MACD Momentum and Beverage Trade Data for A-Share Selection

Summary

This post outlines a daily, after-close stock screen combining positive MACD conditions with beverage import and export data, then ranking qualifying shares by market attention. Its rationale is that MACD may indicate upward momentum, while attention and trade flows could point to investor interest and consumer demand. The example formula uses the relationship between imported and exported goods data, and the Python sketch additionally checks that the MACD signal difference is rising before sorting by heat and signal change.

The post gives no backtest, performance figures, or evidence that these inputs predict returns. It flags that import-export data can shift with policy and market conditions, and that the screen omits company fundamentals and intraday price action. The implementation details also do not fully align: the prose specifies a beverage-related universe and MACD above zero, while the code uses particular indicator changes and field names whose definitions and availability are not established. Treat it as a screening concept requiring data validation and testing, not a demonstrated strategy.

Key ideas

• The screen combines positive MACD conditions with beverage import-export data.
• Qualifying stocks are ranked by individual-stock attention after each trading day.
• The example code adds a rising MACD signal difference as a filter.
• The post provides no performance evidence and warns that trade data and omitted fundamentals create uncertainty.

Tags

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