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Tracks the Hidden_Divergence strategy — consistently profitable across all runs. Use when analyzing divergence-based entries or risk allocation.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
| name | strategy-hidden-divergence |
| description | Tracks the Hidden_Divergence strategy — consistently profitable across all runs. Use when analyzing divergence-based entries or risk allocation. |
| Metric | Value |
|---|---|
| Net Profit | +$4,578 |
| Trades | 93 |
| Win Rate | 31.18% |
| Profit Factor | 1.31 |
| Composite Score | 67.4/100 (B) |
Rank: #4 of 7 in portfolio. Positive PF across 5 consecutive runs.
Tracks the ICT_Killzone_Macro strategy — improved to PF 1.300 but not in active portfolio. Use as a reference for killzone-based experiments.
Historical reference for the TrendPullback strategy — removed from active portfolio in V2.0. Retained as a template for what works in trend following.
Drives the Argus iterative learning loop. After every backtest run, invoke argus_learn.py to score, detect regressions, and generate hypotheses. Update skills/references/ when promoting a change.
Tracks the AVWAP_Confluence strategy — now one of the TOP performers in the portfolio. Use when evaluating strategy strengths or considering AVWAP changes.
Historical reference: SR_Breakout_Retest and Donchian_Breakout previously produced zero trades. This has been resolved in V2.0 — both now generate active signals. Retained as a "don't repeat" reference.
Guidelines for portfolio-level risk management in the Argus backtest system. Covers circuit breakers, correlation handling, position sizing, and market regime detection. Use when modifying engine.py, risk_manager.py, or config.yaml.
