mirror of
https://github.com/NicolasBohn/NexQuant.git
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TPTBusiness
4c45ba33ab
Implemented realistic backtesting: - Load real OHLCV close prices from intraday_pv.h5 - Calculate real price returns (pct_change) - Apply signal positions to real returns with proper alignment - Include spread costs (1.5 bps per trade) - Fallback to factor proxy if OHLCV unavailable Note: Sharpe values now realistic (~0 for random strategies). Strategies need LLM to select predictive factors for positive Sharpe. Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
116 lines
1.4 KiB
Plaintext
116 lines
1.4 KiB
Plaintext
# Environment
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.env
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.env.*
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!.env.example
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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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# Virtual environments
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venv/
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ENV/
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env/
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.venv/
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# IDE
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.idea/
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.vscode/
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*.swp
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*.swo
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*~
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# Testing
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.pytest_cache/
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.coverage
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htmlcov/
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.tox/
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.nox/
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# Logs
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*.log
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log/
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# Cache
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pickle_cache/
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prompt_cache.db
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.cache/
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# Generated/processed data
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git_ignore_folder/
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data_raw/
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# Build artifacts
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*.manifest
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*.spec
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# Local scripts (generated)
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convert_1min.py
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import_1min_qlib.py
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# Results (Backtesting, Factors, Runs)
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results/
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*.db
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*.csv
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*_export.json
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*.h5
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# Documentation (generated)
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QWEN.md
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# AI Agent Files (generated by Qwen Code)
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.qwen/
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# Parallel run workspaces (isolated per run)
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RD-Agent_workspace_run*/
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# Internal documentation (not for public)
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TODO.md
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# Private prompts (your improved versions)
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prompts/local/
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*.local.yaml
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*_private.yaml
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# Private models (your improved versions)
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models/local/
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*.local.py
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*_private.py
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# Test credentials
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.env.test
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*.test.env
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test_credentials.py
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# Closed source local components
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rdagent/scenarios/qlib/local/
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docs/COMPLETE_WORKFLOW.md
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# Local scripts (not for public)
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predix_quick_daytrading.py
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predix_smart_strategy_gen.py
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test/backtesting/test_smart_strategy_gen.py
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docs/SMART_STRATEGY_GEN.md
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# OpenACP local workspace (contains secrets)
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.openacp
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CLAUDE.md
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