Turbulence-Filtered Fractal Breakout
Family: breakout · Regime: trending · Complexity: medium · Asset classes: FX, Equities, Crypto · Timeframes: H1, H4
Thesis
This strategy hypothesizes that market 'turbulence' (the frequency of SMA crossings) acts as a leading indicator of trend quality. By filtering for low-turbulence periods and requiring both a momentum shift (CCI) and a structural breakout (Mn Fractal/Boxline), the system attempts to capture the initial phase of a trend while using real-time spread data to avoid high-cost, low-probability entries common during news events.
Components
- Market Weather Price MA Cross (regime) — Acts as the primary regime filter; low 'cross counts' indicate a trending or stable environment, while high counts signal high-frequency noise/turbulence unsuitable for momentum.
- CCI Arrows (direction) — Provides the core momentum directional bias by identifying shifts in price relative to its statistical mean.
- Mn Fractal Store (entry) — Identifies the specific horizontal price levels (peaks/troughs) that represent structural resistance/support for entry triggers.
- ZigZag Color (Classic) (exit) — Maps the macro-swing structure to identify when the current trend leg has likely exhausted, triggering a technical exit.
- Spread Monitor (Tick-Level) (risk) — Used to dynamically adjust Stop Loss distances and ensure trade execution only occurs when liquidity is sufficient (low spread).
- Boxline (Range Breakout) (volatility_filter) — Filters for volatility expansion by requiring price to break out of a consolidation zone before considering entries.
Known failure conditions
- Market Weather Count remains high (>40) for extended periods, indicating a permanent shift to high-noise chop.
- Average spread exceeds 50% of the target profit margin, rendering the technical edge mathematically irrelevant.
- CCI signals oscillate across the zero-line more than 3 times within a single Boxline range.
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