A-Share Quantitative Analysis Toolkit
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Install @user_ff4d9420/astockdataquant by following https://skillhub.cn/install/skillhub.md.
About this skill
Problems It Solves
Financial research is often blocked less by models than by data plumbing: A-share quotes, fundamentals, macro releases, and event disclosures live in different endpoints, while HK equities, futures, options, and bonds each have their own conventions. It also makes "latest value" answers fragile when historical numbers, fiscal-year quarters, and cross-market trading hours get mixed together. This skill turns those issues into a routing discipline: classify the request as data retrieval, methodology, or report output, then select the preferred implementation for each data domain instead of pulling the same metric through multiple competing paths.
How It Works
- A-share data engine: uses
bin/quant.pyfor core A-share workflows, including real-time quotes, K-lines, quantitative screening,fundamentals, capital flow, longhu lists, and sector heat. - Multi-market data layer: uses
bin/cn/equity.py,bin/cn/futures.py,bin/cn/options.py,bin/cn/macro.py, andbin/cn/research.pyfor HK equities, futures, options, macro data, and company events such as earnings forecasts, lockup expiry, insider trades, buybacks, dividends, and IPO calendars. - Research workflows: provides templates in
references/research-workflows/for annual-report reading, comparable-company analysis, deep dives, earnings reviews, field notes, industry research, morning briefings, and research digests. - Research and output constraints: prioritizes retrieval over memory, requires source and timestamp for key figures, enforces a fixed disclaimer when trade-related advice appears, and favors existing methodology references plus
scripts/for technical signals, quant strategies, and IB validation utilities.
Boundaries
This is better suited for financial data retrieval, research structuring, and report drafting than for live order execution. Some optional data sources must be confirmed before use, and cross-source metrics may differ in definition; outputs should state the source, reporting period, and cutoff time.
Use Cases
- Before morning research, aggregate A-share earnings forecasts, lockups, and insider trades into structured notes.
- While drafting a stock deep dive, verify financial statements, valuation metrics, and comparable multiples.
- When tracking macro and liquidity, retrieve CPI, PMI, financing, northbound flows, and sector heat.
- Turn annual reports or field notes into earnings reviews, morning briefings, or research digests.
Best For
- Buy-side or brokerage researchers: organize A-share quotes, financials, and disclosure events into report workflows.
- Quant strategy engineers: run the A-share data engine and existing quant scripts for backtesting or screening.
- Macro and industry analysts: retrieve macro indicators, northbound flows, sector heat, and policy-to-theme mappings.
- Investment banking analysts: use DCF Excel checks and figure-consistency utilities to prepare deal materials.
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