Selecting Metaverse Stocks by Auction Turnover Rank and Recent Highs

Summary

This proposed equity screen focuses on stocks classified in the metaverse industry. It ranks candidates by the day’s auction amount, retains those among the top five, and combines that ranking with a recent price-high condition. The article first describes a two-day high, then revises its recommended logic to use a five-day highest-close condition. It provides platform expressions and a Python reference, but no historical test, transaction analysis, or evidence of returns.

The author notes that a short price window may be unreliable and that the industry restriction can leave a narrow candidate pool. Suggested refinements include lengthening the price window, adding technical indicators, and broadening related industry keywords. The implementation details are inconsistent: the sample code’s ranking and price fields do not clearly reproduce the stated auction-amount and high-price rules, and the article shifts between two-day and five-day definitions. The method is therefore best read as a screening idea whose definitions would need checking before evaluation.

Key ideas

• The screen restricts candidates to metaverse industry stocks and ranks them by auction amount.
• It selects the top five ranked stocks and adds a recent-high condition.
• The article changes the proposed high window from two days to five days.
• The sample code and described ranking conditions are not fully consistent.
• No backtest or performance evidence is provided, and the author flags narrow coverage and short horizons as risks.

Tags

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