Combining Metaverse Theme, Turnover, Valuation, and ROE Stock Screens

Summary

The document outlines a Chinese A-share stock screen centered on a metaverse industry classification, elevated recent turnover, share prices above a stated threshold, larger market capitalization, and return on equity. It first presents a simpler theme, turnover, and price filter, then proposes adding market-cap and ROE criteria to account for company scale and profitability. It provides example screening expressions and a Python-style workflow, followed by a suggestion to rank selected stocks by recent percentage change and retain a subset.

The article cautions that a price cutoff can exclude otherwise relevant companies and that price-based filters omit fundamental and market-context risks. Its implementation details also need scrutiny: the turnover expression compares a value with its prior observation, which may not directly represent turnover exceeding a fixed percentage; the ROE condition measures a change in ROE rather than ROE being above the stated level. The document supplies no backtest results, data-quality checks, or evidence that the proposed filters predict returns.

Key ideas

• The screen targets stocks classified in the metaverse theme and applies recent activity and price filters.
• The proposed refinement adds market capitalization and profitability criteria.
• The example workflow ranks screened stocks by recent price change and selects a portion of the results.
• The turnover formula compares a current value with its prior value and may not match the stated fixed turnover threshold.
• The ROE formula measures change in ROE rather than directly testing whether ROE exceeds the stated level.
• No backtest or evidence of predictive performance is included.

Tags

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