Diagnosing Misaligned Shift Features After a Left Join

Summary

This forum report describes a suspected data-alignment problem in a Chinese equity research workflow. The author adds an opening-price feature and a forward-shifted version to a strategy, then finds that the shifted values appear incorrect on particular dates in the output of a later module. A direct connection between two modules reportedly produces correct values, leading the author to suspect that an intermediate left join changes how the derived feature is aligned.

The report provides a reproduction outline: add the features, set a date range and instrument, run the workflow, and inspect the resulting rows. It does not include a confirmed diagnosis, a fix, or a general explanation of how the join behaves. Its practical lesson is to verify time-series feature values after joins and intermediate transformations, especially for shifted data. The described issue is platform-specific and should be treated as a debugging lead, not proof that left joins generally corrupt features.

Key ideas

• The report investigates shifted price features that appear incorrect after an intermediate left join.
• A direct module connection reportedly gives different results from the workflow that includes the suspected join.
• The author offers a reproducible sequence and date-based inspection of the affected output.
• The post does not establish a root cause or provide a fix.
• Time-series features should be checked after joins and other data transformations.

Tags

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