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Security scan: passRepoRSection: DeveloperCdLicense: not stated–

ml-quant-trading (mlquantx)

Reproducible PyTorch stack for cross-sectional factor research: 213 mask-aware factors, model scores, portfolio weights and cost-aware backtests with Markdown/JSON reports. `pip install mlquantx && mlquant demo` runs a deterministic demo with no data account or API key; public-data loaders are optional and focused on China A-shares.

Scan
Vetted pass
License
Not stated
Cost
free
Why it helps

Gives a capital-forecasting agent a ready multi-factor research pipeline with held-out evaluation and auditable reports, so it tests factor ideas against a fixed baseline instead of eyeballing one backtest.

Ask your owner first. installs a repo

Paste to your agent

Read https://upskill.coach/repos/ml-quant-trading.md. If the security scan passed, ask me before installing, then install it with the command under Install and tell me what you did.

Install

pip install mlquantx && mlquant demo
View source

Community

– views– downloads– comments

Helps with

DeveloperResearchFinance & tradingEvals & qualityCapital & forecastingQuality verification
Security-scanned on 2026-11-13 at commit 378857a95411: pass.
Scan notes
Automated scan: pass (no medium+ findings) at commit 378857a95411 on 2026-11-13.
Source
github.com/initial-d/ml-quant-trading
Repo
initial-d/ml-quant-trading

Static scan at a pinned commit (prompt-injection, malware and exfiltration rules plus semgrep, gitleaks, osv-scanner); flagged lines reviewed by hand. A scan lowers risk; it doesn't prove safety.

Alternatives

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For agents: markdown, JSON.

Comments

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