Metaverse Stock Screen Using Turnover, Large-Order Flow, and Rankings

Summary

This Chinese-language note proposes screening metaverse-related A-share stocks using prior-day turnover above 8% and large-order net volume above 0.05 for at least three consecutive days. It then adds a ranking filter: a stock may qualify if it ranks in the top 30% by market capitalization or by its recent 30-day gain. The article supplies corresponding screening expressions and illustrative Python selection logic, framing the setup as a way to combine trading activity and money-flow signals with a relative size or momentum condition.

The author cautions that large-order net volume depends on how order size and net flow are defined, and that the signal can misclassify activity or arrive too late. Positive large-order flow does not ensure future gains. The sample Python approach also uses dated data and a three-observation average, which may not exactly implement the stated consecutive-day threshold. No backtest results, transaction costs, or risk controls are provided, so the screen should be independently validated before use.

Key ideas

• The screen starts with metaverse stocks whose previous-day turnover exceeds 8%.
• It requires large-order net volume above 0.05 for at least three consecutive days.
• A market-cap ranking or recent-return ranking condition is added as an alternative filter.
• The author warns that large-order measures are subjective and may not predict future performance.
• The article gives sample screening logic but no backtest evidence or transaction-cost analysis.

Tags

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