Metaverse Stock Screening with a Long-Term Moving Average

Summary

The post outlines a Chinese equity screen for stocks in the metaverse concept group whose price is above a long-term moving average, then ranks candidates by individual-stock popularity. It describes the moving-average condition as a way to identify prices above a long-term reference level and acknowledges that sentiment-led selection can overlook company fundamentals. It suggests adding financial quality measures or technical indicators, though it does not specify how to combine them.

The post includes formula and Python examples, but the implementation does not clearly match the stated ranking rule: it sorts by price-to-earnings value rather than popularity. Its written formula also uses the current close despite describing yesterday’s price. No backtest results, return data, or validation of the screening logic are supplied. Treat the screen as a sketch whose timing, ranking variable, universe definition, and trading rules need to be clarified before evaluation.

Key ideas

• The screen selects metaverse-related Chinese stocks trading above a long-term moving average.
• The stated ranking criterion is stock popularity, although the code ranks by price-to-earnings value.
• The post warns that a sentiment-heavy screen may neglect company fundamentals.
• It provides no performance evidence, and its written timing and code are not fully consistent.

Tags

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