Sector Momentum and News Filters for A-Share Stock Selection
Summary
The document presents a stock-selection design that first ranks Chinese market sectors using a weighted combination of price momentum, money flows, and recent policy-related news. It then scores sub-sectors using reported net-profit growth and price momentum, keeps the highest-ranked groups, and filters their constituent stocks with a moving-average condition and a Bollinger Band price condition. The strategy is scheduled to refresh sector analysis and run stock selection within a trading platform.
The material is an illustrative code example rather than a tested strategy report. The code is duplicated and appears incomplete: several referenced functions, variables, and a position-management section are missing, and some calculations may not match their stated labels. It provides no backtest or live-trading evidence, so the ranking method’s effectiveness and data availability are unverified. Any implementation would need debugging and careful checks for look-ahead bias, data definitions, and realistic execution assumptions.
Key ideas
- The proposed sector ranking combines price momentum, money-flow estimates, and policy-keyword news scores.
- The design narrows stock selection to leading sub-sectors and applies moving-average and Bollinger Band conditions.
- Net-profit growth is used as a sub-sector input alongside recent price momentum.
- The supplied example is incomplete and duplicated, and it does not provide performance evidence.
- Implementation requires checking data definitions, missing functions, and potential look-ahead bias.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.