Fading sweeps of yesterday's high and low
Micro E-mini Nasdaq-100 (MNQ) · 5-minute bars · 2016 to 2026 · ICT and liquidity · A common liquidity-sweep setup
No edge after costs: profit factor 0.84 out of sample.
- Profit factor, out of sample
- 0.84
- Average trade, out of sample
- −0.11R
- Win rate, out of sample
- 31%
- Trades, 10 years
- 602
- Max drawdown
- $16,267
- Pass odds, median plan
- 1.3%
Hypothetical results. These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.
Abstract
We backtested the previous-day high/low sweep fade rules on Micro E-mini Nasdaq-100 (MNQ) 5-minute bars from 2016-01-11 to 2026-10-30: 602 trades, with commission and a tick of slippage on every market and stop fill. In sample (to 2023-08-03) it made −0.06R per trade with a profit factor of 0.92; out of sample (from 2023-08-04) −0.11R per trade and 0.84 over 173 trades. 5 of the 16 parameter settings we tried were profitable out of sample. Sized at $250 of risk a trade, simulated 50K evaluations passed 0% to 3% of the time across 36 tracked plans.
1Hypothesis
When price pokes through yesterday's high or low and closes back inside within three bars, fade the poke, stop beyond its extreme, target twice the risk.
If quick pokes through yesterday's extremes are stop runs that fail, fading the reclaim 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 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:
- Yesterday's high and low are its regular-session (09:30-16:00 ET) extremes. The day must open inside them.
- After a bar trades above yesterday's high, sell the first close back below it if that close comes within reclaim_bars (3) bars, counting the bar that went above. Yesterday's low is the mirror image (buy). Each level gets one try a day, from 09:30 to 12:00 ET.
- Stop: one tick beyond the extreme of the sweep (the highest high since price went above).
- Target: target_r (2) times the risk. Trades risking under 0.05% or over 0.5% of price are skipped.
- Exit: the stop, the target, or flat at 15:55 ET. One trade a day.
- Size: about risk_usd dollars of risk a trade (micro contracts, rounded down, at least 1 and at most max_contracts).
"""Previous-day high and low sweep fade on Micro E-mini Nasdaq-100 (MNQ) 5-minute bars, regular session. Rules: 1. Yesterday's high and low are its regular-session (09:30-16:00 ET) extremes. The day must open inside them. 2. After a bar trades above yesterday's high, sell the first close back below it if that close comes within `reclaim_bars` (3) bars, counting the bar that went above. Yesterday's low is the mirror image (buy). Each level gets one try a day, from 09:30 to 12:00 ET. 3. Stop: one tick beyond the extreme of the sweep (the highest high since price went above). 4. Target: `target_r` (2) times the risk. Trades risking under 0.05% or over 0.5% of price are skipped. 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`)."""import qy class Bot(qy.Strategy): """Fade a failed poke through yesterday's high or low.""" symbol = "MNQ" timeframe = "5m" session = "rth" params = {"reclaim_bars": 3, "target_r": 2.0, "risk_usd": 250, "max_contracts": 50} max_position = 50 entry_window = ("09:35", "12:00") flatten_time = "15:55" overnight = False def setup(self): self.day = None self.h = self.l = None self.yh = self.yl = None def _size(self, risk_points): per_contract = risk_points * self.point_value n = int(self.p.risk_usd // per_contract) if per_contract > 0 else 1 return max(1, min(self.p.max_contracts, n)) def on_bar(self, bar): if bar.date != self.day: if self.h is not None: self.yh, self.yl = self.h, self.l self.day, self.h, self.l = bar.date, bar.high, bar.low self.ok = self.yh is not None and self.yl < bar.open < self.yh self.up = self.dn = None # [bars since the poke, extreme] self.tried_up = self.tried_dn = False else: self.h, self.l = max(self.h, bar.high), min(self.l, bar.low) if not self.ok or self.trades_today >= 1 or not self.position.is_flat or self.orders: return t = bar.dt.hour * 60 + bar.dt.minute + 5 if t >= 720: return tick = self.tick_size if not self.tried_up: if self.up is None and bar.high > self.yh: self.up = [0, bar.high] if self.up is not None: self.up = [self.up[0] + 1, max(self.up[1], bar.high)] if bar.close < self.yh: self.tried_up = True self._fade(-1, bar.close, self.up[1] + tick, self.up[0] - 1) return if self.up[0] >= self.p.reclaim_bars: self.tried_up = True if not self.tried_dn: if self.dn is None and bar.low < self.yl: self.dn = [0, bar.low] if self.dn is not None: self.dn = [self.dn[0] + 1, min(self.dn[1], bar.low)] if bar.close > self.yl: self.tried_dn = True self._fade(1, bar.close, self.dn[1] - tick, self.dn[0] - 1) return if self.dn[0] >= self.p.reclaim_bars: self.tried_dn = True def _fade(self, d, close, stop, bars): risk = abs(close - stop) if not 0.0005 * close <= risk <= 0.005 * close: return f = risk / close * 100 if d > 0: self.buy(self._size(risk), stop_price=stop, target_r=self.p.target_r, tag=f"PDL sweep long | f={f:.4f}") else: self.sell(self._size(risk), stop_price=stop, target_r=self.p.target_r, tag=f"PDH sweep short | f={f:.4f}")4Results
| Statistic | In sample | Out of sample | All |
|---|---|---|---|
| Trades | 429 | 173 | 602 |
| Net P&L | −$5,573 | −$4,229 | −$9,802 |
| Profit factor | 0.92 | 0.84 | 0.90 |
| Average trade | −0.06R | −0.11R | −0.07R |
| 95% interval of the average | −0.19 to 0.08 | −0.32 to 0.09 | −0.19 to 0.04 |
| t-statistic of trade R | −0.82 | −1.10 | −1.28 |
| Win rate | 35% | 31% | 34% |
| Average win / average loss | 1.72 | 1.85 | 1.76 |
| Max drawdown | $10,544 | $6,876 | $16,267 |
| Sharpe ratio (daily, annualized) | −0.60 | −1.29 | −0.78 |
| Longest losing streak | 10 | 11 | 11 |
| Long / short profit factor | 0.98 / 0.88 | 0.83 / 0.84 | 0.94 / 0.87 |
| Average holding time | 34 min | 44 min | 37 min |
| Commission paid | $8,048 | $1,098 | $9,146 |
Drag across the chart to zoom into a period, double-click to reset.
Averages: −0.06R in sample, −0.11R out of sample.
Drag a box to zoom, double-click to reset.
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. 0 were profitable in sample and 5 out of sample.
Bars to reclaim across, target (R) up. Solid outline: the defaults we tested; dashed: the in-sample best.
Hover a cell for both sides of the split.
Bars to reclaim 1.00 to 5.00 across · Target (R) 1.00 to 3.00 in depth · Profit factor, out of sample 0.76 to 1.26 as height and shade. Drag or use the arrow keys to turn it.
Drag to rotate; ctrl or ⌘ and scroll to zoom.
What would change it
Nothing on the grid helps. Its in-sample best, bars to reclaim 2 and target (R) 3, had profit factor 0.97 in sample but 0.94 out of sample, against 0.84 for the defaults.
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.
| Plan | Pass odds, 95% interval | Pass | Fail | Out of time | Median sessions |
|---|---|---|---|---|---|
| FundedNext Futures Flex Challenge 50K | 2.6% | 34% | 63% | 40 | |
| Alpha Futures Standard 50K Evaluation | 1.3% | 15% | 84% | 46 | |
| Alpha Futures Zero 50K Evaluation | 1.3% | 15% | 84% | 46 | |
| Apex Trader Funding 50K EOD Evaluation | 1.3% | 15% | 84% | 46 | |
| Apex Trader Funding 50K Intraday Trailing Drawdown Evaluation | 1.3% | 21% | 78% | 46 | |
| AquaFutures Beginner 50K Evaluation | 1.3% | 5% | 94% | 46 | |
| Bulenox 50K Qualification Account (Legacy, Option 1, trailing drawdown) | 1.3% | 8% | 91% | 46 | |
| Bulenox 50K Qualification Account (Legacy, Option 2, EOD drawdown) | 1.3% | 5% | 94% | 46 | |
| Earn2Trade Gauntlet Mini $50K | 1.3% | 15% | 84% | 46 | |
| Earn2Trade Trader Career Path TCP50 | 1.3% | 15% | 84% | 46 |
7Limitations
- One try per level a day, mornings only.
- One market (MNQ).
- 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 0.84 out of sample. Nothing on the grid helps. Its in-sample best, bars to reclaim 2 and target (R) 3, had profit factor 0.97 in sample but 0.94 out of sample, against 0.84 for the defaults. On this reading of the rules, with these costs, the historical record gives no reason to expect a profit.