Screening Chinese Equities by Turnover, Ten-Day Return, and Metaverse Theme

Summary

This document describes a Chinese equity screen that selects stocks with turnover between 3% and 12%, a positive ten-day gain below 35%, and an association with the metaverse theme. It presents the filters as a way to combine trading activity, recent price direction, and a thematic classification. It also suggests researching the theme’s technologies, applications, products, and ecosystem, then adding industry risk controls.

The article includes formula and Python examples, but they are references rather than a validated backtest. The Python sample uses a particular historical date range and data fields, and its operational definitions and conditions do not consistently match the stated screen; for example, its return and turnover boundaries are inclusive. The text gives no performance evidence, transaction-cost analysis, or portfolio rules. It warns that the theme is immature and subject to uncertain market conditions, changing definitions, sentiment, and policy, so the screen should be treated as a candidate-generation idea rather than evidence of an effective strategy.

Key ideas

• The screen combines moderate turnover, positive ten-day performance, and a metaverse theme classification.
• The article proposes further industry research and explicit controls for theme-related risk.
• The sample implementation uses historical market data but does not establish out-of-sample performance.
• The code’s conditions differ in places from the written screening rules.
• Thematic classifications can be ambiguous and sensitive to sentiment and policy changes.

Tags

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