A-Share Stock Screen Using Volatility, Convertible Bonds, and Valuation

Summary

The document describes an A-share stock screen that combines price amplitude, an outstanding convertible-bond name field, and valuation filters. It first discusses positive price-to-earnings as a profitability condition, then revises the proposed final screen to use price-to-book below a stated threshold. The referenced formula also includes turnover and excludes certain security codes, while the Python example filters listed stocks and checks financial and daily price data.

The author cautions that price-to-earnings is a static measure and may vary in usefulness across industries and accounting practices. Suggested improvements include adding valuation, company performance, and industry context, with dynamic measures such as PEG and ROE. The post provides formulas and sample code but no backtest results or evidence that the screen predicts returns. The prose and code differ in details, including use of a positive earnings check in the implementation, so the screening conditions should be reconciled before use.

Key ideas

• The proposed screen combines price amplitude with convertible-bond and valuation conditions.
• The final stated logic favors a price-to-book filter after noting limitations of price-to-earnings comparisons.
• The reference formula also applies turnover and security-code conditions.
• The Python example retrieves financial and daily data to filter candidate stocks.
• The document gives no backtest evidence, and its prose and implementation do not align fully.

Tags

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