Selecting Metaverse Stocks by Institutional Flow and Circulating Market Value

Summary

This Chinese-language post describes a stock screen that combines metaverse-sector membership, a positive institutional-flow measure, and circulating market value between 5 and 10 billion yuan. It presents the criteria as a way to find moderately sized companies attracting institutional interest, and includes references to platform formulas and Python-based data retrieval. The code uses stock data and money-flow fields to construct a daily list of candidates.

The post identifies several limitations: metaverse companies may be volatile, institutional-flow data can lag, and market value alone omits other relevant company and market factors. It suggests combining the screen with industry and other stock metrics and reviewing it regularly. No backtest results, selection dates, benchmark comparison, or evidence of predictive performance are provided. The implementation’s data fields and sector identification should be checked against the intended provider’s definitions before drawing conclusions from the screen.

Key ideas

• The screen requires metaverse-sector classification, positive institutional-flow readings, and circulating value within a stated range.
• The post illustrates a daily candidate-selection process using Chinese stock data.
• The author notes that flow measures may lag and that sector stocks can be unstable.
• The screen lacks reported performance evidence and omits fundamental and broader market analysis.

Tags

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