A Metaverse Stock Screen Using a Long-Term Average and Turnover

Summary

The document outlines an equity screening rule for stocks in the metaverse theme. It selects names whose previous-day price is above the 250-day moving average and whose turnover rate falls between 3% and 12%. The accompanying explanation treats the thematic classification as a way to target a popular sector, the moving-average condition as a long-term price filter, and the turnover range as a filter for intermediate trading activity.

It provides formula references and a Python example intended to retrieve constituent stocks and apply the conditions. The post also flags broad market and company-reporting risks, and notes that turnover can lag. It suggests adding valuation measures and reviewing fundamentals, but presents no backtest, return evidence, or detailed portfolio and execution rules. The code example’s data fields and conditions are not independently validated in the document, so the screen should be treated as a stated selection idea rather than a tested strategy.

Key ideas

• The screen targets metaverse stocks above their 250-day moving average.
• It requires turnover to lie between 3% and 12%.
• The post frames the moving average as a long-term price filter and turnover as an activity filter.
• It identifies market, company-reporting, and turnover-lag risks.
• No backtest evidence or complete portfolio and execution rules are provided.

Tags

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