Stock Screening with Turnover, Trade Flow, and Bollinger Bands

Summary

This post describes a stock screen combining trading activity with a price-location filter. It selects shares with turnover between 3% and 12%, an outside-to-inside trading volume ratio above 1.3, and a closing price between the middle and upper Bollinger Bands. It offers both a database-style formula and a Python example using 20-period bands with two standard deviations.

The post explains the intended interpretation: turnover and the volume ratio are used as signs of trading interest, while Bollinger Bands help characterize price movement. It gives no backtest, sample definition, or performance evidence. It also warns that the screen may exclude other worthwhile stocks and remain vulnerable to market fluctuations, suggesting financial data and fundamental analysis as possible additions. The examples have a boundary inconsistency: the prose uses inclusive turnover limits, while the Python conditions are strict.

Key ideas

• The screen requires turnover from 3% to 12%, an outside-to-inside volume ratio above 1.3, and a close between the middle and upper Bollinger Bands.
• The code example calculates 20-period Bollinger Bands using two standard deviations.
• The post provides no performance test to establish whether the selection rules generate returns.
• The author notes that market swings and omitted fundamental information limit the screen.

Tags

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