NQ HMA Midday Strategy by QuantByBoji
By QuantByBoji
Performance Metrics
- Author: QuantByBoji
- Symbol: CME_MINI:NQ1!
- Timeframe: 15 minutes
- Net P&L: +19,875.00 USD (+1.99%)
- Win Rate: 58.0%
- Profit Factor: 1.336
- Max Drawdown: 17,780.00 USD (1.74%)
- Total Trades: 112
Description
The Story Behind This StrategyThis strategy didn't come from a quick backtest or a weekend project. It's the result of months of systematic research across multiple strategy families (DVD, Zscore, HMA) on both NQ and ES futures.My Research Process:I started with six strategy families and ran extensive backtests spanning from 2019 through April 2025, followed by recent validation from 2025 through April 2026. My goal wasn't to maximize historical PnL - it was to identify robust strategies with better drawdown behavior, stronger profit factors, and more stable portfolio-level risk/reward.After evaluating hundreds of parameter combinations and multiple objective functions, I narrowed down to two core NQ candidates. This HMA Midday strategy emerged as one of them because it showed:Strong recent performance (2025-2026: $16,865 profit, 1.53 profit factor)Reasonable drawdown characteristics ($8,940 max drawdown)Clean portfolio behavior when combined with other strategiesBetter risk-adjusted returns than the baseline HMA versionWhat This Strategy Actually Does:It's a momentum-based system using Hull Moving Averages, EMAs, and Rate of Change to identify trade setups during specific time windows (11:00-15:45 ET trading, 10:30-13:00 ET entries). I added the one-trade-per-day limit after observing that multiple daily entries often degraded risk-adjusted returns.The Honest Truth:This is still a research strategy, not a live-trading systemI have a Python version with walk-forward optimization that I use to tune parameters when market regimes changeParameters should be re-optimized periodically - they're not set-and-forgetThe strategy works best as part of a portfolio, not in isolationPast performance (2019-2026) doesn't guarantee future resultsWhy I'm Publishing It:To share the methodology and code structure with the community. The approach - combining trend indicators with momentum filters, time windows, and ATR-based risk management - is worth studying even if you don't trade this exact configuration.Developer: QuantByBojiStatus: Research candidate, not live-trading recommendation