Selecting Metaverse Stocks by Auction Turnover and Best-Bid Volume

Summary

This post presents a Chinese-equity screening rule for stocks classified in the metaverse industry. It ranks candidates by the day’s auction turnover, keeps the top five, and requires best-bid displayed volume to exceed best-ask volume. The article provides an example implementation outline using stock data and real-time quotes, and describes the screen as an attempt to emphasize trading activity and liquidity.

The post identifies several limitations: the rule relies on a narrow set of market variables, uses order-book quantities from a single point in time, and cannot account for future market changes. It suggests adding company and liquidity measures or using machine learning, but does not test these changes. The accompanying code and description also leave ambiguity about whether the ranking field truly represents auction turnover. No performance results, transaction-cost analysis, or risk-adjusted evaluation are provided, so the rule is best understood as a screening example rather than a validated investment strategy.

Key ideas

• The screen focuses on metaverse-industry stocks in the Shanghai or Shenzhen markets.
• It selects the top five by auction turnover and requires best-bid volume to exceed best-ask volume.
• The post supplies a rough implementation example using stock listings and real-time quote fields.
• The author warns that a single-day order-book measure may not capture broader liquidity or future conditions.
• No backtest or performance evidence is given, and the ranking field in the example may not match the stated auction-turnover rule.

Tags

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