ATOM Logit-Bandpass Cycle Trader

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

Thesis

The hypothesis is that ATOMUSDT exhibits specific 'market structure cycles' where volume-backed momentum (Scanner) and machine-learned structure (Logit) coincide with frequency-domain oscillations (BPF). By filtering for these high-participation cyclical turns and using a noise-resistant filter (SGF), we can capture 15m swings while managing risk via adaptive trend trailing.

Components

• Custom 006 Hybrid Table Scanner (regime) — Filters for high-conviction environments where price is trending (EMA) and participation is high (Volume).
• ATOM Coefficient Indicator (logit) (direction) — Provides the directional bias using a pre-trained logistic regression model on market structure features.
• Bandpass Filter (BPF) (entry) — Acts as a cycle-aware trigger to enter trades when price momentum oscillates into alignment with the trend.
• MultiKAMA (TyphooN) (exit) — Provides an adaptive trailing stop that tightens during low efficiency/high volatility and widens during smooth trends.
• Williams Fractals (risk) — Defines hard structural levels for initial stop-loss placement based on the most recent pivot.
• Savitzky-Golay Filter (SGF) (volatility_filter) — Smooths price action to filter out high-frequency noise that might trigger the BPF prematurely.

Known failure conditions

• SGF and BPF lag becomes greater than the average 15m candle range, leading to entries at the end of moves.
• ATOMUSDT market structure shifts (e.g., move to PoS or major exchange delisting) rendering hardcoded logit coefficients obsolete.
• Extended periods of '0' regime scores on the Hybrid Scanner during low-liquidity weekends.

Explore the full interactive blueprint with parameter ranges and evidence on WOBR StrategyVerse, or generate this strategy as an MT4/MT5 Expert Advisor with QuantMogul AI Engine (free download).