Stock Screening with Rising Lows, Amplitude, and Turnover

Summary

This Chinese-language post describes a stock-selection screen using three conditions: amplitude above 1, rising bottoms, and turnover between 3% and 12%. It provides corresponding indicator logic for a Chinese trading platform and a Python example. The Python sketch combines amplitude and turnover checks with a rolling-window condition intended to identify a rising bottom, then orders selected names by percentage change.

The post characterizes the method as a technical screen supplemented by turnover data and notes that delayed turnover data may make selections lag current conditions. It suggests broadening the screen with sentiment, volume, or financial measures, and mentions machine learning as a possible way to adjust indicators. No backtest results, benchmark, precise definition of amplitude, or evidence that the filters improve returns is supplied. The rolling-window example’s bottom comparison is not fully explained, so its implementation should be checked before use.

Key ideas

• The screen requires amplitude above 1, rising bottoms, and turnover within a 3% to 12% band.
• The post offers both platform-specific indicator logic and a Python sketch of the selection conditions.
• The Python example ranks selected stocks by percentage change after applying the filters.
• The author notes that turnover data can introduce selection delays and suggests adding other measures.
• No empirical performance results or benchmark comparison are provided.

Tags

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