Quant research

NASDAQ-100 FYP Strategy

Year
2026
Role
Research, implementation, evaluation
Status
Final-year project
Pine Script v6TradingViewNQ1! futuresWalk-forward analysis
%
Win rate (in-sample)
+$
In-sample P&L
In-sample profit factor
Trades
Fig. 01 – NASDAQ-100 FYP strategyEquity · in-sample
Jan 2025Feb 2026
+$28,400Net P&L
56.94%Win rate
1.703Profit factor

What it is

My final-year project: a rule-based quantitative strategy for NQ1! E-mini futures built around Smart Money Concepts. It targets the NY morning session with an Inverse Fair Value Gap plus Change in State of Delivery double confirmation, inside a strict 28-minute execution window.

Honest results

In-sample (Jan 2025 – Feb 2026): 56.94% win rate, +$28,400 net P&L, 1.703 profit factor, 0.95% max drawdown across 72 trades.

Out-of-sample (Jan 2023 – Dec 2024): 36.27% win rate, 0.855 profit factor, −$15,650. Reporting the weaker out-of-sample period is deliberate – it shows awareness of overfitting and market-regime risk rather than hiding it.

What survived testing

  • A 1-minute liquidity-sweep filter was the only added filter that helped: +7.76% win rate, +0.311 profit factor. It stayed.
  • HTF EMA trend filter, minimum FVG-size filter, strong-candle filter, and a volume filter were all tested and cut – no meaningful edge, or worse.

The sequel: the edge went on trial

After submission I built a six-phase, pre-registered research program around this strategy – a no-lookahead backtest engine, walk-forward validation, and frozen decision rules – to settle whether the +$28,400 was a real edge or period-specific tuning. It was tuning: across ~10 years, three futures markets, and 1,402 out-of-sample trades, the edge did not survive. The full story is in the Quant Strategy Research Program case study.