD). Nearly as shallow as FoFs but with much better return profiles (median Sharpe of 1.53 vs 1.37 for FoFs). Quant strategies protect capital through dynamic hedging, short positions, and algorithmic risk management. The ability to go flat or net short during a drawdown is the key differentiator. The worst quant fund in the database had a -95.8% SI drawdown, proving that quant is not risk-free, but the median tells you the typical experience is a manageable 21% peak-to-trough decline.
Multi-strategy (-29.2% median MDD). Middle of the pack. A 29% drawdown is painful but recoverable. The wide range within multi-strategy (worst was -90.9%, best was effectively flat) reflects the diversity of approaches. A multi-strat that is mostly market-neutral will have a drawdown profile closer to quant. One that is mostly directional will look more like long-only.
Long-only (-71.5% median MDD). The median long-only fund has lost nearly three-quarters of its peak value at some point. This is not an anomaly or a tail risk. It is the typical experience. If you invest in a long-only crypto fund and hold through a full market cycle, you should expect a 70%+ drawdown. The only question is when. If your board cannot stomach that kind of decline, long-only is not the right strategy. Period.
Index/tracker (-78.7% median MDD). The deepest drawdowns, for the same structural reasons they have the worst returns: futures-based products amplify losses, and these products provide zero downside protection by design. The worst index product in our database drew down 93.9%.
The asymmetry problem
The math of drawdowns is cruel and nonlinear. The deeper the drawdown, the harder it is to recover.
| Drawdown | Gain needed to recover | How long (typical crypto) | Investor experience |
|---|---|---|---|
| -10% | +11% | 1-3 months | Minor. Most investors stay. |
| -25% | +33% | 3-9 months | Uncomfortable. Some questions from LPs. |
| -50% | +100% | 12-24 months | Painful. Fund may gate withdrawals. New fundraising is very difficult. |
| -75% | +300% | 24-36+ months | Existential. Many investors redeem. Fund may close. |
| -90% | +900% | May never recover | Catastrophic. Fund almost certainly closes. Investors lock in losses. |
Look at the middle row. A 50% drawdown needs a 100% gain to break even. In crypto, a 100% gain is not impossible, but it typically requires a full market cycle. That means an investor who entered at the peak might wait 2+ years just to get back to breakeven, while paying management fees the entire time.
Now look at the -75% row. A 300% gain is needed. That is an extraordinary return that most fund managers will never achieve. The median long-only fund in our database has drawn down 71.5%. Many of those funds are still underwater from their peak NAV. The recovery math tells you why 409 funds in our database are classified as “dead.”
A quant fund that goes +10%, -5%, +12%, -3% over four years compounds to +14.4%. A long-only fund that goes +80%, -60%, +40%, -15% compounds to -18.9%. The long-only fund had higher absolute returns in the up years. But the deep drawdowns destroyed the compounding. This is why Sharpe ratios matter more than raw returns for long-term wealth creation, and why drawdown management is not just risk management. It is return management.
Case study: the 2022 bear market
The 2022 bear market was the most comprehensive stress test the crypto fund industry has ever faced. Bitcoin fell from its November 2021 peak of roughly $69,000 to under $16,000 by November 2022, a drawdown of approximately 76%. The CFR Index fell 40.6% for the full year.
But 2022 was not just a market drawdown. It was a cascade of three distinct crises that compounded each other.
Phase 1: Luna/UST collapse (May 2022)
The algorithmic stablecoin UST lost its peg, wiping out roughly $60 billion in market value. Funds with direct Luna or UST exposure were hit immediately. Three Arrows Capital, which managed an estimated $10-15 billion at its peak, had $200-560 million in Luna exposure. The collapse triggered the firm’s insolvency, which in turn created a contagion cascade across the industry.
Not every fund handled Luna the same way. Pantera Capital had a significant Luna position but sold approximately 80% of it before the collapse, reportedly booking roughly 10x returns on that exit. That kind of risk management discipline, the willingness to take profits and reduce concentrated positions, is the difference between surviving and not.
Phase 2: Three Arrows/Genesis/Celsius contagion (June-August 2022)
Three Arrows Capital’s insolvency created a wave of counterparty risk. Lenders who had extended credit to 3AC (including Genesis, Voyager, Celsius, and BlockFi) faced massive losses. Funds with lending exposure, collateral stuck at bankrupt intermediaries, or positions that required liquidity from counterparties that no longer had it were all affected.
Phase 3: FTX collapse (November 2022)
The collapse of FTX added a third wave of drawdowns. Funds with assets on FTX experienced immediate, total losses on those positions. Multicoin Capital, one of the most prominent crypto funds, disclosed that approximately 10% of its hedge fund assets were on FTX. The fund reportedly drew down 91.4% from its peak, though it has since recovered significantly.
The 2022 bear market taught the industry that the biggest drawdowns are not caused by market risk alone. They are caused by counterparty risk, contagion risk, and concentration risk. These are operational risks that no Sharpe ratio or beta number can capture. They require operational due diligence: understanding who your fund’s counterparties are, where their assets are custodied, and how concentrated their positions are.
What 2025 revealed about drawdown risk
2025 was a milder stress test than 2022, but it was still informative. Bitcoin fell 6.3% for the year, with a particularly sharp Q4 selloff (BTC -23.3%, including November’s -17.5% decline).
The trailing 12-month max drawdown data from our database confirms that the strategy hierarchy held up exactly as the since-inception data would predict.
| Strategy | Median 12M MDD | Avg 12M MDD | Worst 12M MDD |
|---|---|---|---|
| Fund of Funds | -6.7% | -18.3% | -77.5% |
| Algorithmic/Quant | -8.9% | -20.2% | -93.9% |
| Multi-Strategy | -11.1% | -20.5% | -89.5% |
| Long Only | -39.4% | -39.3% | -96.4% |
| Index/Tracker | -41.2% | -44.8% | -87.0% |
The median quant fund’s 12-month max drawdown was just -8.9%. The median long-only fund’s was -39.4%. In a year when Bitcoin itself dropped 6.3%, the typical long-only fund experienced a 39% peak-to-trough decline. That tells you everything about the strategy’s risk management (or lack thereof).
For the full analysis of 2025 performance, see our annual performance review.
See drawdown data for every fund
The Performance Database includes SI, 24-month, and 12-month max drawdowns plus 60+ risk metrics for hundreds of crypto funds. Filter by strategy and sort by drawdown to find the lowest-risk managers.
Explore the Performance Database → Free sampleFour types of drawdown risk
Not all drawdowns are the same. Understanding why a fund drew down is as important as understanding how much it drew down.
Market risk. The simplest form: the market goes down, and the fund goes down with it. This is proportional to the fund’s beta. A fund with 0.84 beta to Bitcoin will lose roughly 84% of what Bitcoin loses. Market risk is unavoidable for directional strategies and manageable for hedged ones.
Counterparty risk. The fund has assets with a counterparty that fails. FTX is the defining example: funds with assets on FTX lost those assets entirely, regardless of their trading strategy. Counterparty risk is an operational risk that can hit any strategy. The fix is qualified custody and counterparty diversification.
Leverage risk. The fund uses borrowed capital to amplify returns. When the market moves against a leveraged position, losses are amplified proportionally. Three Arrows Capital used significant leverage, which turned a manageable market loss into an insolvency. Leverage risk is controllable but requires strict position limits and margin management.
Concentration risk. The fund has too much of its portfolio in a single position or correlated positions. Luna exposure is the canonical example: funds with 20-30% of their portfolio in a single asset that went to zero experienced catastrophic drawdowns. Diversification limits reduce concentration risk, but many crypto funds deliberately concentrate because they believe concentration is the source of alpha.
When evaluating a fund’s drawdown history, ask: what caused the drawdown? If it was market risk and the drawdown was proportional to the fund’s beta, that is expected behavior. If it was counterparty or concentration risk, the fund’s operational controls may be inadequate. See our due diligence checklist for the operational questions to ask.
What allocators should do with this data
Set a drawdown budget before you invest. Decide in advance: what is the maximum drawdown your portfolio can tolerate from the crypto allocation? If the answer is 25%, you should not be in long-only or index products (median MDD of 71.5% and 78.7%). You should be in quant (20.7%) or fund of funds (18.1%), or blending quant with spot BTC in a ratio that keeps the overall drawdown within budget.
Use historical drawdown data as a minimum, not a maximum. A fund that has drawn down 30% in its history can draw down more than 30% in the future. The past drawdown tells you the risk it has experienced, not the risk it could experience. For crypto, where black swan events (Luna, FTX) occur more frequently than in traditional markets, assume the worst is ahead, not behind.
Look at 12-month drawdowns in addition to since-inception. SI drawdowns capture the lifetime worst case, which may include a period (2018, 2022) that is not representative of the current portfolio. Trailing 12-month drawdowns show you the recent risk profile, which may be more relevant for current allocation decisions.
Dead funds matter. Our database tracks 409 funds that have closed. Many of them experienced drawdowns severe enough to trigger closure. The drawdown statistics for surviving funds are biased upward because the worst performers dropped out of the dataset. Keep that survivorship bias in mind when interpreting the numbers.
During severe drawdowns, many funds gate withdrawals or extend redemption notice periods. This means an investor who wants to exit during a drawdown may not be able to. The investor’s actual experience can be worse than the NAV drawdown suggests, because they are locked in while the NAV continues to decline. When evaluating a fund, check the redemption terms (notice period, gate provisions, lock-up) alongside the drawdown data. A fund with a 30% max drawdown and a 90-day gate is a different experience from one with the same drawdown but daily liquidity.
FAQ
What is the average max drawdown for crypto funds?
The median since-inception max drawdown across 303 funds in our database is -35.4%. The average is -39.2%. By strategy: fund of funds -18.1% median, quant -20.7%, multi-strategy -29.2%, long-only -71.5%, index/tracker -78.7%. The worst single fund in the database experienced a -96.4% drawdown.
Which strategy has the smallest drawdowns?
Fund of funds have the shallowest median max drawdown at -18.1%, followed closely by quant/algorithmic at -20.7%. However, quant funds deliver better risk-adjusted returns (higher Sharpe ratios) for similar drawdown profiles. If your goal is minimizing drawdowns while maintaining decent returns, quant strategies are the strongest category in our data. See the strategy comparison for the full picture.
How long does it take to recover from a crypto fund drawdown?
It depends on the depth. A 25% drawdown typically recovers in 3-9 months in crypto. A 50% drawdown may take 12-24 months. A 75% drawdown requires a 300% gain and may take 2-3 years or never recover at all. The 2022 bear market drawdowns took most funds 18-24 months to recover, with some still underwater. Recovery times are influenced by market conditions, strategy (hedged strategies recover faster), and whether the drawdown was caused by market risk or operational failure.
How many crypto funds have closed due to drawdowns?
We track 409 “dead” funds in our database that have closed. While not all closures are directly caused by drawdowns (some are strategic wind-downs, team departures, or regulatory exits), severe drawdowns are the leading cause of fund closure. The 2018 bear market and the 2022 triple crisis (Luna, 3AC, FTX) each triggered significant waves of fund closures.
Where can I see drawdown data for individual funds?
The CFR Performance Database includes since-inception, 24-month, and 12-month max drawdowns for hundreds of funds, along with 60+ other risk metrics. You can sort by drawdown to identify the lowest-risk managers in any strategy category. A free sample is available.