Adaptive Efficiency Cycle Trader

Family: hybrid · Regime: trending · Complexity: medium · Asset classes: FX (Majors), Gold (XAU/USD), Equity Indices (Trend-prone) · Timeframes: H1, H4

Thesis

Profitable trend trading requires a filter for 'market efficiency' (the ratio of noise to movement). By using VIDYA to quantify this efficiency and the Moving Average Ribbon to define directional hierarchy, we identify 'True Trends'. Within these trends, price behaves cyclically; entering at cycle troughs (Restu Oversold) and exiting at cycle peaks (DSP Cross) captures the highest-velocity portion of the trend move while minimizing drawdown during corrections.

Components

• Variable Index Dynamic Average (VIDYA) (regime) — Acts as a volatility-adjusted trend quality filter. Only enters trades when the efficiency of the trend exceeds noise levels.
• Moving Average Ribbon (chingc) (direction) — Provides hierarchical trend confirmation; requires full stack alignment to ensure high-probability directionality.
• Restu Kaioh Scalping Indicator (entry) — Used for pullback entry timing; identifies local exhaustion (OS/OB) within a primary trend.
• Ehlers Detrended Synthetic Price (DSP) (exit) — Isolates the cyclical component to time exits when the trend's momentum wave completes its cycle.
• ATR Heiken Ashi (risk) — Calculates smoothed volatility for dynamic stop-loss placement and risk-adjusted position sizing.

Known failure conditions

• Market enters a 'low-volatility drift' where VIDYA cannot adapt quickly enough to price micro-cycles.
• Negative correlation between price efficiency (VIDYA) and cycle stability (DSP) leads to early exits in strong trends.
• Extended flat-line MA ribbon alignment during high-impact news spikes.

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.