Honest risk disclosure
Every published return on this site is real, computed on out-of-sample data. We are also painfully aware of how these strategies can lose money. This page is the part most fund sites omit.
3
High-severity risks
3
Medium-severity risks
1
Operational risks
Helios has produced -10% monthly drawdowns out of sample. US Intraday Alpha has had multi-week sequences where the model is wrong more often than right. These are not edge cases. They are the price of running a real strategy.
If a quoted Sharpe is 1.0 and you size positions accordingly, a -15% to -25% drawdown in a single 6-month window is statistically ordinary. Plan for it.
A strategy designed in a low-vol environment may rip in a high-vol one (and the other way around). Our crypto book worked well during the 2024 bull and would have performed worse through the 2022 regime. We refit monthly to adapt, but adaptation has a delay.
Translation: any month our headline performance can underperform your worst expectations, and the cause is usually genuine market regime change rather than a broken strategy.
We subtract realistic execution costs and funding from our backtests. We still cannot perfectly model slippage on every fill, especially in less-liquid US small-caps. Realised live performance tends to come in 10-20% below comparable backtest figures over long enough horizons. Assume that gap is real.
Perpetual futures strategies operate with leverage. A -20% drawdown at 2× gross becomes a -40% drawdown on your equity, and if you mis-size, more. Liquidation is irreversible. Never deploy more than you can afford to lose entirely.
Exchange failures, freeze events, oracle manipulation, smart contract bugs, regulatory action, and stable-coin de-pegs are all risks in crypto markets. Equivalent risks exist in equity markets (circuit breakers, flash crashes, broker failures). These probabilities are not captured in any backtest we publish.
Our universes are small (14 crypto pairs, ~80 mid-cap US names, ~1,000 large-cap US names). Diversification is bounded. A correlated draw-down across the universe — common in stress regimes — hits every position at once.
Signals can be delayed by exchange latency, API outages, or our own deployment problems. We aim for sub-second turnaround on alerts but cannot guarantee it. If a signal fires while our upstream is degraded, you may not receive it on time.
What losing stretches actually looked like
These are the real underwater curves of each strategy — every point below the line is money the book was down from its prior peak, drawn straight from published NAV. Not a hypothetical.
Helios
US Intraday Alpha
US Liquid Long-Short
The losing trades behind them
The worst realized trades each strategy has actually booked, pulled from the live trade logs. Every strategy takes losses like these — the edge is in the aggregate, not any single position.
Helios
worst realized tradesUS Intraday Alpha
worst realized tradesUS Liquid Long-Short
worst realized tradesWhat we do about it
Monthly refit
Models adapt to regime change
10% per-coin cap
No single position can dominate
≤2× gross leverage
Bounded liquidation risk
Vol-targeting
Position size shrinks in stress
Published drawdowns
Every red NAV cell shown publicly
The honest takeaway: these strategies can and will lose money in any 6-month window. Use them as one allocation in a broader plan, not as a substitute for emergency-fund discipline.
This page is not a comprehensive risk disclosure. See ourTerms & Disclosures for the full legal text. Trading involves substantial risk of loss. Past performance is not indicative of future results.