TPTBusiness bed75b0a95 feat: Fix realistic backtesting (Step 1+2) ...

Step 1 - Evaluierung bekannter Strategien:
- Added 'close' to exec context for existing strategies
- Strategies can now use close.index for signal creation
- MomentumDivergenceZScore evaluates correctly: Sharpe=3.59, DD=-0.22%

Step 2 - Annualisierungsfaktor korrigiert:
- Fixed: sqrt(252*1440/96) → sqrt(252*1440) for 1-min data
- Added minimum 0.1 years to avoid extreme values for short periods
- Linear scaling for <1 year, compound for >=1 year

Test results (MomentumDivergenceZScore):
- Status: accepted
- Sharpe: 3.59 (realistic)
- Max DD: -0.22%
- Win Rate: 49.46%
- Ann Return: 543.75% (linear scaled for 259 min period)

Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>

2026-04-09 13:39:18 +02:00

..

CoSTEER

feat: Fast mode - CoSTEER goes to backtest after 1 iteration

2026-04-04 20:52:39 +02:00

data_science

fix: Add Bandit security scanning and fix critical vulnerabilities

2026-04-03 11:55:05 +02:00

factor_coder

feat: Fix 1min data integration and centralize all prompts

2026-04-04 08:20:58 +02:00

finetune

feat: add LLM-finetune scenario (#1314)

2026-03-02 19:04:10 +08:00

model_coder

chore: initial Predix state (RD-Agent fork + EURUSD setup)

2026-03-22 21:20:02 +01:00

rl

feat: Full system integration - RL + Protections + Backtesting + CLI

2026-04-03 13:53:32 +02:00

optuna_optimizer.py

feat: Strategy Generator working with local LLM (P0-P4)

2026-04-09 12:55:04 +02:00

strategy_orchestrator.py

feat: Fix realistic backtesting (Step 1+2)

2026-04-09 13:39:18 +02:00