Logit-Wave ATOM Hybrid Trend Strategy

Family: hybrid · Regime: trending · Complexity: high · Asset classes: Crypto (ATOMUSDT) · Timeframes: 15m, D1

Thesis

The hypothesis is that ATOMUSDT price movements on the 15m timeframe follow institutional daily trends (D1 BB) and can be predicted using a logistic regression model of market structure (ATOM Coefficient) when confirmed by local volume clusters (WaveTrend). The strategy assumes that market 'noise' is minimized when internal UDT memory diagnostic tests pass, providing a cleaner signal for the logit model.

Components

• Unsupported array.range UDT method (regime) — Acts as a 'logic sanity check' regime; if the diagnostic test fails to return a 0 value (representing a static/non-volatile UDT state), execution is halted to prevent trading in unstable memory environments.
• Extrem SuperTrend (direction) — Defines the primary trend bias using ATR-based trailing stops to ensure entries align with medium-term momentum.
• ATOM Coefficient Indicator (logit) (entry) — Provides the core entry trigger via a logistic regression model that predicts price direction based on ATOM-specific market structure.
• FractalScanner (exit) — Provides the exit logic by identifying local swing highs/lows where momentum is likely to stall or reverse.
• Average True Range (ATR) (risk) — Determines the dynamic stop-loss distance and scales position size relative to current market volatility.
• WaveTrend v3 [WavesUnchained] (confirmation) — Filters the logit entry by requiring high-conviction volume and market structure alignment scores.
• D1 Bollinger Bands (Period 90) on M15 (Forward Shifted) (volatility_filter) — Filters out trades against the dominant Daily trend to avoid 'death by a thousand cuts' in counter-trend environments.

Known failure conditions

• ATOMUSDT price action decouples from the hardcoded logit coefficients (model drift).
• The strategy generates zero trades due to the array.range UDT diagnostic failing in the production environment.
• D1 Bollinger Band lookahead bias results in significant divergence between backtest and live performance.

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