Skills

China Earnings Preview

Pre-earnings analysis for A-share stocks.

Install

npx skills add jwangkun/claude-for-financial-services-cn --skill china-earnings-preview -g -a claude-code -y
Category
Writing
Updated
2mo ago
License
Apache-2.0
Context cost
Mediumabout 1,686 tokens
Runs scripts
No, instructions only

What it does

Pre-earnings analysis for A-share stocks. Builds scenario frameworks (actual vs consensus, beat/miss cases), identifies key metrics to watch, and prepares positioning notes before Chinese companies report quarterly results. Use instead of the original earnings-preview skill for A-share coverage. Triggers on "A股财报前瞻", "季报前瞻", "业绩前瞻", "earnings preview", "what to watch for [company] earnings", or "pre-earnings setup".

china-earnings-preview

Purpose

Build A股季报/年报前瞻分析, preparing for company earnings releases with scenario frameworks and key metrics to watch.

Data Sources

Primary: iFind MCP (Tier-1 付费) / AkShare MCP (Tier-2 免费备选)

get_quote(ticker)                        → Current valuation, PE/PB
get_historical_data(ticker)              → Trading context, 52-wk range
get_financials(ticker, "income", "annual")  → Historical revenue/EPS trends
# News (china-news MCP, separate server)
get_stock_news(ticker="{{TICKER}}")          → Pre-earnings context
get_industry_stocks(industry="...")      → Peer trading multiples

Consensus Estimates Sources

SourceAccessNotes
Wind 一致预期InstitutionalMost comprehensive
Choice 一致预期InstitutionalAlternative
慧博投研Web / APIGood coverage
同花顺 iFinDWeb / APIRetail-friendly UI
东方财富WebFree, some coverage
巨潮 业绩预告RegulatoryMandatory disclosures

If consensus unavailable, derive from:

  • Historical growth rates
  • Management guidance from prior calls
  • Industry benchmarks

Secondary Sources

  • 公司公告 (earnings preview notices 业绩预告)
  • 行业研究报告 (sector reports)
  • 卖方研报 (broker research summaries)

Workflow

Step 1: Establish Baseline

Historical performance (last 4-8 quarters):

QuarterRevenue (亿)YoYNet Income (亿)YoYEPS (元)Net Margin
Q1 2024
Q2 2024
Q3 2024
Q4 2023

Identify trends:

  • Accelerating or decelerating growth?
  • Margin expansion or compression?
  • Seasonal patterns?
  • One-time items to normalize?

Step 2: Gather Consensus Estimates

Consensus table:

Read the whole SKILL.md on GitHub

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