Al Brooks Price Action Trading Engine
PAI-Lab
An adaptive, multi-timeframe trading engine that translates Al Brooks' discretionary price-action methodology into quantified, risk-gated execution logic.
PAI-Lab reads market structure across four timeframes at once — 1H and 15M for context, 5M for structural signals such as second entries and wedge reversals, and 1M for precise micro-entry timing. Every candidate signal is scored against a composite pressure metric, then routed through a state machine that gates counter-trend and breakout trades until they are structurally confirmed. Before capital is committed, a Monte Carlo simulation sandbox runs a thousand-iteration synthetic backtest against the current regime, only allowing trades that clear a minimum expected value and probability of profit — with risk, targets, and position size all scaling continuously with a live trend/range probability rather than snapping between fixed modes.
What we are exploring
The system is shaped by questions we keep returning to in our research notes. Where answers are speculative, the design is conservative; where the answers are mature, we ship against them.
Why it matters
Projects exist to be measured against outcomes, not against a launch narrative. The studio reviews each project against the standard a regulated enterprise would apply to any operational system.