jgrusewski 4b7fb3340f feat(plan): recursive plan revision — living plan document (N17) ...

When readiness≥0.7 and conviction changes significantly mid-trade:
+30% conviction → extend plan (thesis strengthening)
-60% conviction → shorten to exit in 3 bars (thesis collapsing)
Normal fluctuation (0.4x-1.3x) → plan unchanged.
The model learns to revise plans based on evolving assessment.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-17 09:12:37 +02:00

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backtesting

refactor: collapse 9-level to 7-level ExposureLevel — eliminate degenerate Flat variants

2026-04-11 11:54:09 +02:00

common

fix: switch tracing to stderr (unbuffered) — stdbuf has no effect on Rust

2026-04-02 16:29:55 +02:00

config

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ctrader-openapi

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data

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database

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market-data

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ml

feat(plan): recursive plan revision — living plan document (N17)

2026-04-17 09:12:37 +02:00

ml-asset-selection

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ml-backtesting

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ml-checkpoint

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ml-core

feat: position-gated episodes + 5000-bar limit — close 45x training/val gap

2026-04-16 21:56:44 +02:00

ml-data

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ml-data-validation

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ml-dqn

feat: wire up all IQL features + remove dead code

2026-04-13 19:28:00 +02:00

ml-ensemble

feat(ensemble): GPU-native ensemble reduce kernel, remove CPU fallbacks

2026-03-29 22:35:37 +02:00

ml-explainability

feat(ensemble): GPU-native ensemble reduce kernel, remove CPU fallbacks

2026-03-29 22:35:37 +02:00

ml-features

fix: zen precommit — 2 criticals + 3 lows resolved

2026-04-17 02:05:20 +02:00

ml-hyperopt

refactor: LHS is the correct algorithm for small budgets, not a fallback

2026-03-29 19:18:47 +02:00

ml-labeling

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ml-observability

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ml-paper-trading

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ml-ppo

Revert "refactor: remove ALL bf16 legacy wrappers — pure native f32 across entire codebase"

2026-04-13 17:09:34 +02:00

ml-regime

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ml-regime-detection

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ml-risk

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ml-security

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ml-stress-testing

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ml-supervised

cleanup: remove half crate dependency from entire workspace

2026-04-10 18:54:14 +02:00

ml-universe

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ml-validation

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model_loader

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risk

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risk-data

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storage

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trading_engine

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trading-data

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training_uploader

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