Screening Metaverse Stocks by Relative Volume, Momentum, and Valuation

Summary

This Chinese-language post describes a stock screen for the Metaverse sector. It selects shares with a volume ratio above 1.5 and below 6, then ranks candidates by stock popularity. Its proposed final version adds a price-to-earnings ratio below 30. The examples also refer to at least two limit-up sessions within 50 days and a ranking condition based on relative strength or market capitalization, although the prose and code do not align perfectly on every screening detail. Reference implementations are included for a Chinese stock platform and Python using Tushare data.

The post argues that popularity and elevated trading activity may identify widely watched stocks, while warning that a heat-based selection can encourage chasing prices. It suggests adding fundamental measures, and its final screen uses valuation as one such condition. No return series, benchmark comparison, transaction-cost analysis, or out-of-sample results are given. The strategy is specific to Chinese market classifications and data conventions, and inconsistencies between the stated logic and sample code require resolution before implementation.

Key ideas

• The screen focuses on Metaverse-sector stocks with a volume ratio between 1.5 and 6.
• Candidates are ordered by popularity, and the proposed final version adds a price-to-earnings cap of 30.
• The examples also mention limit-up frequency and sector or market-cap ranking conditions.
• The author warns that selecting for popularity can expose investors to chasing overheated shares.
• The post provides code references but no backtest results, and its prose and code contain differences.

Tags

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