A Chinese Stock Screen Using Auction Activity and Price Filters

Summary

This post outlines an A-share stock screen combining a metaverse-sector classification, positive recent returns, and positive auction turnover. It proposes an additional six-month positive-return filter, and later suggests valuation and trend conditions such as price-to-earnings and price-to-book limits, a close above the 20-day average, and rising Bollinger bands. The author interprets turnover as a sign of activity and the price conditions as evidence of short-term strength.

The post provides indicator expressions and example Python, but no backtest, portfolio rules, transaction costs, or performance evidence. It warns that the screen omits broader company fundamentals and that auction turnover can be distorted by speculative activity. The formulas and sample code may not implement every stated condition consistently, so the screen should be treated as a proposal rather than a validated strategy.

Key ideas

• The initial screen selects metaverse stocks with positive returns and positive prior-day auction turnover.
• The proposed refinement adds a positive return over roughly six months.
• The post suggests combining activity and price filters with valuation and trend measures.
• It provides no backtest evidence and cautions that turnover can be misleading.

Tags

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