Chinese Stock Screen Combining Turnover, Order Flow, and Auction Signals

Summary

This stock selection method filters for turnover between three and twelve percent, a positive relationship between price change and net super-large-order flow, and positive auction-related buying conditions. Its stated rationale is to favor liquid stocks receiving institutional attention and to use opening auction information to screen for strength. Formula and Python examples describe volume, turnover, order flow, auction variables, and a ranking by a weight based on average turnover and volume relative to price.

The author notes that the screen lacks fundamental analysis and may be sensitive to market sentiment; auction and unusually large-order signals are also characterized as risky. Suggested refinements include adding technical indicators and adapting risk controls to market conditions. The post gives no backtest, performance statistics, or evidence that the proposed filters improve returns, and the prose and example code do not map perfectly onto one another.

Key ideas

• The screen uses a three-to-twelve percent turnover band and positive price-change and large-order-flow conditions.
• Auction-period buying measures and a large-order threshold further restrict the eligible stocks.
• The Python example ranks qualifying names using a volume and turnover based weight.
• The method omits fundamental analysis and may be vulnerable to sentiment shifts and auction-related risk.
• No backtest results are reported, and the text and code have some implementation differences.

Tags

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