Screening Metaverse Stocks by Recent Rankings and Moving Averages

Summary

This Chinese-language post outlines a short-term A-share screening rule. It selects stocks classified in the metaverse theme that appeared on the previous day’s trading rankings, then applies a five-day moving-average condition. The post offers formula and Python examples for retrieving market and historical data, as well as a note that the rule can be implemented in stock-screening software.

The source describes the setup as requiring the stock’s average price to be above its five-day average, while its formula and sample code use moving-average comparisons that are not fully consistent with that wording. It provides no backtest results or evidence of returns. The author cautions that the screen relies on a narrow set of short-term signals and may miss other relevant financial or technical information; suggested additions include valuation, leverage, profitability, and explicit stop-loss or profit-taking rules.

Key ideas

• The screen combines a metaverse industry classification with a previous-day trading-rank appearance.
• A five-day moving-average condition is used to filter candidate stocks.
• The prose description and the supplied formulas do not express the moving-average condition consistently.
• The post provides implementation examples but no measured performance evidence.
• The author flags the narrow signal set and suggests broader financial checks and risk controls.

Tags

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