A Metaverse Stock Screen Using Long-Term Trend and Auction Volume

Summary

This post proposes screening Chinese stocks associated with the metaverse theme using a long-term price trend condition and an activity measure combining the prior session’s turnover rate with the current opening auction volume relative to prior volume. It includes a Python example that retrieves constituent stocks, applies price and volume conditions, and filters out ST-designated companies and newer listings. The stated intent is to select candidates for investment, not to define a complete portfolio or execution plan.

The description contains an important inconsistency: its initial logic refers to the prior close above a 250-day moving average, while the later summary and sample code use a five-day average. The turnover and auction-volume ratio is presented as a simple proxy, and the post itself acknowledges that this may not capture market activity fully. It suggests adding other volume, technical, and fundamental measures, but gives no backtest, benchmark comparison, or evidence of returns. The screen is therefore an example hypothesis whose exact trend condition needs clarification and whose results require testing.

Key ideas

• The proposed screen combines a metaverse theme filter, a moving-average price condition, and an auction-volume ratio.
• The post conflicts between a 250-day moving average condition and a five-day average in its later description and code.
• The sample code also applies listing-age and ST-stock filters.
• The author describes the turnover-volume ratio as an incomplete measure of activity.
• No backtest or return evidence is provided, so the screen remains an unvalidated selection idea.

Tags

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