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Following the opening drive on the Russell 2000

Micro E-mini Russell 2000 (M2K) · 5-minute bars · 2017 to 2026 · Momentum

No edge after costs: profit factor 0.82 out of sample.

Profit factor, out of sample
0.82
Average trade, out of sample
−0.13R
Win rate, out of sample
27%
Trades, 10 years
1,634
Max drawdown
$28,676
Pass odds, median plan
12.1%

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.

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Abstract

We backtested the opening drive rules on Micro E-mini Russell 2000 (M2K) 5-minute bars from 2017-07-17 to 2026-10-30: 1,634 trades, with commission and a tick of slippage on every market and stop fill. In sample (to 2024-01-17) it made −0.02R per trade with a profit factor of 0.98; out of sample (from 2024-01-18) −0.13R per trade and 0.82 over 509 trades. 0 of the 16 parameter settings we tried were profitable out of sample. Sized at $250 of risk a trade, simulated 50K evaluations passed 3% to 21% of the time across 36 tracked plans.

1Hypothesis

If the first 5-minute bar moves at least 0.1%, ride it until the close, with the stop beyond that bar.

If a strong first bar shows the day's initiative, holding with it until the close should earn more than the first bar's range risks.

2Data

Instrument
Micro E-mini Russell 2000 (M2K), traded on the RTY price series (RTY.v.0: the most traded contract, rolled on volume). CME Globex via Databento.
Period
2017-07-17 to 2026-10-30: 2,396 sessions, 922,339 one-minute bars, built into 184,092 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: 2024-01-18 on (727 days), after 1,698 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 first 5-minute bar of the regular session (09:30 to 09:35 ET) has a body of (close - open) / open, in percent.
  2. Entry: if the body is at least min_body_pct (0.1%) up, buy at 09:35 ET; if at least 0.1% down, sell.
  3. Stop: one tick beyond the first bar's other extreme (its low for a long).
  4. Exit: the stop, or at exit_min (15:55 ET, as minutes after midnight: 955). No target.
  5. Size: about risk_usd dollars of risk a trade (micro contracts, rounded down, at least 1 and at most max_contracts).
bot.py, the file the engine ran
"""Opening drive: follow a strong first 5-minute bar, on Micro E-mini Russell 2000 (M2K). Rules:  1. The first 5-minute bar of the regular session (09:30 to 09:35 ET) has a body of (close - open) /     open, in percent.  2. Entry: if the body is at least `min_body_pct` (0.1%) up, buy at 09:35 ET; if at least 0.1% down,     sell.  3. Stop: one tick beyond the first bar's other extreme (its low for a long).  4. Exit: the stop, or at `exit_min` (15:55 ET, as minutes after midnight: 955). No target.  5. 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):    """Ride a strong first bar for the rest of the day."""     symbol = "M2K"    timeframe = "5m"    session = "rth"    params = {"min_body_pct": 0.1, "exit_min": 955, "risk_usd": 250, "max_contracts": 50}    max_position = 50    entry_window = ("09:35", "09:40")    flatten_time = "15:55"    overnight = False     def setup(self):        self.day = 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):        t = bar.dt.hour * 60 + bar.dt.minute + 5        if self.position and t >= self.p.exit_min:            self.close_position("exit time")            return        if bar.date == self.day:            return        self.day = bar.date        body = (bar.close - bar.open) / bar.open * 100        tick = self.tick_size        if body >= self.p.min_body_pct:            stop = bar.low - tick            self.buy(self._size(bar.close - stop), stop_price=stop, tag=f"Drive long | f={abs(body):.4f}")        elif body <= -self.p.min_body_pct:            stop = bar.high + tick            self.sell(self._size(stop - bar.close), stop_price=stop, tag=f"Drive short | f={abs(body):.4f}")

4Results

Table 1. In sample (2017-07-17 to 2024-01-17) against out of sample (2024-01-18 to 2026-10-30), after costs.
StatisticIn sampleOut of sampleAll
Trades1,1255091,634
Net P&L−$4,777−$15,981−$20,759
Profit factor0.980.820.93
Average trade−0.02R−0.13R−0.05R
95% interval of the average−0.13 to 0.10−0.30 to 0.04−0.15 to 0.04
t-statistic of trade R−0.27−1.52−1.05
Win rate28%27%28%
Average win / average loss2.512.272.44
Max drawdown$14,988$16,753$28,676
Sharpe ratio (daily, annualized)−0.14−1.10−0.42
Longest losing streak221822
Long / short profit factor0.98 / 0.970.78 / 0.860.92 / 0.94
Average holding time162 min156 min160 min
Commission paid$14,840$4,802$19,641
Cumulative P&LDrawdown from the highOut of sample from 2024-01-18

Drag across the chart to zoom into a period, double-click to reset.

Figure 1. Cumulative P&L after costs and its drawdown from the running high, 2017-07-17 to 2026-10-30, at about $250 of risk a trade. The shaded part is out of sample.
In sample (1,125 trades)Out of sample (509)Averages

Averages: −0.02R in sample, −0.13R out of sample.

Figure 2. The distribution of trade results in R, as a share of each side's trades. Bars are in sample; the line is out of sample.
In sampleOut of sampleQuintile mean, 95% intervalOLS fitDensity contours

1,600 of 1,634 points drawn; the fit and the means use all of them. Drag a box to zoom, double-click to reset.

Figure 3. Trade R against the first bar's size, log x-axis; the dashed line is the OLS fit (r = 0.01, p = 0.80, n = 1,634; Spearman ρ = 0.43). Out of sample alone: r = 0.01, p = 0.77. Squares are the means of five equal-count bins, with 95% intervals.

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. 2 were profitable in sample and 0 out of sample.

955
0.91
0.86
0.82
0.78
840
0.88
0.86
0.80
0.75
720
0.89
0.89
0.83
0.77
660
0.89
0.91
0.82
0.74
0
0.050
0.10
0.20

Smallest first bar (%) across, exit (minutes after midnight ET) up. Solid outline: the defaults we tested; dashed: the in-sample best.

Hover a cell for both sides of the split.

Smallest first bar (%) 0.00 to 0.20 across · Exit (minutes after midnight ET) 660.0 to 955.0 in depth · Profit factor, out of sample 0.74 to 0.91 as height and shade. Drag or use the arrow keys to turn it.

Drag to rotate; ctrl or ⌘ and scroll to zoom.

Figure 4. Profit factor across smallest first bar (%) and exit (minutes after midnight ET), as a map and as a surface of the same grid. Values above 4 are drawn at 4.

What would change it

Nothing on the grid helps. Its in-sample best, smallest first bar (%) 0.2 and exit (minutes after midnight ET) 955, had profit factor 1.06 in sample but 0.78 out of sample, against 0.82 for the defaults.

In-sample yearOut-of-sample year95% interval
Figure 5. Average trade by calendar year with its 95% interval: a year-by-year walk through the history. Lighter bars are in-sample years.
Figure 6. Average trade in three volatility regimes: terciles of the 20-session average of the daily range (% of the open), up to the day before the trade (regular session). The cut-offs use the whole period, so this describes, it doesn't forecast.
Figure 7. Average trade by weekday and by the hour of entry (New York time), with 95% intervals.
Median25th to 75th percentile5th and 95thRuin: down $2,000
Figure 8. 2,000 simulated years of 252 sessions, drawn session by session from the whole backtest (days without trades included), with 48 paths drawn; red paths lost $2,000 at some point. Risk of ruin 83.2% [81.4%, 84.7%]; 37% of years ended up; median ending P&L −$2,208, 5th to 95th percentile −$12,187 to +$8,604.

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.

PlanPass odds, 95% intervalPassFailOut of timeMedian sessions
AquaFutures Beginner 50K Evaluation21.0%62%17%26.5
Bulenox 50K Qualification Account (Legacy, Option 2, EOD drawdown)20.9%62%17%26
Bulenox 50K Qualification Account (Legacy, Option 1, trailing drawdown)19.1%72%9%25
Alpha Futures Zero 50K Evaluation19.0%73%8%25
Apex Trader Funding 50K EOD Evaluation19.0%73%8%25
Funded Futures Family 50K Evaluation (standard plan)19.0%73%8%25
Top One Futures Elite Challenge 50K19.0%73%8%25
FundedNext Futures Rapid Pro Challenge 50K18.9%73%8%25
Lucid Trading LucidPro 50K Evaluation18.9%73%8%25
Tradeify 50K GROWTH Evaluation18.9%73%8%25
Scale 0 to 25%.
Figure 9. Simulated pass odds by plan, best first, with each plan's fail and out-of-time shares and the median sessions to a pass.

7Limitations

  • No target: trades exit at the stop or at 15:55 ET.
  • One market (M2K).
  • 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 0.82 out of sample. Nothing on the grid helps. Its in-sample best, smallest first bar (%) 0.2 and exit (minutes after midnight ET) 955, had profit factor 1.06 in sample but 0.78 out of sample, against 0.82 for the defaults. On this reading of the rules, with these costs, the historical record gives no reason to expect a profit.

Every number on this page comes from the M2K bot above, run by our backtest engine on our own data. We publish what doesn't work as well as what does, and we don't tune rules to look good.

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.