A股多方法估值
SkillCommerce & financeSee what a Chinese A-share company may be worth by comparing several standard valuation methods side by side. Once added, your AI can produce a valuation range, lay out the assumptions and sensitivities behind each method, and work out what expectations a current market price implies. It does not blend the methods into a single target price and does not give buy or sell advice.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding it, ask your AI to value a specific A-share company using the methods you want compared, or to check what a current price implies. Each answer will show the assumptions, the sensitivities, and where the methods differ.
Then ask your AI: use the A股多方法估值 skill
What your AI can do with it
- Value A-share companies using DCF, comparable companies, historical ranges, PB-ROE or residual income, SOTP, or mid-cycle approaches
- Run your chosen valuation methods side by side on the same company
- Show the assumptions each method relies on and how sensitive the results are to them
- Highlight where the methods disagree with each other
- Present results as a valuation range rather than one number
- Work backwards from a market price to the expectations it implies
What this skill tells your AI
The instructions your AI receives, as published by cyijun/china-financial-services in plugins/china-model-builder/skills/a-share-valuation-triangulation/SKILL.md and read by ahel’s review.
估值输出是假设下的价值范围和分歧来源,不是精确目标价。
工作流
- 先调用
a-share-research-evidence固定估值日、股价日、财务预测版本、股本、净债务、少数股东和非经营资产。 - 使用
china-market-data获取同日daily_basic、原始行情、三表和指标;历史区间必须满足PIT与同口径要求。 - 判断公司类型与盈利阶段后选择方法,并说明未采用方法的原因。
- 建立基础、压力和乐观运营情景,情景由收入、利润率、资本强度、营运资本和周期位置驱动,不赋主观概率。
- DCF明确FCFF/FCFE、WACC/Ke构成、预测期、终值、净债务桥和稀释股本,并展示敏感性。
- 可比公司先定义业务、规模、阶段、资本结构和会计口径可比性,再使用同一时点和期间的倍数。
- 周期品使用中周期盈利;金融机构优先PB-ROE、剩余收益或DDM;多业务公司考虑SOTP。
- 并列方法区间和隐含假设,解释差异,并反向求解当前价格隐含的增长、利润率、ROE或周期位置。
DCF执行要求
非金融企业使用china-dcf-model/scripts/dcf_model.py或同等可审计实现。至少显式输入估值日、来源清单、收入基数、逐年增长/EBIT率/税率/D&A/资本开支/营运资本、估值日WACC构成、终值增长、净债务桥和稀释股本;输出逐年FCFF、显式期现值、终值占比、企业价值到股权价值桥、每股价值及WACC×永续增长敏感性。敏感性必须自动包含基础WACC和基础增长率,中心格与基础估值一致。
任何工作簿或脚本的公式生成、公式重算和生产数据验证是三种状态;未调用重算引擎时写formula_recalculation_unverified。
硬约束
- 风险利率、风险溢价、Beta、债务成本和税率必须带日期与来源。
- 可比公司选择必须先于倍数结果。
- 不可比口径先调整或扩大区间,不假装精确。
- 不机械加权、不取无依据中间值,不给评级、买卖或仓位。
输出契约
输出估值基准、方法选择、假设、方法结果、敏感性、反向隐含预期、分歧、不可验证项和失效条件。
需要方法选择时读取references/method-selection.md。
Signals
- GitHub stars
- 20
- Forks
- 3
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
a-share-valuation-triangulation- Source
- github.com/cyijun/china-financial-services