TLB-MESA Structural Momentum Strategy

Family: hybrid · Regime: trending · Complexity: high · Asset classes: Equities, Forex, Indices · Timeframes: H1, H4, D1

Thesis

The strategy assumes that market structure is best identified by price-action reversals (TLB) rather than time-based candles. By filtering the resulting 'noise-free' trend with Ehlers' signal processing (MESA Stochastic), we can identify high-probability entries into an established trend. The use of Darvas Boxes provides a non-arbitrary stop-loss based on recent consolidation, while Pitchforks exploit the tendency of price to return to a mean median line within a trend channel.

Components

• Three-Line Break (TLB) with MA (regime) — Defines the macro trend regime by filtering out minor price fluctuations, ensuring trades only occur in the direction of structural shifts.
• Unsupported matrix remove_col (direction) — Used here as a basic price-action slope filter (Direction) despite its structural coding errors.
• Ehlers MESA Stochastic (MSTOCH) (entry) — Identifies cyclical entry points by applying a high-pass filter to remove trend bias before calculating momentum.
• Auto Pitchfork (exit) — Provides dynamic targets based on median line theory and fractal pivots.
• Darvas Boxes MetaTrader 5 (risk) — Determines the technical 'floor' or 'ceiling' for stop-loss placement based on consolidation breakouts.
• GHOST OrderFlow Dashboard — DerivEAPro v10 (confirmation) — Provides a final confirmation of order flow sentiment to ensure momentum is backed by volume/sentiment.

Known failure conditions

• Price breaches the Darvas Box boundary opposite to the trade direction immediately after entry.
• TLB 'LinesToBreak' is too high for current volatility, causing the regime to flip only after the move is exhausted.
• The matrix.remove_col error prevents the execution environment from processing the direction filter.

Explore the full interactive blueprint, parameter ranges and evidence on WOBR StrategyVerse, or generate this strategy as an MT4/MT5 Expert Advisor with QuantMogul AI Engine.