Screening Metaverse Stocks with a Long-Term Average and Bollinger Bands

Summary

This stock-selection example screens companies in a Chinese metaverse-related sector using a long-term trend condition and a Bollinger Band price range. The stated rules require price to be above its 250-day moving average and the close to fall between the middle and upper Bollinger Bands. The post also includes reference indicator formulas and a Python example that queries daily data, applies additional listing and exchange filters, and sorts selected stocks by closing price.

The explanation frames the sector membership as a thematic filter, the moving average as a long-term price reference, and the band range as a volatility condition. It provides no backtest results or evidence that these conditions generate excess returns. The author flags dependence on historical prices and the narrow use of one technical indicator, and recommends considering other indicators, financial measures, and risk controls. Implementation details may not align perfectly: the prose refers to yesterday’s price in places, while the final rule and code use current closing data.

Key ideas

• The screen first restricts the universe to stocks associated with the metaverse theme.
• It requires price to be above its 250-day moving average.
• The closing price must lie between the middle and upper Bollinger Bands.
• The post supplies indicator references and an example data-query workflow, but no reported performance evaluation.
• Historical-price dependence and limited indicator coverage are stated weaknesses.

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