Metaverse Stock Screening with Turnover, Afternoon Flows, and Size

Summary

This Chinese-language post outlines an A-share screening idea focused on metaverse stocks. Its initial filters are prior-day turnover above 8% and a measure intended to identify afternoon large-order net inflows. The author discusses dependence on trading-volume data and warns that afternoon buying does not guarantee a rising price. The proposed refinement adds a market-cap ranking filter, alongside suggestions to consider financial data and indicators such as relative strength or moving averages.

The post includes example formula and Python implementations, but the two descriptions are not fully aligned: the Python example adds a recent price-change condition and appears to use circulating market capitalization, while the stated final screen describes a market-cap threshold. No backtest results or performance evidence are supplied. The strategy is therefore a screening hypothesis whose data definitions and implementation need validation before use; flow and turnover signals may be noisy and can omit other relevant company or market information.

Key ideas

• The screen targets metaverse stocks with prior-day turnover above 8% and afternoon net buying activity.
• The proposed final logic adds a market-cap ranking constraint.
• The post suggests combining volume-based signals with financial measures and technical indicators.
• Large-order inflow is not sufficient evidence of a sustained price advance.
• The example implementations differ in some conditions and require careful validation.

Tags

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