chore: Move internal MD files to docs/ directory

Moved to docs/:
- CHANGELOG.md (duplicate of changelog/)
- IMPLEMENTATION_SUMMARY.md
- STRATEGY_BUILDER_DESIGN.md
- TODO.md
- QWEN.md (AI assistant context only)

Root MD files (GitHub standards only):
- README.md (main documentation)
- LICENSE (legal requirement)
- SECURITY.md
- CODE_OF_CONDUCT.md
- CONTRIBUTING.md
- SUPPORT.md
- ATTRIBUTION.md

Root directory: 31 files → 29 files

TODO.md

@@ -1,150 +0,0 @@
-# Predix — Implementierungs-Tracker
-
-## Übersicht
-- **Start:** April 2026
-- **Ziel:** Vollständig integriertes Quant Trading System in `fin_quant` Loop
-- **Status:** ✅ ALLE PHASEN ABGESCHLOSSEN (P0-P9)
-
----
-
-## Phasen
-
-### P0: Data Loader (2h) ✅ ABGESCHLOSSEN
-- [x] `rdagent/scenarios/qlib/local/data_loader.py` erstellt
-  - [x] OHLCV Loading + Caching (HDF5 → pd.Series)
-  - [x] Faktor Loading + Metadaten (JSON + Parquet)
-  - [x] Feature Matrix Builder (alignment mit close)
-  - [x] Thread-sicheres Caching
-- [x] Tests: `test/local/test_data_loader.py` (11 passed)
-- [x] Abhängigkeiten: Keine
-
-### P1: Strategy Worker (4h) ✅ ABGESCHLOSSEN
-- [x] `rdagent/scenarios/qlib/local/strategy_worker.py` erstellt
-  - [x] LLM Call Wrapper (llama.cpp :8081)
-  - [x] Backtest Engine (subprocess mit OHLCV)
-  - [x] Acceptance Gate (FTMO-konform)
-  - [x] FTMO Compliance Check
-- [x] Tests: `test/local/test_strategy_worker.py` (41 passed)
-- [x] Abhängigkeiten: P0 (data_loader.py)
-
-### P2: Strategy Orchestrator (6h) ✅ ABGESCHLOSSEN
-- [x] `rdagent/scenarios/qlib/local/strategy_orchestrator.py` erstellt
-  - [x] Multi-Process Pool (4-8 Workers)
-  - [x] Task Queue (random factor selection)
-  - [x] LLM Semaphore (max 2 parallel für llama.cpp)
-  - [x] Result Collection + Deduplizierung
-  - [x] Strategy Saver (JSON + Reports)
-- [x] CLI Command: `rdagent generate_strategies`
-- [x] Tests: `test/local/test_strategy_orchestrator.py` (30 passed)
-- [x] Abhängigkeiten: P1
-
-### P3: Optuna Optimizer (4h) ✅ ABGESCHLOSSEN
-- [x] `rdagent/scenarios/qlib/local/optuna_optimizer.py` erstellt
-  - [x] Parameter Space Definition (FTMO-konform)
-  - [x] Objective Function (Sharpe × |IC| × √trades)
-  - [x] FTMO Penalty Logic
-  - [x] TPE Sampler + MedianPruner
-  - [x] 20-50 Trials pro Strategie
-- [x] Integration in Strategy Orchestrator
-- [x] Tests: `test/local/test_optuna_optimizer.py` (60 passed)
-- [x] Abhängigkeiten: P1, `pip install optuna`
-
-### P4: CLI Commands (2h) ✅ ABGESCHLOSSEN
-- [x] `rdagent/app/cli.py` erweitert
-  - [x] `generate_strategies` Command
-  - [x] CLI Parameter (count, workers, style, optuna)
-  - [x] Rich Console Output
-  - [ ] Integration in `fin_quant` Loop
-- [x] Tests: `test/integration/test_cli_commands.py` (21 tests)
-- [x] Abhängigkeiten: P2, P3
-
-### P5: ML Training Pipeline (6h) ✅ ABGESCHLOSSEN
-- [x] `rdagent/scenarios/qlib/local/ml_trainer.py` erstellt
-  - [x] Feature Matrix Builder (alle Top-N Faktoren)
-  - [x] Time-Series Train/Val Split
-  - [x] LightGBM Training (early stopping)
-  - [x] Feature Importance Analysis
-  - [x] Model Save/Load
-- [x] CLI Command: `rdagent train_models`
-- [x] Tests: `test/local/test_ml_trainer.py` (46 passed)
-- [x] Abhängigkeiten: P0, `pip install lightgbm`
-
-### P6: Feedback an fin_quant Loop (3h) ✅ ABGESCHLOSSEN
-- [ ] Hook in `QuantRDLoop.feedback()` einbauen
-  - [ ] `_trigger_ml_training()` alle 500 Faktoren
-  - [ ] `_trigger_strategy_generation()` alle 1000 Faktoren
-  - [ ] ML Feature Importance → Prompt Feedback
-- [ ] Prompt-Loader erweitern (local/ml_feedback.yaml)
-- [ ] Tests: `test/local/test_feedback_integration.py`
-- [ ] Abhängigkeiten: P5
-
-### P7: Portfolio Optimizer (6h) ✅ ABGESCHLOSSEN
-- [ ] `rdagent/scenarios/qlib/local/portfolio_optimizer.py` erstellen
-  - [ ] Korrelationsmatrix (max 0.3)
-  - [ ] Mean-Variance Optimization
-  - [ ] Risk Parity (gleicher Risiko-Beitrag)
-  - [ ] Black-Litterman (LLM Views als Priors)
-  - [ ] Portfolio-Backtest
-- [ ] CLI Command: `rdagent optimize_portfolio`
-- [ ] Tests: `test/local/test_portfolio_optimizer.py`
-- [ ] Abhängigkeiten: P5
-
-### P8: Integrationstests (4h) ✅ ABGESCHLOSSEN
-- [ ] End-to-End Pipeline Test
-  - [ ] Data Loading → Strategy Gen → Backtest → Accept
-- [ ] Parallelisierung Test
-  - [ ] 4 Workers, 2 LLM parallel, keine Race Conditions
-- [ ] Optuna Test
-  - [ ] 20 Trials, Konvergenz prüfen
-- [ ] FTMO Compliance Test
-  - [ ] SL ≤ 2%, DD ≤ 10%, Daily Loss ≤ 5%
-- [ ] Tests: `test/integration/test_full_pipeline.py`
-- [ ] Abhängigkeiten: P0-P7
-
-### P9: Dokumentation (3h) ✅ ABGESCHLOSSEN
-- [ ] README.md aktualisieren
-  - [ ] Neue Commands dokumentieren
-  - [ ] Architektur-Diagramm
-  - [ ] Setup-Anleitung
-- [ ] QWEN.md aktualisieren
-  - [ ] Neue Module in Architecture Section
-  - [ ] Data Flow Diagram
-  - [ ] Project Status
-- [ ] Abhängigkeiten: P0-P8
-
----
-
-## Dependencies Checklist
-
-- [ ] `pip install optuna` (P3)
-- [ ] `pip install lightgbm` (P5)
-- [ ] `pip install xgboost` (P5, optional)
-- [ ] llama.cpp Server auf :8081 mit `--parallel 2` (P1-P3)
-
-## FTMO Compliance Rules
-
-| Regel | Limit | Prüfung |
-|-------|-------|---------|
-| Max Stop Loss | 2% | Hard-coded in Optuna Space |
-| Max Drawdown | 10% | Acceptance Gate |
-| Max Daily Loss | 5% | Risk Management Layer |
-| Risk/Reward | ≥ 2:1 | TP ≥ 2× SL enforced |
-| Max Positions | 1 | Strategy Code enforced |
-
-## Risiko-Metriken (Ziele)
-
-| Metrik | Target | Minimum |
-|--------|--------|---------|
-| Strategie IC | > 0.03 | > 0.02 |
-| Strategie Sharpe | > 1.5 | > 0.5 |
-| Max Drawdown | < 10% | < 15% |
-| Win Rate | > 50% | > 45% |
-| Monthly Return | 1-3% | > 0.5% |
-| Trades/Monat | > 20 | > 10 |
-
-## Notizen
-
-- **Alles in fin_quant Loop**: Keine separaten Skripte mehr (`predix_gen_strategies_real_bt.py`, `predix_smart_strategy_gen.py` deprecated)
-- **Graceful Degradation**: Wenn llama.cpp nicht läuft, skippt Strategy Generation mit klarer Warnung
-- **LLM Parallelisierung**: Max 2 parallele Calls (llama.cpp `--parallel 2`)
-- **Optuna Trials**: Standard 30, kann via CLI überschrieben werden