Chinese Stock Screening with Metaverse, Auction Flows, and Turnover

Summary

This Chinese stock-screening example combines three filters: membership in the metaverse theme, positive net buying by large traders during the opening auction, and turnover between 2% and 9%. It presents the approach as a way to find stocks with activity and buying interest while avoiding the highest-turnover names. The article also shows indicator-formula and Python examples for applying the filters and selecting candidates.

The document provides no backtest results or performance evidence. Its explanation of risk is general: market data may be imprecise or stale, and capital-flow signals can mislead. The sample code’s data fields and calculations may not faithfully implement the stated auction-flow and turnover definitions, so the screening logic would need validation against the intended data source before use. The article suggests combining the screen with other analysis and adjusting it as market conditions change.

Key ideas

• The screen limits candidates to stocks in the metaverse theme.
• It requires positive net buying by large traders during the opening auction.
• It keeps stocks with turnover between 2% and 9%.
• The article supplies example formulas and Python code but reports no tested performance.
• Flow and market-data signals can be unreliable, so the screen needs further analysis.

Tags

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