A Limit-Up and Turnover Filter for Metaverse Stocks

Summary

This Chinese community post proposes a stock-selection screen for companies classified in the metaverse sector. It selects names that had at least one limit-up session within the previous 25 trading days and whose turnover rate averaged between 2% and 9% over that period. The stated rationale is to find stocks with recent strong price action and a moderate level of trading activity. The post gives formula references and a Python-style implementation that evaluates recent limit-up events and average turnover, then sorts candidates by market capitalization.

The author acknowledges that the turnover band is subjective, sector conditions can change, and selected stocks may still involve information asymmetry or difficult trading behavior. Suggested refinements include using average turnover, adding fundamental measures such as profitability or industry position, and considering other price and volume indicators. The post provides no backtest results, benchmark, or evidence that the screen predicts returns. Its selection rationale is therefore a hypothesis, and the code and formulas may require validation against the data definitions and trading rules of the chosen platform.

Key ideas

• The screen looks for metaverse stocks with a limit-up event during the prior 25 trading days and average turnover between 2% and 9%.
• The stated rationale combines recent price strength with a bounded level of trading activity.
• The post supplies formula and code references, but does not report backtest performance or comparative evidence.
• Turnover thresholds are subjective, and sector conditions or stock-specific risks may affect results.
• Proposed extensions include fundamental filters and additional price or volume indicators.

Tags

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