Selecting Metaverse Stocks by Institutional Flow and Auction Buying

Summary

This post describes a Chinese equity screen for metaverse-related stocks. It combines a positive institutional-flow measure with positive net buying attributed to major participants during the opening auction. The proposed selection rule is intended to identify stocks where both institutional activity and auction demand are favorable.

The post gives indicator references and example Python code, but the implementation does not clearly match every stated condition: it uses company-name filtering as a proxy for industry membership and block-trade volume as a proxy for auction net buying. It reports no backtest results or performance evidence. The author flags the sector’s early development and unstable prices, the lag in institutional-flow data, and the volatility of auction activity. Suggested refinements include adding technical indicators, adjusting condition weights, and considering company and industry fundamentals.

Key ideas

• The screen selects metaverse-related stocks with positive institutional-flow readings and positive auction net buying.
• The post provides indicator references and sample data-processing logic.
• The sample implementation uses proxies that may not correspond exactly to the stated industry and auction conditions.
• The author identifies sector volatility, delayed institutional data, and unstable auction activity as risks.
• Possible refinements include technical indicators, condition weighting, and fundamental analysis.

Tags

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