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Tracks the ICT_Killzone_Macro strategy — improved to PF 1.300 but not in active portfolio. Use as a reference for killzone-based experiments.
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Basé sur la classification professionnelle SOC
| name | strategy-ict-killzone |
| description | Tracks the ICT_Killzone_Macro strategy — improved to PF 1.300 but not in active portfolio. Use as a reference for killzone-based experiments. |
Improved individually to PF 1.300 (+11.60%, DD -4.85%) but removed from portfolio because adding it worsened overall results (PF 1.17 to 0.98).
| Metric | Before (Run 4) | After (Single) |
|---|---|---|
| Net Profit | -$1,815 | +$1,218 (11.60%) |
| Profit Factor | 0.54 | 1.300 |
| Max DD | — | -4.85% |
Changes made:
Despite excellent single-strategy results, adding ICT_Killzone to the 7-strategy portfolio caused PF to drop from 1.17 to 0.98. The strategy likely overlaps with existing session-based entries (London open moves already captured).
Lesson: A strategy that works in isolation may still hurt the portfolio.
Tracks the Hidden_Divergence strategy — consistently profitable across all runs. Use when analyzing divergence-based entries or risk allocation.
Historical reference for the TrendPullback strategy — removed from active portfolio in V2.0.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Historical reference: SR_Breakout_Retest and Donchian_Breakout previously produced zero trades.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.
