Checking Missing Valuation Data in a Chinese Stock Dataset

Summary

This forum post reports a suspected data-quality problem in a Chinese stock valuation dataset. The author observed that the September 14, 2022 snapshot appeared to contain more than 1,600 missing or erroneous records, while the adjacent dates seemed to have only dozens of records without a price-to-earnings value. The post asks for the full date range to be checked for similar anomalies.

To illustrate the issue, it compares the dataset shape and the count of missing trailing-twelve-month PE values for September 13, 14, and 15. This is a basic method for detecting a sudden break in coverage by comparing missing-value counts across neighboring dates. The post does not provide the outcome of the requested audit, identify the cause, or establish whether the apparent gaps affect other fields or dates, so the observation should be treated as an unverified data-quality report.

Key ideas

• The author flags a sharp apparent increase in missing valuation records on September 14, 2022.
• The reported anomaly concerns missing trailing-twelve-month PE values in a Chinese stock dataset.
• Comparing row counts and missing-value counts on neighboring dates is used to surface the suspected gap.
• The post requests an audit across all dates but does not report the audit results or cause.

Tags

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