Screening Stocks by Turnover, Large-Order Flow, and Convertible Bonds

Summary

This article presents a stock screen using turnover, price change, large-order net flow, trading volume, and outstanding convertible-bond information. The stated selection logic requires turnover between 3% and 12%, a positive product of price change and large-order net flow, and a nonempty convertible-bond name. The examples also impose a volume threshold and rank candidates, though the platform formula and Python example express parts of the logic differently.

The article treats convertible-bond information as an additional filter and argues that it may help narrow the candidate list. It supplies sample formula and Python logic, but no backtest, return data, or evidence that the filter improves results. Its caveats include missing fundamental valuation analysis and possible delays in convertible-bond data. It suggests testing parameters and combining the screen with other indicators, while acknowledging overfitting risk. The differences between the written criteria and the code, including the timing and calculation of several fields, mean users should reconcile the definitions and validate data timing before drawing conclusions.

Key ideas

• The stated screen combines a 3%–12% turnover band with positive price-change and large-order-flow interaction.
• It also requires outstanding convertible-bond information and includes a trading-volume condition in its examples.
• The document supplies implementation examples but gives no evidence of historical or live performance.
• It warns that the screen omits fundamental valuation and may use delayed convertible-bond data.
• The written rules and sample implementations differ in field definitions and timing.

Tags

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