Screening Stocks for Volatility, Ten-Day Average Proximity, and Afternoon Buying

Summary

The post describes a Chinese stock screen that combines three conditions: daily amplitude above one, an opening price within five percent of the ten-day moving average, and estimated positive net buying during the afternoon. Its rationale is to find volatile shares near a short-term average that also show stronger buying activity later in the session. Formula and Python examples estimate amplitude and moving-average proximity, then compare price-volume activity classified as buying or selling to derive a net-flow signal.

The author warns that the screen omits company fundamentals and that large trades may be followed by selling pressure. Suggested refinements include adding financial and industry measures and applying stronger risk controls. The post provides no backtest, return figures, or evidence that its flow proxy identifies institutional buying. The sample calculations also leave important details unclear, including the intraday data interval and how observations map to individual stocks; the code’s flow calculation may not reliably implement the stated per-stock condition. The criteria should therefore be treated as a rough screening idea requiring data validation and independent testing.

Key ideas

• The screen combines amplitude, opening-price proximity to a ten-day average, and afternoon net buying.
• Its flow proxy classifies price-volume changes as buying or selling activity.
• The post notes that fundamental quality and the risk of large-trader selling are not addressed.
• It recommends adding fundamental filters and tighter risk controls.
• No performance results are presented, and the intraday calculation needs clearer validation.

Tags

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