Metaverse Stock Screening with Auction Ranking and a Weekly Moving Average Cross

Summary

This Chinese stock-selection example screens companies in the metaverse industry using two conditions: ranking among the day’s top five by auction amount and a weekly price cross above the 30-week moving average. It describes the approach as a way to combine recent market activity with a trend signal, then lists risks such as narrow industry coverage, reliance on technical indicators, and omission of company fundamentals.

The document gives platform-specific screening logic and a Python example intended to retrieve stock data and apply a moving-average test. However, the sample’s implementation appears inconsistent with the stated method: it uses close prices where auction amounts are needed, refers to an undefined score, and its cross condition may not correctly identify an upward cross. It provides no backtest results or evidence that the selection rules are profitable. The screen should therefore be treated as an outline rather than a validated trading strategy.

Key ideas

• The screen focuses on metaverse stocks and ranks candidates by the day’s auction amount.
• A weekly price cross above the 30-week moving average is used as a trend filter.
• The document flags narrow industry coverage and the lack of fundamental analysis as risks.
• Its sample code has apparent inconsistencies and does not provide evidence of strategy performance.

Tags

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