Gap and go on the Nasdaq-100

Abstract

We backtested the gap and go rules on Micro E-mini Nasdaq-100 (MNQ) 5-minute bars from 2016-01-11 to 2026-10-30: 741 trades, with commission and a tick of slippage on every market and stop fill. In sample (to 2023-08-03) it made +0.01R per trade with a profit factor of 1.00; out of sample (from 2023-08-04) +0.08R per trade and 1.12 over 226 trades. 10 of the 16 parameter settings we tried were profitable out of sample. Sized at $250 of risk a trade, simulated 50K evaluations passed 1% to 5% of the time across 36 tracked plans.

1Hypothesis

After a gap of at least 0.3% that the first 5-minute bar confirms, trade with the gap, stop beyond the first bar, target twice the risk.

If a large gap that holds its first bar reflects real news, it should keep moving in its direction for the rest of the day.

2Data

Instrument

Micro E-mini Nasdaq-100 (MNQ), traded on the NQ price series (NQ.c.0: front month, rolled on the calendar). CME Globex via Databento.

Period

2016-01-11 to 2026-10-30: 2,745 sessions, 1,056,797 one-minute bars, built into 210,814 5-minute bars of the regular session (09:30 to 16:00 ET).

Costs

$0.75 commission a contract each way and 1 tick ($0.50) of slippage on every market and stop fill. Limit orders fill when price touches them; market orders fill at the next bar's open and stops at their price, each with one tick of slippage; when a bar touches both the stop and the target, the stop counts.

Position size

About $250 of risk a trade: micro contracts, rounded down, at least one. R is a trade's net P&L divided by its risk at entry.

Out of sample

The last 30% of weekdays: 2023-08-04 on (846 days), after 1,974 in-sample days. The rules were fixed before either side was run.

3Method

Our reading of the publicly described rules; the creator may trade it differently. The rules, exactly as the code runs them:

1. The gap is the 09:30 ET open against the previous session's 16:00 close, in percent.
2. Entry: if the gap is at least min_gap_pct (0.3%) and the first 5-minute bar closes in the gap's direction (up after a gap up, down after a gap down), trade with the gap at 09:35 ET.
3. Stop: one tick beyond the first bar's other extreme (its low for a long).
4. Target: target_r (2) times the risk.
5. Exit: the stop, the target, or flat at 15:55 ET. One trade a day.
6. Size: about risk_usd dollars of risk a trade (micro contracts, rounded down, at least 1 and at most max_contracts).

1"""Gap and go on Micro E-mini Nasdaq-100 (MNQ) 5-minute bars, regular session, New York time.2 3Rules:4  1. The gap is the 09:30 ET open against the previous session's 16:00 close, in percent.5  2. Entry: if the gap is at least `min_gap_pct` (0.3%) and the first 5-minute bar closes in the gap's6     direction (up after a gap up, down after a gap down), trade with the gap at 09:35 ET.7  3. Stop: one tick beyond the first bar's other extreme (its low for a long).8  4. Target: `target_r` (2) times the risk.9  5. Exit: the stop, the target, or flat at 15:55 ET. One trade a day.10  6. Size: about `risk_usd` dollars of risk a trade (micro contracts, rounded down, at least 1 and at11     most `max_contracts`).12"""13import qy14 15 16class Bot(qy.Strategy):17    """Trade with a large opening gap when the first bar confirms it."""18 19    symbol = "MNQ"20    timeframe = "5m"21    session = "rth"22    params = {"min_gap_pct": 0.3, "target_r": 2.0, "risk_usd": 250, "max_contracts": 50}23    max_position = 5024    entry_window = ("09:35", "09:40")25    flatten_time = "15:55"26    overnight = False27 28    def setup(self):29        self.day = None30        self.prev_close = None31        self.last_close = None32 33    def _size(self, risk_points):34        per_contract = risk_points * self.point_value35        n = int(self.p.risk_usd // per_contract) if per_contract > 0 else 136        return max(1, min(self.p.max_contracts, n))37 38    def on_bar(self, bar):39        first = bar.date != self.day40        if first:41            self.day = bar.date42            self.prev_close = self.last_close43        self.last_close = bar.close44        if not first or self.prev_close is None:45            return46        gap = (bar.open - self.prev_close) / self.prev_close * 10047        if abs(gap) < self.p.min_gap_pct:48            return49        tick = self.tick_size50        if gap > 0 and bar.close > bar.open:51            stop = bar.low - tick52            self.buy(self._size(bar.close - stop), stop_price=stop, target_r=self.p.target_r, tag=f"Gap and go long | f={abs(gap):.4f}")53        elif gap < 0 and bar.close < bar.open:54            stop = bar.high + tick55            self.sell(self._size(stop - bar.close), stop_price=stop, target_r=self.p.target_r, tag=f"Gap and go short | f={abs(gap):.4f}")

4Results

5Robustness

We reran the strategy on a grid of 16 settings of its two main parameters, each on the full history with the same split. 8 were profitable in sample and 10 out of sample.

6Prop-firm implications

The backtest's sessions run through the rules of 36 tracked 50K evaluations: 2,000 runs of up to 60 sessions each, with the drawdown and daily limits checked against each trade's intraday low. Intervals are Wilson 95% intervals of the simulation. A simulation of the past, not the chance that anyone passes.

7Limitations

• The stop sits at the first bar's extreme, which can be wide on news days.
• One market (MNQ).
• A backtest on the past, with fills simulated from one-minute bars; live fills, queues and outages differ.

8Conclusion

Marginal: profit factor 1.12 out of sample, not clearly above break-even, t = 0.8. Nothing on the grid clearly helps. Its in-sample best, smallest gap (%) 0.5 and target (R) 3, did better out of sample, profit factor 1.28 against 1.12 for the defaults, but over only 153 trades, t = 1.5: too few, or too noisy, to call it a fix. The result is too close to break-even to tell apart from noise after costs.