Building a Baostock Workflow for Historical Data and Research

Summary

The document outlines a workflow for using Baostock as a source of historical Chinese equity data. It recommends downloading a broad stock and index universe, storing adjusted daily bars locally, and retrieving intraday bars only for the dates needed. For financial statements, it proposes batching requests and saving results for later use. The suggested storage and research setup uses columnar files for daily and financial data, a local query engine, and a separate format for minute bars.

For data quality and research, the article suggests comparing daily prices across providers, flagging discrepancies, and deriving technical features from the downloaded fields. It also describes connecting the data to backtesting and trading systems, and mentions convertible-bond histories, adjustment factors, and trading calendars. The evidence consists of implementation examples and reported download and storage figures, not a controlled performance or reliability study. API rate limits, provider differences, data freshness, and the accuracy of the examples may constrain use; the article itself acknowledges the need for another source for real-time ticks.

Key ideas

• Download historical data in batches and cache it locally for repeated research.
• Request minute bars only for the periods required, since the article describes API rate limits.
• Compare data across providers to detect discrepancies before relying on it.
• Use local storage and query tools to organize daily, financial, and intraday datasets.
• Treat the suggested workflow as a data-engineering guide rather than evidence of a profitable strategy.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.