Sigmoid-SML Structural Expansion

Family: trend_following · Regime: trending · Complexity: medium · Asset classes: Forex, Equities, Crypto · Timeframes: H1, H4, D1

Thesis

Price acceleration away from a long-term mean (measured by a Sigmoid function) indicates a high-probability trend regime. However, entries at the peak of momentum are often sub-optimal. This strategy bets that entering at 'validated structural zones' (SML) during these expansions provides a superior risk-reward profile, using MdAE to insulate the stop-loss from typical price noise (open-to-close deviation).

Components

• Logistic Function (SIGMOID) (regime) — Acts as a non-linear trend filter; values > 0.5 indicate price is in an accelerating bullish phase relative to its 200-period mean.
• Momentum (MOM) (direction) — Confirms that the short-term price velocity aligns with the broader regime identified by the Sigmoid function.
• SML — SUPPORT/RESISTANCE MATRIX (entry) — Identifies high-probability entry points by finding price reactions at historical pivot clusters (Support in uptrends, Resistance in downtrends).
• Relative Strength Index (RSI) (exit) — Identifies momentum exhaustion points to lock in profits before mean-reversion occurs against the trend.
• Median Absolute Error (risk) — Provides a robust volatility estimate for stop-loss placement, measuring the typical 'prediction error' between open and close.

Known failure conditions

• The asset enters a prolonged low-volatility 'sawtooth' pattern where Sigmoid hovers at 0.5 and MOM oscillates around zero.
• SML zones fail to hold repeatedly (break-and-retest failure), indicating a fundamental shift in market structure.
• MdAE collapses to near-zero, resulting in stops that are too tight for standard spread/commission friction.

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.