Screening Metaverse Stocks with Institutional Flow and Moving Averages

Summary

This Chinese-language post outlines a stock screen combining three conditions: membership in the metaverse theme, a positive institutional-flow measure, and a rising or diverging moving-average signal. It gives formula references and a Python example that attempts to collect stock lists, money-flow data, and daily prices, then filter candidates. The strategy is framed as a way to combine a thematic selection with a flow measure and a technical trend condition.

The post does not provide a backtest, performance figures, or evidence that the screen predicts returns. It acknowledges that industry exposure can miss broader sector moves, that one flow measure may not capture the full market, and that a moving-average condition does not ensure an upward trend. The formula and code descriptions are not fully aligned on the moving-average condition, so implementation details should be checked carefully before use. Suggested extensions include broader market and fundamental filters and explicit risk controls.

Key ideas

• The screen combines metaverse-themed stocks, positive institutional-flow readings, and a moving-average condition.
• The post provides formula references and a Python example for assembling candidate stocks.
• The source gives no measured performance or backtest evidence for the screen.
• The author identifies theme concentration, incomplete flow information, and unreliable trend signals as risks.
• The moving-average logic differs between parts of the post and requires careful verification.

Tags

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