Combining MACD, Company Profitability, and Auction Activity for Stock Selection

Summary

The proposed stock screen combines a positive MACD reading, a profitability-based company filter, and ranking by current auction trading activity, selecting five stocks. The accompanying Python example approximates the company-quality screen using recent income data: it removes firms with negative net profit margins or operating revenue, ranks the remaining names by a volume-price measure, and then checks whether MACD is positive. The text also provides a formula reference for the MACD and company-type conditions.

The article offers no backtest, performance statistics, or evidence that the screen improves returns. Its explanation acknowledges that MACD is only one technical indicator, auction values can change quickly, and acceptable profitability does not rule out financial or industry risks. The implementation details also leave timing and data alignment questions, including the use of prior-day MACD alongside a current-day auction ranking. The screen is best understood as a proposed selection rule, not a validated strategy.

Key ideas

• The screen selects five stocks using positive MACD, a profitability filter, and auction activity ranking.
• The example treats negative net profit margin or operating revenue as grounds for excluding a company.
• The document warns that MACD and auction activity can each produce unreliable selections.
• No backtest or return evidence is provided, and timing alignment between inputs is not fully explained.

Tags

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