Metaverse Stock Screening by Turnover and Institutional Ownership

Summary

This post outlines a China A-share screening rule for stocks classified in the metaverse sector. It first describes selecting names with prior-day turnover above a threshold and positive institutional activity, then gives a final rule using prior-day turnover above eight percent and institutional ownership above five percent. It also includes example references to sector classification, turnover, and ownership fields, plus a Python sketch that retrieves sector members and filters them using daily market and holder data.

The post flags meaningful limitations: the screen uses only a small set of inputs, institutional data may be delayed or inaccurate, and the approach may overfit. It suggests adding technical or fundamental variables, or using better institutional flow data, but supplies no backtest, performance evidence, or validation of the sample implementation. The initial and final descriptions also differ on the institutional criterion, so the final ownership threshold should be treated as the stated rule rather than evidence that the screen is profitable.

Key ideas

• The final screening rule combines metaverse sector membership, prior-day turnover above eight percent, and institutional ownership above five percent.\nThe post gives example data fields and a Python outline for applying the filter to sector constituents.\nIt warns that the limited inputs may create overfitting and that institutional data can be delayed or inaccurate.\nNo backtest or performance evidence is provided, and the post's initial institutional activity condition differs from its final ownership filter.

Tags

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