initial-d / ml-quant-trading
PyTorch ML quant research: 213 factors, bias correction, portfolio optimization, backtesting, and System-One/Jev-style decisions.
Why this job: works in the areas we cover, but does not say which job it does
What it does
No market-data account or API key is required. The deterministic demo runs the full research pipeline in about 30-90 seconds on a typical CPU-only laptop and writes shareable Markdown and JSON reports under artifacts/small/.
Get started
python -m pip install mlquantx
mlquant demo- Maintenance
- Active
- Last commit 10 days ago
- Stars
- 107
- +3 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.4.1
- Released 28 days ago
- Built with
- Python
- 92% of the code
Is it looked after?
- Contributors
- 3
- Last 90 days
- Issues
- 88% closed
- 3 still open
- Pull requests
- 50 merged
- 0 waiting
- Releases
- 12
- 12 in the last year
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More: languages, topics, project record and preview image
Languages
- Python 92%
- Shell 4%
- C++ 2%
- Jupyter Notebook 1%
Topics
- a-shares
- ai-agents
- algorithmic-trading
- alpha-factors
- backtesting
- china-stock-market
- cross-sectional
- deepseek-harness
- factor-investing
- jev
- machine-learning
- multi-factor-model
Project record
- JobOther AI tools
- StatusListed
- Commits302
- Forks40
- Watching4
- Stars in 28 days+16
- CreatedJun 5, 2025
- First seen by usNov 7, 2026
- CheckedNov 7, 2026