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Tracks the AVWAP_Confluence strategy — now one of the TOP performers in the portfolio. Use when evaluating strategy strengths or considering AVWAP changes.
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Basierend auf der SOC-Berufsklassifikation
Tracks the Hidden_Divergence strategy — consistently profitable across all runs. Use when analyzing divergence-based entries or risk allocation.
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Historical reference for the TrendPullback strategy — removed from active portfolio in V2.0.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.
Historical reference: SR_Breakout_Retest and Donchian_Breakout previously produced zero trades.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.
| name | strategy-avwap-confluence |
| description | Tracks the AVWAP_Confluence strategy — now one of the TOP performers in the portfolio. Use when evaluating strategy strengths or considering AVWAP changes. |
| Metric | Value |
|---|---|
| Net Profit | +$8,182.68 |
| Trades | 353 |
| Win Rate | 21.25% |
| Profit Factor | 1.12 |
| Composite Score | 63.8/100 (B) |
| Contribution | 27.6% of portfolio profit |
AVWAP_Confluence is now the third-largest profit contributor, behind Bollinger Mean Reversion and PriceAction_SR. Despite a low win rate (21%), the strategy's average win significantly exceeds its average loss, producing a solid PF of 1.12.
Key characteristics:
