The ICT Silver Bullet: fair value gaps in the 10 o'clock hour

Abstract

We backtested the ICT Silver Bullet rules on Micro E-mini Nasdaq-100 (MNQ) 1-minute bars from 2016-01-11 to 2026-10-30: 2,141 trades, with commission and a tick of slippage on every market and stop fill. In sample (to 2023-08-03) it made −0.13R per trade with a profit factor of 0.83; out of sample (from 2023-08-04) −0.03R per trade and 0.95 over 643 trades. 2 of the 25 parameter settings we tried were profitable out of sample. Sized at $250 of risk a trade, simulated 50K evaluations passed 3% to 11% of the time across 36 tracked plans.

1Hypothesis

Between 10:00 and 11:00 ET, take the first fair value gap: three one-minute candles where the middle one moved so fast it left a gap. Enter when price comes back to the gap, stop beyond the pattern, target twice the risk.

If price tends to return to a fair value gap and then continue in the gap's direction, a limit entry at the gap's edge in the 10 o'clock hour should reach 2R often enough to pay for costs.

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 1,054,003 1-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. A bullish fair value gap (FVG) is three 1-minute candles where the third candle's low is above the first candle's high: the middle candle left a gap. A bearish FVG is the mirror image (the third candle's high below the first candle's low).
2. Only gaps whose three candles all fall between 10:00 and 10:59 ET count, and only gaps of at least min_gap_ticks (4 ticks, one point), so a one-tick gap is not a setup.
3. The first qualifying gap of the hour sets the day's trade, in its direction.
4. Entry: a limit order at the gap's near edge (for a bullish gap, its top: the third candle's low), working until 11:00 ET. It is cancelled if price reaches the target first.
5. Stop: one tick beyond the three candles' extreme (for a bullish gap, below their lowest low).
6. Target: target_r (2) times the risk.
7. Exit: the stop, the target, or flat at 15:55 ET. One trade a day.
8. Size: about risk_usd dollars of risk a trade (micro contracts, rounded down, at least 1 and at most max_contracts).

Not modelled: the draw on liquidity, which the creator uses to pick the direction; this version

takes the first gap either way.

1"""ICT Silver Bullet: the first fair value gap of the 10:00-11:00 ET hour, on MNQ 1-minute bars.2 3Our reading of the publicly described rules; the creator may trade it differently.4 5Rules:6  1. A bullish fair value gap (FVG) is three 1-minute candles where the third candle's low is above7     the first candle's high: the middle candle left a gap. A bearish FVG is the mirror image (the8     third candle's high below the first candle's low).9  2. Only gaps whose three candles all fall between 10:00 and 10:59 ET count, and only gaps of at10     least `min_gap_ticks` (4 ticks, one point), so a one-tick gap is not a setup.11  3. The first qualifying gap of the hour sets the day's trade, in its direction.12  4. Entry: a limit order at the gap's near edge (for a bullish gap, its top: the third candle's13     low), working until 11:00 ET. It is cancelled if price reaches the target first.14  5. Stop: one tick beyond the three candles' extreme (for a bullish gap, below their lowest low).15  6. Target: `target_r` (2) times the risk.16  7. Exit: the stop, the target, or flat at 15:55 ET. One trade a day.17  8. Size: about `risk_usd` dollars of risk a trade (micro contracts, rounded down, at least 1 and at18     most `max_contracts`).19  Not modelled: the draw on liquidity, which the creator uses to pick the direction; this version20  takes the first gap either way.21"""22import qy23 24 25def _hm(dt):26    return dt.hour * 60 + dt.minute27 28 29class Bot(qy.Strategy):30    """The first fair value gap between 10:00 and 11:00 ET, entered on the retrace into it."""31 32    symbol = "MNQ"33    timeframe = "1m"34    session = "rth"35    params = {"min_gap_ticks": 4, "target_r": 2.0, "risk_usd": 250, "max_contracts": 50}36    max_position = 5037    entry_window = ("10:00", "11:00")38    flatten_time = "15:55"39    overnight = False40 41    def setup(self):42        self.done_day = None43        self.pending = None44 45    def _size(self, risk_points):46        per_contract = risk_points * self.point_value47        n = int(self.p.risk_usd // per_contract) if per_contract > 0 else 148        return max(1, min(self.p.max_contracts, n))49 50    def _tick(self, x):51        return round(x / self.tick_size) * self.tick_size52 53    def on_fill(self, fill):54        self.pending = None55 56    def on_bar(self, bar):57        h, l = bar.high, bar.low58        # A working entry: cancel it once price has reached the target without filling it.59        if self.pending is not None and self.position.is_flat:60            side, target = self.pending61            if (side > 0 and h >= target) or (side < 0 and l <= target):62                self.cancel_all()63                self.pending = None64        t = _hm(bar.dt)  # start of the third candle65        if self.done_day == bar.date or not (602 <= t <= 658) or len(self.high) < 3:66            return67        tick = self.tick_size68        h1, l1 = self.high[2], self.low[2]      # first candle69        lo3 = min(self.low[0], self.low[1], l1)70        hi3 = max(self.high[0], self.high[1], h1)71        gap_up = (l - h1) / tick                 # bullish gap: third low above first high72        gap_dn = (l1 - h) / tick                 # bearish gap: third high below first low73        if gap_up >= self.p.min_gap_ticks:74            entry = self._tick(l)75            stop = self._tick(lo3 - tick)76            risk = entry - stop77            target = entry + self.p.target_r * risk78            self.done_day = bar.date79            self.buy(self._size(risk), limit=entry, stop_price=stop, target_r=self.p.target_r,80                     tag=f"FVG long | f={gap_up:.0f}")81            self.pending = (1, target)82        elif gap_dn >= self.p.min_gap_ticks:83            entry = self._tick(h)84            stop = self._tick(hi3 + tick)85            risk = stop - entry86            target = entry - self.p.target_r * risk87            self.done_day = bar.date88            self.sell(self._size(risk), limit=entry, stop_price=stop, target_r=self.p.target_r,89                      tag=f"FVG short | f={gap_dn:.0f}")90            self.pending = (-1, target)

4Results

5Robustness

We reran the strategy on a grid of 25 settings of its two main parameters, each on the full history with the same split. 1 were profitable in sample and 2 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 draw on liquidity, which the creator uses to choose the direction, is not modelled: we take the first gap either way.
• Limit orders fill on a touch, which flatters entries a little; a real queue may not fill at the price.
• One market (MNQ) and a fixed 2R target; the creator targets liquidity pools.
• A backtest on the past, with fills simulated from one-minute bars; live fills, queues and outages differ.

8Conclusion

No edge after costs: profit factor 0.95 out of sample. Nothing on the grid helps. Its in-sample best, smallest gap (ticks) 16 and target (R) 4, had profit factor 1.02 in sample but 0.96 out of sample, against 0.95 for the defaults. On this reading of the rules, with these costs, the historical record gives no reason to expect a profit.