sector-rotation

Analyze A-share sector performance with a multi-factor scoring framework.

Updated Jul 29, 2026

Search Tags:#momentum #valuation #market-analysis #sector-rotation #a-share #investment-strategy

Ready to run

npx skills add https://github.com/santoosaraujo/vibe-trading-claude --skill sector-rotation-santoosaraujo

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sector-rotation
Source: https://github.com/santoosaraujo/vibe-trading-claude/tree/main/.claude/skills/sector-rotation
Command: npx skills add https://github.com/santoosaraujo/vibe-trading-claude --skill sector-rotation-santoosaraujo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas.

What problem does it solve?

This skill addresses the complexity of identifying high-potential sectors in the A-share market by synthesizing fragmented data into a clear, actionable rotation strategy.

Core Features & Use Cases

Multi-dimensional Scoring: Evaluates sectors based on profitability, momentum, valuation, and capital flow.
Chain Analysis: Maps industry dependencies to identify lead-lag relationships across supply chains.
Use Case: Investors can use this to determine whether to overweight sectors like Electronics or Automotive based on real-time PMI trends and policy catalysts.

Quick Start

Run the sector-rotation skill to generate a comprehensive report on current sector rankings and asset allocation recommendations.

Frequently Asked Questions about sector-rotation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify A-share sector rotation signals for asset allocation?▼

A-share sector rotation analysis evaluates market performance using profitability, momentum, valuation, and capital flow. It maps industry supply chain dependencies to identify lead-lag relationships, helping investors pinpoint high-potential sectors for strategic asset allocation.

Can I use pandas for quantitative ranking in A-share sector momentum analysis?▼

Yes, pandas supports quantitative ranking and historical data processing for A-share sector momentum analysis. The framework processes multi-factor scoring data to calculate sector rankings and identify profitable rotation signals.

What is the best way to map industry supply chain transmission effects for investment strategy?▼

Mapping industry dependencies identifies lead-lag relationships across supply chains to track transmission effects. This chain analysis reveals how policy catalysts and PMI trends propagate through sectors, providing data-driven overweight or underweight investment recommendations.

Does this sector rotation analysis support real-time PMI trends and policy catalysts?▼

Yes, sector rotation analysis integrates real-time PMI trends and policy catalysts into its multi-dimensional scoring framework. Investors use these macroeconomic indicators to determine whether to overweight sectors like Electronics or Automotive based on current market conditions.

When should I not use a multi-factor sector rotation strategy for A-share investments?▼

Avoid multi-factor sector rotation strategies when historical data is insufficient for pandas quantitative ranking, or when market volatility disrupts standard lead-lag supply chain relationships. Accurate profitability and momentum scoring requires continuous, high-quality historical data inputs.