Lewis FIXMIN
Engineer. NQ Trader. Builder.
I build systematic trading strategies for NQ futures. No discretion, no emotion, no gurus. What you see on this site is a documented process: a method that can be tested, measured, and reproduced — not a personality cult.
"Most people trade emotion. I trade systems."
The documented process
FIXMIN started as a personal observation: every trading loss I could trace back to a decision made outside the system. A position held too long because it "felt" right. An entry skipped because of news. A size too large because conviction was high. The pattern was clear — discretion was the risk.
The response was to engineer it out. Each strategy begins as a hypothesis, coded explicitly in PineScript v6. The same logic is replicated in Python for independent statistical validation using walk-forward methodology across multiple out-of-sample windows. Nothing reaches live execution without passing this process, without exception.
The NQ (Nasdaq E-mini, /NQ on CME Group) was chosen deliberately: deep liquidity, structural volatility from the technology-heavy Nasdaq 100 composition, and a micro-contract (MNQ) that enables fractional position sizing at the individual operator level. The $20/point value with CME's data depth allows statistically robust backtests with 500+ completed trades per strategy.
The result is an operating system for trading — not a prediction engine, not a signal service. The operator's role is infrastructure, not market opinion.
Systematic
All entries, exits and position sizes defined before market open. Zero ad-hoc decisions during trading hours.
Validated
500+ trade minimum per backtest. Walk-forward validation across 3+ out-of-sample windows. 1% fixed risk per trade.
Documented
Every process step is written down. The method is reproducible — not dependent on intuition or market feel.
Tools & instruments
NQ / MNQ Futures
CME Group Nasdaq E-mini and Micro E-mini. Primary trading instrument.
PineScript v6
TradingView strategy layer. Method syntax, explicit variable scoping, alert-driven execution.
Python 3 (NumPy · Pandas · Vectorbt)
Independent backtest validation, walk-forward analysis, parameter sweep.
Broker API
Live execution via programmatic order routing. TradingView alerts or direct Python signal bridge.