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Been grinding on this for about 6 months full-time now. Started with mean-reversion ideas, then went into microstructure, order flow, ML, cross-asset lead-lag, basically everything I could get my hands on. I have 3 years of Databento L2 tick data on MNQ, 7 years of 1-min bars, 15 years of MGC, a 20-core server, and I built a custom Rust stack for tick parsing and L2 order book reconstruction before I realized I was reinventing what Nautilus does better, so I pivoted to Nautilus 1.225 with mlfinpy and vectorbt on top.
So, the actual work. I tested 17 strategies. Let me just dump them so you understand I'm not asking about RSI settings.
On the microstructure side, I tried spread regime filters, quote response after aggressive bursts, volume price classification (Harris style), sweep continuation and sweep reversal, book imbalance directional, aggressor volume trend follow, delta and CVD divergence, and absorption patterns. All came out around 50% win rate once I corrected for the obvious stuff like measuring book imbalance after the move instead of before.
On the classic technical side, I did ORB 5/15/30 min with and without ATR trail, inside bar breakout (started at 84% WR, dropped to 53% after I found my lookahead bug), FVG on 30-min bars (this one was the closest I got to something, 55% WR over 103 trades, but p=0.15, so basically noise), mean reversion with asymmetric R:R, which is structurally losing because NQ is momentum intraday; gap fill at RTH open, which worked in recent years but breaks on 7-year history.
I tried ML twice: triple barrier labeling with random entries as a baseline. The ML matched the random baseline exactly. Then meta-labeling with 6 models and an ensemble on top, zero improvement over no signal. That's when I really internalized the "ML amplifies edge, doesn't create it" thing.
GEX as a regime filter turned out to capture vol clustering, not direction. Permutation entropy: nothing. Cross-asset signals (ZN, DX, Gold into NQ): nothing. Overnight momentum follow-through: nothing. Composite voting across 5 weak signals: still nothing; weak plus weak is not strong.
The most recent attempt was the one I did the most rigorously: Nautilus backtest with a LatencyModel at 100ms base + 50ms insert, one-tick deterministic slippage, $0.50 per contract per side, bar adaptive high-low ordering to avoid the OHLC asymmetry bias, and I even implemented a delayed entry pattern where the signal detected on bar N is buffered and submitted on bar N+1 to stop the fills from happening inside the same bar as the signal (which is a subtle lookahead in bar backtests). Sixty-eight unit tests on the whole thing.
The strategy was just Bollinger Band mean reversion 5-min, BB(20, 2σ), ATR-based stops, session 09:40 to 15:50 ET with lunch skipped, and force flatten at 15:45. Nothing fancy.
Ran it for the full year 2023, 117 trades over 252 days. WR 48.7%, expectancy minus $6.52 per trade, total PnL minus $762, Sharpe minus 1.34. Bootstrap 10k iterations gave me IC 95% on expectancy of \[minus $14.99, plus $1.82\]. So technically "not significantly different from zero," but zero edge demonstrated.
I did post-hoc analysis on those 117 trades. Two things jumped out. First, in a 2023 bull market, I took 79 shorts versus 38 longs. The strategy kept calling uptrend continuations "overbought reversion" and got run over. Second, 14h ET was a bloodbath. Thirty-five trades in that hour, WR 34%, minus $605 by itself. Afternoon news flow breakouts don't reverse.
Then I thought, "Okay, the problem is no regime filter; let me add ATR(5)/ATR(30) < 0.8 as a 'range regime' switch and only trade MR in range." Before writing any code, I looked at the 117 existing trades grouped by regime. Got the exact opposite of what I expected. Range regime was the WORST segment, minus $11.59 per trade, WR 37%. Expansion regime was less bad, minus $4.35 per trade, WR 54%. Strong expansion was plus $0.21, but on 51 trades, which is noise. In a tight range, the bands are so narrow the signal is triggering on pure bar noise; there's no real deviation to revert from.
Then I thought, "Fine, overnight gap fade; that's academically documented (Lou Polk, Skouras 2019)." Pulled the 1,696 days of MNQ I had and looked at the distribution before coding. Mean gap is +8.3 pts (consistent with the overnight drift paper, fine), but the fill rate of the gap toward previous close inversely scales with magnitude. Eighty-one percent fill for tiny gaps you can't exploit after costs, 33% for gaps > 0.5σ, literally 0% for gaps > 1.5σ. So the retail folklore that big gaps fill is just false on MNQ. The big gaps continue; they don't revert. And there's no up versus down asymmetry in fills either (30% vs 29%) so I can't even pick one side.
Which is where I am right now. Stuck. I keep reading posts here where people mention they have a live edge on NQ or ES intraday, and I absolutely believe some of you do, because the infra and rigor I see in certain comments is real. But I cannot find one. Not a tradeable one. Not after costs. Not after honest bias correction.
So my questions, and I'm being genuine here:
1. Is there a fundamental reason a retail trader without colocation should expect to find zero edge on MNQ/NQ intraday bars, and the guys you see posting live profits are either HFT adjacent, event driven, or trading a completely different timeframe/style than "5-min bars + indicator + stop + TP"? Basically, am I fishing in an empty pond?
2. If the edge on index futures is real for retail, what category of strategy should I even be looking at? I've done indicator MR, breakouts, order flow, ML, cross asset, regime filters, and gap plays. Is the thing I'm missing something structural like MOC imbalances, FOMC/CPI window trades, roll arbitrage, index rebalancing flows, something event-driven that none of my bar-based setups could ever capture?
3. For people who genuinely have a live intraday edge on NQ/ES, how many strategies did you burn before finding it? Is 17 normal, or did I burn through variants of the same bad approach without realizing it?
4. Is my methodology actually sound, or am I fooling myself somewhere? I do walk forward, permutation baselines, realistic slippage/fees/latency, and bootstrap IC on expectancy; I compare it to permutation null. What am I not doing that I should?
5. Honest question: should I just drop intraday futures and go for something else ?
Thanks for reading this far.