Metaverse Stock Screening with Moving Averages and Auction Turnover

Summary

This post proposes screening stocks in the metaverse industry using two conditions: price or average price above a five-day moving average, and prior-day auction turnover above 0.26. It interprets the moving-average condition as a short-term upward trend and auction turnover as a sign of market attention. The document includes indicator-formula and Python examples, though the implementation details are not fully aligned with the written rule: one formula uses a moving-average comparison and a turnover condition in the opposite direction, while the Python example compares closing price with the moving average and uses a volume-to-amount calculation.

No backtest results, returns, or benchmark comparisons are provided. The post acknowledges that the screen uses few signals, emphasizes short-term activity, and may mistake heavy turnover for bullish demand. It suggests adding technical and fundamental measures, but gives no tested combination or evidence that this improves outcomes. The industry classification, auction-turnover definition, thresholds, and code behavior would need verification before the screen could be reproduced reliably.

Key ideas

• The proposed screen targets metaverse-related stocks with price above a five-day moving average.
• It also uses prior-day auction turnover above 0.26 as an activity filter.
• The formula examples conflict with the written turnover threshold and should be reconciled.
• The post warns that high turnover can reflect trading activity without predicting gains.
• No backtest or performance evidence is reported.

Tags

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