A Metaverse Stock Screen Using Institutional Flows and Turnover

Summary

This post proposes a Chinese equity screen that selects stocks associated with the metaverse theme, positive institutional flow, and turnover between 2% and 9%. It explains the intended roles of the filters: sector exposure targets a growth theme, institutional activity is treated as a possible directional clue, and turnover is used as a liquidity and trading-activity constraint. It also sketches a data workflow for combining industry labels, flow data, financial information, turnover, and market-cap rankings to produce a candidate list.

The post offers no performance test or empirical evidence that the combined screen earns returns. It acknowledges that industry concentration can miss broader market moves, institutional flows may not represent all trading, and turnover can be driven by speculation. Its example code and criteria are not fully consistent: the prose gives a turnover range in percentage points, while the sample data filter uses decimal thresholds, and several ranking or exclusion steps are unclear. Treat the screen as an unvalidated hypothesis requiring careful data alignment and testing.

Key ideas

• The proposed screen combines metaverse industry exposure, positive institutional flow, and a turnover band.
• The post presents institutional buying as a possible signal, but does not establish predictive performance.
• It sketches a workflow combining industry, flow, financial, turnover, and market-cap data.
• The author flags sector concentration, incomplete flow information, and speculative turnover as risks.
• The example contains ambiguities, including inconsistent turnover units, and provides no backtest evidence.

Tags

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