Trend-Shape Stock Selection Using Pullback, Volume, and Regression Filters

Summary

This brief strategy proposal starts with the constituents of the CSI 300 and looks for stocks whose latest price remains within an 8% pullback from the highest price of the past 30 days. It also compares average trading volume over the latest seven sessions with the average over roughly 200 sessions, requiring the recent measure to be no more than 160% of the longer-term measure.

A further proposed filter fits a linear regression, expressed as price against time, to historical stock prices. The author suggests using its slope and intercept, along with a measure of price fluctuation, and restricting those values to chosen ranges. This is presented as a way to quantify trend shape, but the post does not specify those ranges, define the fluctuation measure, explain entry or exit rules, or report any backtest. The method is therefore an incomplete screening concept rather than a reproducible trading system; its thresholds and behavior across market conditions remain unevaluated.

Key ideas

• The proposed universe is the CSI 300.
• Candidates must be within an 8% pullback from their 30-day high.
• Recent seven-session average volume is capped relative to the roughly 200-session average.
• The author proposes filtering a price-time regression by slope, intercept, and price fluctuation, but leaves the bounds undefined.

Tags

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