Tam Adj Peg

TAM-Adj-PEG

Core Idea

Traditional PEG asks:

Is the current valuation expensive relative to future EPS growth?

TAM-Adj-PEG asks a broader question:

How long can this growth last, is the TAM large enough, and can the company convert TAM growth into durable profits?

Use this framework for AI infrastructure, semiconductors, healthcare, SaaS, payment networks, high-growth manufacturers, bottleneck suppliers, early turnarounds, and option-like equities.

Treat results as research analysis, not investment advice. For latest/current scoring, verify valuation, estimates, TAM, margins, and company-specific data from current sources before calculating.

Required Inputs

Collect the newest available data before scoring:

• Valuation: current PE or TTM PE, forward PE, and traditional PEG if available.
• Growth: expected 2-3 year EPS CAGR, revenue CAGR, TAM CAGR, and current revenue / TAM penetration.
• Profit quality: gross margin, EBIT margin, free cash flow profile, capex intensity, and dilution risk.
• Business quality: competitive position, pricing power, customer concentration, technology iteration risk, cyclicality, and key milestones.
• Preferred sources: company IR releases/presentations, earnings calls, SEC filings, consensus estimate providers, industry TAM reports, and reputable financial data sources.

For U.S.-listed companies, use SEC filings as the baseline for reported fundamentals. edgartools is an optional helper for retrieving latest 10-K, 10-Q, 8-K, XBRL financial statements, filing text, insider transactions, and ownership filings.

If the environment does not already have it, install with pip install edgartools or uv pip install edgartools. The import package is edgar, not edgartools. SEC access requires an identity; set EDGAR_IDENTITY="Name email@example.com" in the environment or call from edgar import set_identity; set_identity("name@example.com") before requests.

Minimal usage pattern:

from edgar import Company

company = Company("AAPL")
financials = company.get_financials()
income = financials.income_statement()
cashflow = financials.cashflow_statement()

Use SEC data to support:

• revenue scale, segment mix, gross margin, EBIT margin, free cash flow, capex intensity, debt/cash, dilution, and share-count trends
• customer concentration, pricing language, backlog/order commentary, supply constraints, technology risk, and cyclicality disclosures
• 8-K earnings releases or guidance disclosures when they provide the newest company-reported inputs

Do not rely on SEC data alone for forward PE, EPS CAGR, consensus revisions, current valuation, TAM size, TAM CAGR, or competitive market-share estimates. Keep reported SEC facts separate from forecasts and industry assumptions, and cite the filing form/date when using SEC evidence.

If PE or EPS CAGR is not meaningful because the company is loss-making or earnings are highly volatile, mark PE/PEG as distorted and use normalized earnings, EV/Sales, milestone scenarios, or an option-style framework.

Core Formula

Calculate:

TAM-Adj-PEG = Forward PE / (EPS CAGR x TAM Runway Factor x Quality Factor)
Adjusted Growth = EPS CAGR x TAM Runway Factor x Quality Factor

Use EPS CAGR as a percentage number in the denominator. Example: if forward PE is 40 and adjusted growth is 50%, then TAM-Adj-PEG = 40 / 50 = 0.8.

Do not directly add TAM CAGR to EPS CAGR. EPS CAGR usually already reflects part of TAM expansion; TAM should mainly adjust growth duration and certainty.

TAM Runway Factor

Use TAM Runway Factor to correct for how long high growth can continue:

TAM Runway Factor = sqrt(Growth Duration / 5)

Rough scoring:

Do not assign runway by sector label alone. AI-driven semiconductor bottlenecks can deserve a 15-20+ year runway when demand is structurally expanding, the company controls a hard-to-replicate choke point, and each technology generation reinforces its position. Conversely, SaaS or platform companies should not automatically receive a long runway if frontier AI models can compress workflow value, commoditize features, weaken seat-based pricing, or shift the profit pool to model/infrastructure providers.

Quality Factor

Use Quality Factor to correct for whether growth can remain in the company's income statement:

Evaluate nine questions:

1. Can TAM growth actually accrue to this company? 2. Does the company have pricing power? 3. Is customer concentration high? 4. Does frequent technology iteration require repeated requalification? 5. Are gross margin and EBIT margin sustainable? 6. Does growth require heavy capex? 7. Can competitors quickly catch up or become second/third sources? 8. Does growth depend on financing or share issuance? 9. Can frontier AI models erode the product's workflow value, pricing model, or distribution moat?

Result Interpretation

Special Cases

Loss-Making Companies

• Do not directly use PE.
• Mark PE/PEG as distorted.
• Use normalized EPS, EV/Sales, milestone scenarios, or option-style analysis.
• Focus on key milestones and financing/dilution risk.

Cyclical Companies

• Do not use peak-cycle EPS mechanically.
• Use normalized EPS.
• Discount Quality Factor for cyclicality.
• TAM runway can add support, but supply/demand cycle risk must be deducted.
• For AI semiconductor supercycles, separate structural demand runway from inventory, capacity, and margin-cycle risk. A semiconductor leader can receive a long TAM Runway Factor if it is a durable bottleneck; the cyclical penalty should mainly flow through normalized EPS and Quality Factor, not an automatic short-runway cap.

Turnarounds

Show two versions:

This avoids misclassifying a turnaround as a normal growth stock.

Position-Type Framework

Output Format

Use this structure for every ticker:

# TICKER: TAM-Adj-PEG 估值分析

公司：XXX
股票代码：XXX

1. 当前估值
- 当前 PE：
- Forward PE：
- 传统 PEG：

2. 增长拆解
- 未来 EPS CAGR：
- Revenue CAGR：
- TAM CAGR：
- 当前收入 / TAM：
- 高速增长 runway：

3. TAM Runway Factor
- 估计值：
- 原因：

4. Quality Factor
- 估计值：
- 加分项：
- 扣分项：

5. TAM-Adj-PEG
公式：
TAM-Adj-PEG = Forward PE / (EPS CAGR x TAM Runway Factor x Quality Factor)

计算：
- 修正后增长率：
- TAM-Adj-PEG：

6. 结论
- 估值档位：
- 主要上行驱动：
- 主要下行风险：
- 适合的仓位类型：

Detailed Reference

Read references/original-framework.md when a task needs the full Chinese framework text, all scoring tables, or the original explanation of TAM-Adj-PEG logic.

可以，把 TAM-Adj-PEG 总结成一个可复用的股票分析 skill。

TAM-Adj-PEG Skill

目标

传统 PEG 只回答：

当前估值相对于未来 EPS 增速贵不贵？

TAM-Adj-PEG 进一步回答：

这个增长能持续多久？TAM 是否足够大？公司能否把 TAM 增长真正变成利润？

适合分析：

• AI infra
• 半导体
• 医药
• SaaS
• 支付网络
• 高增长制造业
• 小型瓶颈供应商
• 早期反转股 / 期权股

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一、核心公式

[ TAM\text{-}Adj\text{-}PEG=\frac{Forward\ PE}{EPS\ CAGR \times TAM\ Runway\ Factor \times Quality\ Factor} ]

也可以写成：

[ TAM\text{-}Adj\text{-}PEG=\frac{Forward\ PE}{Adjusted\ Growth} ]

其中：

[ Adjusted\ Growth = EPS\ CAGR \times TAM\ Runway\ Factor \times Quality\ Factor ]

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二、输入项

每次分析一家公司时，至少收集：

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三、TAM Runway Factor

用于修正“增长能持续多久”。

[ TAM\ Runway\ Factor = \sqrt{\frac{Growth\ Duration}{5}} ]

粗略打分：

注意：不要把 TAM CAGR 直接加到 EPS CAGR 上，因为 EPS CAGR 通常已经部分反映了 TAM 扩张。TAM 更应该影响的是 runway 和确定性。

注意：不要按行业标签机械分配 runway。AI 浪潮下的半导体瓶颈环节，如果需求是结构性扩张、公司掌握难复制的 choke point、且每一代技术迭代都强化其位置，可以给 15-20 年甚至 20 年+ 的超级周期 runway。反过来，SaaS / 平台股也不能天然享受超长 runway；如果 AI 前沿模型会压缩 workflow 价值、商品化功能、削弱 seat-based pricing，或把利润池转移到模型/基础设施层，就应下调 TAM Runway Factor 或 Quality Factor。

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四、Quality Factor

用于修正“增长能不能留在公司利润表里”。

Quality Factor 主要看 9 个问题

1. TAM 增长能不能落到这家公司？

比如 AI 数据中心增长，不等于所有供应商都赚钱。要看它是不是瓶颈。

2. 公司是否有定价权？

有定价权的增长比纯出货量增长更值钱。

3. 客户是否集中？

单一大客户占比高，要打折。

4. 技术迭代是否频繁？

比如光模块、ASIC、消费电子零部件，每一代都要重新验证，Quality Factor 要打折。

5. 毛利率是否可持续？

如果 EPS 增长主要来自价格周期或毛利率高点，要打折。

6. 资本开支是否沉重？

如果增长需要大量 capex，估值容忍度要降低。

7. 竞争对手是否容易追上？

如果二供、三供快速进入，TAM 增长会被分走。

8. 增长是否依赖融资或增发？

早期公司如果要靠不断融资兑现 TAM，Quality Factor 必须大幅打折。

9. AI 前沿模型是否会侵蚀产品价值？

对 SaaS / 平台型公司尤其要看：AI 模型是否会替代原有 workflow、商品化功能模块、削弱按席位收费、降低切换成本，或让利润池转移到模型层 / 基础设施层。如果答案是肯定的，不能因为公司叫 SaaS 或平台就给超长 runway。

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五、传统 PEG 和 TAM-Adj-PEG 的区别

传统 PEG 容易犯两个错：

1. 低估长坡厚雪公司 例如英伟达、台积电、LLY，PE 高但增长持续性强。

2. 高估周期高点公司 例如内存、航运、部分材料股，EPS 暴涨但持续时间有限。

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六、结果解释

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七、特殊公司处理

1. 亏损公司

比如 LMND、SIVE、AAOI 早期阶段、Intel 某些阶段。

处理方式：

• 不直接用 PE。
• 标注：PE/PEG 失真。
• 用正常化 EPS 或 EV/Sales 辅助。
• 重点看关键里程碑。

格式：

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2. 周期股

比如海力士、美光、材料、航运、能源。

处理方式：

• 不能用当年 EPS 高点。
• 用 normalized EPS。
• Quality Factor 打折。
• TAM runway 可以加分，但周期性必须扣分。
• 对 AI 半导体超级周期，要把“结构性需求 runway”和“库存 / 扩产 / 毛利率周期”拆开看：如果公司是长期瓶颈，可以给较长 TAM Runway Factor；周期性主要通过 normalized EPS 和 Quality Factor 扣分，而不是机械限制 runway。

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3. 反转股

比如 Intel、NVO 某些阶段。

处理方式：

拆成两个版本：

基准版

按当前盈利能力算。

反转成功版

按 2-3 年后正常化利润算。

例如：

这样可以避免把反转股误判为成长股。

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八、标准输出模板

以后你给我一个股票代码，我可以按这个模板输出：

公司：XXX
股票代码：XXX

1. 当前估值
- 当前 PE：
- Forward PE：
- 传统 PEG：

2. 增长拆解
- 未来 EPS CAGR：
- Revenue CAGR：
- TAM CAGR：
- 当前收入 / TAM：
- 高速增长 runway：

3. TAM Runway Factor
- 估计值：
- 原因：

4. Quality Factor
- 估计值：
- 加分项：
- 扣分项：

5. TAM-Adj-PEG
公式：
TAM-Adj-PEG = Forward PE / (EPS CAGR × TAM Runway Factor × Quality Factor)

计算：
- 修正后增长率：
- TAM-Adj-PEG：

6. 结论
- 估值档位：
- 主要上行驱动：
- 主要下行风险：
- 适合的仓位类型：

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九、仓位解释框架

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十、最重要的判断原则

TAM-Adj-PEG 不是为了让所有高 TAM 公司看起来便宜。

它真正要区分的是：

一句话版：

TAM-Adj-PEG = 用 TAM 的持续性和增长质量，修正传统 PEG 对“增长”的粗暴理解。