Systematic Futures Strategy

Trade the
Nasdaq 100
without discretion.

NQ Alpha Engine is a fully automated, model-driven strategy trading Micro E-mini Nasdaq 100 futures. No human override. No emotional interference. Rules execute every time.

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Return +104.7%
Win Rate 62.4%
Trades 197
Max DD 10.2%
Sharpe 4.66
Profit Factor 2.2:1
Live AUM $1.30M
Since Mar 2026
Track Record

Performance

Cumulative Return
+104.7%
Since March 2026
Win Rate
62.4%
123 wins / 74 losses
Max Drawdown
10.2%
Mar 30 – Apr 3, 2026
Sharpe Ratio
4.66
Sortino: 14.83
Profit Factor
2.2x
Avg win $164 / loss $126
Win Months
100%
4 of 4 months profitable
Monthly Returns
Year Mar Apr May Jun YTD
2026 — — +36.6% +25.6% +1.0% +18.1% — — — — — — +81.3%

Includes estimated broker commissions and strategy subscription fees.

✓
Trades-Own-Strategy Certified
The strategy manager trades this system in a real, funded brokerage account at AMP Clearing (CQG) with 100% scaling. Since certification on March 10, 2026, 99.3% of signals have been executed live. TOS certification is independently verified by Collective2.
Methodology

The Framework

NQ Alpha Engine is built on a proprietary quantitative framework that treats Nasdaq 100 futures price dynamics as a stochastic process governed by separable drift and diffusion components. Drawing on Itô calculus, the system models the conditional mean-reversion tendencies of price at structural support zones — identifying regions where the drift component demonstrably dominates the noise term and bounce probability is statistically elevated. Candidate levels are scored by an XGBoost ensemble model trained on thousands of historical market structures, evaluating 37 engineered features spanning volatility regime, higher-timeframe confluence, session context, and momentum state.

Signal generation is governed by a multi-layered filtering architecture. The instantaneous diffusion coefficient — estimated in real time through adaptive volatility measurement — determines whether the current regime supports mean-reversion entries. Independent statistical gates suppress activity during trend-day environments where the noise term overwhelms any structural edge. A dynamic scoring threshold calibrates automatically to the prevailing regime, ensuring the system only commits capital when the probabilistic conditions are aligned.

Risk is treated as a first-class constraint, not an afterthought. The system enforces hard exposure limits on every trade, a one-loss-per-day rule, and a cooldown mechanism that prevents re-entry into levels already traded. No position is ever averaged down. No human discretion enters the execution loop. Every decision — from stochastic regime classification to signal scoring to order placement — is made by the model, every time.

Common Questions

FAQ

NQ Alpha Engine trades the Micro E-mini Nasdaq 100 futures contract (MNQ) on CME. Each MNQ contract controls $2 per index point. At current NQ levels (~29,000), one contract represents approximately $58,000 in notional value. The strategy trades one contract at a time.
Signals are generated by a machine learning model (XGBoost ensemble) that scores historical support levels on the MNQ H1 chart. The model evaluates 37 features including price structure, volatility regime, higher-timeframe confluence, RSI context, and session dynamics. Only levels scoring above a dynamic threshold trigger an order. No human makes any trade decisions.
Every trade carries a fixed 200-point stop loss, equal to $400 per MNQ contract. This is non-negotiable — the system places a hard stop on every order and it is never moved or overridden. There is no fixed take profit target. Exit timing is determined entirely by the model based on real-time market conditions — the system closes the position when its internal criteria are met. This means winning trades vary in size rather than being capped at a fixed R multiple, allowing the strategy to capture more on strong moves and exit efficiently when momentum fades.
Collective2 suggests a minimum of $25,000, and that is a reasonable target for comfortable operation. Realistically, $10,000 is workable — it covers margin requirements with buffer for normal drawdowns. Going below $5,000 becomes problematic: most brokers require higher overnight margin to hold MNQ positions through the close, and a thin account can get flagged or force-closed before the trade has time to work. Starting with less also amplifies psychological pressure during losing streaks, which is the most common reason traders abandon a system prematurely. The strategy is designed to be followed systematically — give it enough capital that a normal drawdown doesn't feel like a crisis.
Subscribe on Collective2, then connect your broker account via AutoTrade. Supported brokers include AMP Clearing (CQG), Interactive Brokers, Tradovate, Tradier, and others. Once connected, trades execute automatically in your account whenever the strategy places a signal — no action required from you. Full setup instructions are available at collective2.com/lets-get-started.
Losing streaks are a mathematical certainty in any probabilistic trading system with a 62% win rate — they are not a signal that the strategy is broken. The edge emerges over a large sample of trades, not individual outcomes. Stopping during a drawdown and restarting after a winning period is the most reliable way to underperform the strategy's published results. The correct response to a drawdown is to do nothing and let the system continue executing.
Yes. The strategy holds Trades-Own-Strategy (TOS) certification from Collective2, which independently verifies that the manager is trading this exact system in a real funded brokerage account at AMP Clearing (CQG). Since certification began on March 10, 2026, 99.3% of signals have been executed live. The manager's account runs at 100% scaling — identical to what subscribers receive.
MNQ futures are highly liquid, but large subscriber counts can create meaningful market impact at the specific price levels the strategy targets. Keeping subscriber count limited protects execution quality for existing subscribers. A strategy that degrades its own edge through overcrowding is not in anyone's interest.
The results are real. The strategy manager holds Trades-Own-Strategy (TOS) certification from Collective2, which independently verifies that real capital is being risked in a live funded brokerage account at AMP Clearing (CQG) — not a paper account, not a simulation. The manager trades this system at 100% scaling, meaning every signal that goes to subscribers is also executed with his own money on the line. The Collective2 track record reflects those live signals precisely. There may be minor fill differences between the published record and individual subscriber accounts due to broker and timing variation, but the signal record itself is a near-exact mirror of real trading. Since TOS certification on March 10, 2026, 99.3% of signals have been executed live.

This is a fair question, and the honest answer is: backtest data would tell you less than you think, and the live record tells you more.

Nasdaq 100 is highly regime-dependent. The structural dynamics of a trending bull market, a volatility spike, or a macro-driven selloff are fundamentally different — and a model optimized on one regime can look extraordinary in backtesting while failing in the next. Any backtest numbers I could share would be subject to overfitting, look-ahead bias, and the basic problem that the historical market conditions that generated them no longer exist in the same form.

This is precisely why the XGBoost model is retrained on a rolling basis — it is designed to adapt to current regime conditions rather than lock in on a static historical fit. A strategy that retrains regularly cannot produce a meaningful multi-year backtest anyway, because the model itself changes over time.

What you actually want to know is: what can I expect in terms of returns, drawdowns, and volatility as a subscriber? Here is what the live data shows:

  • Average win: $164  |  Average loss: $126
  • Win rate: 62.4% across 197 live trades
  • Max drawdown to date: 10.2% (Mar 30 – Apr 3, 2026)
  • Worst month: +1.0% (March 2026, partial month)
  • Typical trade frequency: 2–3 trades per day
  • Hard stop per trade: $400 — worst realistic losing week (5 losses): ~$2,000

This is real forward-tested performance with real fills, not a curve-fitted simulation. It is the most credible picture of what to expect as a subscriber.