Triple ADX Multi-Timeframe MAPE Scaler

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

Thesis

Trends demonstrate higher persistence when momentum (ADX) aligns across multiple lookback periods and timeframes simultaneously. By using MAPE to measure the 'error' of price relative to its mean, we can scale risk to be inversely proportional to market chaos, entering only when the 'signal-to-noise' ratio is favorable during ATR-based breakouts.

Components

• ProfitRobots Dashboard Template (regime) — Provides the hierarchical regime filter, ensuring entries only occur when the 1H and 4H timeframes align in a structural trend (Price > EMA 200).
• UT Bot Alerts (MQL5) (direction) — Acts as the primary directional trigger by identifying short-term ATR-based breakouts from consolidation.
• Easy Trend Visualizer (ETV) (entry) — Ensures the entry occurs during a high-conviction momentum 'surge' where three different ADX periods are simultaneously rising.
• Ichimoku Kinko Hyo (exit) — The Kijun-sen (Base Line) provides a dynamic trailing exit that accounts for medium-term equilibrium.
• Mean Absolute Percentage Error (MAPE) (risk) — Standardizes risk by calculating the historical deviation from the mean; used to set stops and size positions based on relative price instability.
• Fisher Transform (EarnForex) (confirmation) — Normalizes price distribution to confirm that the momentum surge is not yet exhausted (mean reversion hasn't begun).

Known failure conditions

• Persistent divergence between Fisher Transform and UT Bot signals leading to whipsaws.
• Market regimes where ADX stays below 20 for extended periods, preventing entry during low-volatility drifts.
• MAPE values consistently exceeding 2%, indicating extreme volatility where the model's error rate makes stop-placement unreliable.

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.