A-Share Multi-Dimensional Decision

Problem This Solves

Short-term A-share stock selection is often pulled in one direction by a single signal. Fundamentals-only analysis can miss sectors where capital is rotating, technical-only analysis can buy weak sectors, and event-driven analysis can mistake a one-off catalyst for a durable theme. The skill organizes the market environment, hot-sector momentum, stock strength, and final scoring into a reviewable decision chain, helping narrow a large candidate universe to a small set of focused names.

How It Works

The workflow follows a five-layer, top-down structure:

• External markets: checks US and HK markets, A50 futures, macro data, policy signals, and risk cues to decide whether the environment supports participation.
• Index trend: compares Shanghai Composite, Shenzhen Component, and ChiNext against volume and moving-average context to classify rising, range-bound, or falling conditions.
• Capital flow: tracks concept-sector rankings, main and northbound net inflows, leading-stock strength, and sector lifecycle stage.
• Stock screening: ranks names inside hot sectors using technicals, capital behavior, fundamentals, sector position, and catalysts.
• Final decision: aggregates weighted scores into star ratings and position bias, then narrows the output to a few core candidates.

The emphasis is on turning weak signals into checkable screening rules rather than predicting price moves.

Boundaries

This is better suited to medium- and short-term hot-sector rotation, capital-flow tracking, and candidate ranking. It is not a substitute for long-term value investing. The framework depends heavily on data quality: moving averages, MACD, northbound flow, and dragon-tiger list signals can become misleading if market data, capital-flow data, or event data are stale. Hot themes decay quickly, so a strong sector from yesterday may no longer be relevant today. Any score should be revalidated against the latest market context before being used.