Joining Chinese Stock Bars, Fundamentals, and Money Flow Data

Summary

This post documents an attempted BigQuant workflow for combining daily Chinese stock bars with prefactor and money-flow tables. The query joins records by date and instrument, selects price and valuation fields, calculates returns, and applies a non-null filter. It then passes the query into a data extraction module for a date range that includes extra history before the requested start. The example illustrates how feature construction and extraction can be arranged in a quantitative research pipeline.

The reported run fails during SQL binding because the money-flow table alias does not contain the requested inflow-rate column. The post supplies the error and query but does not show a corrected field name or a successful run, so it serves mainly as a diagnostic example rather than a working recipe. Researchers applying the pattern need to check the actual schema and available columns in their data environment. The excerpt offers no strategy, backtest, or evidence about the predictive value of the joined features.

Key ideas

• The example joins daily bars, prefactors, and money-flow data on date and instrument.
• It constructs return features and filters rows with missing values.
• The extraction fails because a referenced money-flow column is absent from the table schema.
• The post does not provide a corrected query or validate any trading signal.

Tags

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