Best Day Trading Strategies Ranked: 8 NQ Systems Backtested

The best day trading strategies on Nasdaq futures, judged by one strict rule, turned out to be a short list: of the eight intraday systems we backtested on NQ, only the three range breakouts finished net positive after costs, and only one, the 15-minute opening range breakout (ORB), cleared a profit factor of 1.0 in both halves of the test. Everything else, including gap fills, VWAP trend days and a 15-minute RSI(2) pullback, lost money once we charged a realistic cost per trade.

This is the day-trading slice of our top 20 trading strategies ranked pillar. Same data, same method, just the eight "day trade" entries ranked among themselves.

How we ranked these day trading strategies

We fixed the method before looking at the ranking so we could not shop for a flattering threshold:

• Data: NQ continuous front-month futures, 3,884 regular sessions (09:30-16:00 ET) on 15-minute bars, June 7, 2010 to April 16, 2026.
• Settings: each strategy uses its standard, textbook setting. No optimization.
• Costs: 1.0 NQ point deducted from every round trip for slippage and commission. Results are in NQ index points per 1 contract. MNQ is $2 per point, NQ is $20 per point.
• Fills: if a single bar touches both the stop and the target, we count the stop first (conservative). All positions are flat by the close, so there is no overnight gap risk in these numbers.
• Qualify: at least 30 trades. All eight day trades have hundreds or thousands, so sample size is not the problem here.
• Score ("robust PF"): the lower of the profit factor for 2010-2019 and for 2020-2026. A strategy only ranks high if it worked in both eras. Tie-break: total points.

Why the era split matters: NQ went from roughly 1,800 to roughly 26,000 over the test. A 1% move in 2024 is worth about ten times as many points as a 1% move in 2011, so raw point totals are dominated by 2020-2026. The robust PF stops a strategy from hiding a losing decade behind a few big recent years.

Day trading strategies ranked: the table

Profit factor is gross wins divided by gross losses. Above 1.0 makes money, below 1.0 loses. "Closed-trade DD" is the worst peak-to-trough drop in cumulative closed-trade points. For day trades that close every session it is close to real drawdown, but it still ignores intrabar swings.

Per-strategy breakdown

1. 15-minute opening range breakout (ORB): the only one that held in both eras

• Rule: mark the high and low of the first 15-minute bar. Buy a break of the high or sell a break of the low. Stop at the other side of the range. Hold to the close.
• Numbers: 3,880 trades, 39.6% winners, PF 1.17 overall, 1.03 in 2010-2019 and 1.21 in 2020-2026. +15,205 points total (+642.2 then +14,562.8). Closed-trade drawdown 2,918 points.
• Verdict: the winner, but read the split. 2010-2019 was essentially breakeven. Nearly all of the profit arrived in the high-volatility 2020s. On MNQ the average trade works out to about $7.84 (3.92 pts x $2).

Full write-up: ORB 15 vs 30 minute opening range breakout. For stop variations, see ORB stop placement: midpoint vs range.

2. Initial balance breakout (first hour)

• Rule: same idea on the first 60 minutes (the "initial balance" in Market Profile terms). Stop at the opposite side, hold to the close.
• Numbers: 3,690 trades, 48.3% winners, PF 1.06 overall, 0.93 then 1.11. +5,421.8 points total, but -1,443.2 in 2010-2019 and +6,865 in 2020-2026. Closed-trade drawdown 4,688.2 points.
• Verdict: net positive, but it lost money for a whole decade. The wider range means a wider stop and a thinner edge per trade (1.47 pts average).

Details: initial balance breakout strategy.

3. 30-minute opening range breakout

• Rule: first 30-minute range, stop at the other side, hold to the close.
• Numbers: 3,857 trades, 43.7% winners, PF 1.12 overall, 0.91 then 1.19. +11,010.8 points total: -2,252.8 in 2010-2019, +13,263.5 in 2020-2026. Closed-trade drawdown 5,237 points.
• Verdict: the second-largest point total, but it earned its rank on the tie-break, not on robustness. Its worst-era PF (0.91) is the same as the gap fill's.

4. Opening gap fill (fade)

• Rule: fade every opening gap of 0.1% or more back toward the prior close. Stop = 1x the gap size the other way.
• Numbers: 3,236 trades, 48.4% winners, PF 0.97 overall, 0.91 then 0.99. -2,369.5 points (-1,591 then -778.5). Closed-trade drawdown 6,051.8 points.
• Verdict: lost in both eras. The "gaps always fill" folklore did not pay on NQ with these rules. See opening gap fill strategy on Nasdaq.

5. VWAP trend day

• Rule: at the 10:00 bar, go long if price is above session VWAP, short if below. Hold to the close.
• Numbers: 3,884 trades, 49.2% winners, PF 0.99 overall, 0.89 then 1.03. -1,080.8 points (-3,200.2 then +2,119.5). Closed-trade drawdown 7,230.5 points, the worst on this list.
• Verdict: a coin flip with a cost attached. See VWAP trend day strategy backtest.

6. 15-minute RSI(2) pullback

• Rule: buy when 15-minute RSI(2) drops below 10 while price is above the 50-bar EMA. Exit when RSI rises above 70, or at the close.
• Numbers: 1,599 trades, 63.5% winners (the highest here), PF 0.85, 0.83 then 0.86. -2,937 points (-744.5 then -2,192.5). Closed-trade drawdown 3,765.5 points.
• Verdict: the classic high-win-rate trap. It wins often and still loses money. The daily version is a different story (see Connors RSI(2) on Nasdaq futures), and our best RSI settings for day trading post digs into the intraday settings.

7 and 8. Inside day + 30-min ORB and NR7 + 30-min ORB (Toby Crabel filters)

• Rule: take the 30-minute ORB only on the day after an inside day (658 trades), or only after an NR7 day, the narrowest range of the last seven (399 trades). These volatility-contraction filters are commonly credited to Toby Crabel.
• Numbers: Inside day: PF 1.09, 0.79 then 1.22, +1,480.5 points (-1,036.8 then +2,517.2). NR7: PF 1.02, 0.67 then 1.18, +218 points (-877.5 then +1,095.5).
• Verdict: the filters did not help. The unfiltered 30-minute ORB had a 2010-2019 PF of 0.91. Both filtered versions were worse in that era (0.79 and 0.67). They trade less, so they lose less in absolute points, but the edge per trade did not improve in a way that survived both eras. See NR7 and inside day strategy.

What a 1-point cost does to thin edges

Day trading edges are small, so costs decide the verdict. Because we deduct exactly 1.0 point per round trip, you can add the trade count back to see the result before costs (a simple derived number):

• Opening gap fill: -2,369.5 after costs, about +866.5 before costs on 3,236 trades. Roughly +0.27 points per trade gross, wiped out by the 1-point charge.
• VWAP trend day: -1,080.8 after costs, about +2,803.2 before. Around +0.72 points per trade gross, not enough.
• 15-minute RSI(2): -2,937 after costs and still about -1,338 before costs. It had no gross edge at all.
• 15-minute ORB: +15,205 after costs, about +19,085 before. The 1-point charge took roughly a fifth of the gross result.

Two of the three losers were slightly profitable before costs. That is the most common way a day trading strategy dies: a real but tiny tendency that can't pay the spread plus commission. If your own fills are worse than 1 point per round trip, even the ORB's margin gets thinner.

What this backtest does not tell you

These are past results on one market and they don't guarantee future results. Fills are assumed at exact breakout and stop levels, which fast markets won't always give you. We don't model taxes, platform fees beyond the 1-point allowance, news-day halts or position sizing. Point totals are for one contract held through the whole test. For comparison, buy and hold NQ made +24,677.2 points over the same span with a 5,878.2-point drawdown. That isn't a like-for-like comparison (buy and hold carries overnight and multi-month risk), but it's a useful reality check: the best intraday system here made less than passive long exposure.

FAQ

Loomi.Ai provides educational market research, not financial advice. Trading futures and options involves substantial risk of loss, and backtested results are historical and do not guarantee future returns.

Sources

• Loomi backtest: blog_strategy_tests.py + results JSON, Loomi research
• Loomi strategy ranking: rank_strategies.py + strategy_ranking.json, Loomi research