BaiQuant-public
Unverified ML strategy on Indices by bkidy. BotFinder score 18 out of 100.
OpenAI Codex + GPT-5.5 assisted A-share quantitative finance research toolkit using Harness-style backtesting, stock selection, paper trading, and risk review
Source: github
BotFinder analysis pending.
BaiQuant-public
BaiQuant English README | 中文故事版 / Codex Series 01 OpenAI Codex + GPT-5.5 assisted A-share quantitative finance research toolkit for after-close stock selection, backtesting, paper replay, and manual trading review. Case study: I gave an A-share account to Codex and doubled it in one month BaiQuant turns a daily A-share research routine into reproducible code: pull local data, rank candidates, review risk, record real fills, and learn from the next session. | | | | --- | --- | | Built with | OpenAI Codex + GPT-5.5 | | Research style | Harness-style loop: idea -> rule -> code -> test -> backtest -> review | | Market focus | China A-share equities | | Public strategy | steady-20d | | Operating mode | after-close plan, next-session manual execution | | Data stance | bring your own data; no proprietary market data is shipped | BaiQuant is research infrastructure, not investment advice. It is designed for individual researchers who want a local, inspectable workflow for A-share stock selection, strategy experiments, and manual trading review. What It Does - Builds a local A-share research
⚠ No verified equity curve — no track-record source connected.
Drawdown profile
Data unavailable — contact the owner.
Verification ledger
How the score has moved
Recalculated at each data collection. Transparency means showing the bad weeks too.
No score history is stored yet — only the current score is shown.
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⚠ No live verification account connected — ask for proof before buying.
Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)