A-Share Earnings Forecast Model

What Problem It Solves

A-share earnings forecasts often suffer from inconsistent data sources, unauditable assumptions, and conclusions that are hard to trace. This skill turns consensus expectations, industry views, company research notes, and historical financials into a structured research brief for single-name fundamental modeling.

How It Works

• Data retrieval: Prefer jy-financedata-api and jy-financedata-tool, querying one security and a small number of metrics at a time to avoid batch-call failures.
• Forecast framework: Output two years of historicals and three years of forecasts for revenue, profit, EPS, PE, and ROE, plus industry trend, key drivers, and transmission paths.
• Sensitivity testing: Use the T+1 forecast as the base case to measure how core variable swings affect net profit attributable to shareholders, then state assumptions and elasticity commentary.
• Traceability: Numeric values should carry [^1] footnotes, with the matching API tools listed at the end to reduce unsupported claims.

Scope and Cautions

• Supports A-share Main Board, STAR Market, ChiNext, and BSE listed companies.
• Does not cover fund analysis, portfolio diagnosis, macro research, or industry report summaries.
• Missing data should be marked as “no data”; usage depends on mcporter, MCP service setup, and JY_API_KEY authentication.