A-Share Stock Screen Using Metaverse Exposure and Moving Averages

Summary

This post describes a Chinese stock-selection screen that selects companies classified in a metaverse industry group, requires a positive return condition, and filters for a 20-day moving average above the 120-day moving average. It presents the moving-average relationship as a way to identify stocks whose recent price trend is stronger than the longer-term trend. The post also gives formula and Python examples for applying the conditions to a stock universe and sorting selected names by price.

The screen is a simple technical and thematic filter, not a complete investment model. The author notes that it omits company financials and fundamentals and that technical signals can lag or prove unreliable. The suggested improvement is to combine trend and market information with fundamentals and valuation, though no tested combined model or performance results are supplied. The examples therefore describe a screening idea rather than evidence of a profitable strategy.

Key ideas

• The screen combines a metaverse industry classification, a positive return condition, and a rising short-term versus long-term moving-average relationship.
• The 20-day and 120-day averages are used to characterize recent trend relative to a longer horizon.
• The post provides formula and Python examples for filtering a stock list.
• The approach omits company fundamentals and valuation, and its technical signals may lag or fail.
• No backtest results are provided for the proposed screen or its suggested enhancements.

Tags

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