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tam-adj-peg

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TAM-Adj-PEG

TAM-Adj-PEG

Core Idea

核心理念

Traditional PEG asks:
text
Is the current valuation expensive relative to future EPS growth?
TAM-Adj-PEG asks a broader question:
text
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.
传统 PEG 会问：
text
当前估值相对于未来 EPS 增长是否过高？
TAM-Adj-PEG 会提出更广泛的问题：
text
这种增长还能持续多久、TAM 是否足够大，以及公司能否将 TAM 增长转化为持久的利润？
此框架适用于 AI 基础设施、半导体、医疗保健、SaaS、支付网络、高增长制造商、瓶颈供应商、早期困境反转企业和期权式股票。
应将结果视为研究分析，而非投资建议。如需最新或当前评分，应在计算前通过当前来源核实估值、预测、TAM、利润率和公司特定数据。

Required Inputs

所需输入

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:
python
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.
评分前应收集最新可得数据：
  • 估值：当前 PE 或 TTM PE、Forward PE，以及传统 PEG（如有）。
  • 增长：预期的 2–3 年 EPS CAGR、Revenue CAGR、TAM CAGR，以及当前 Revenue / TAM 渗透率。
  • 盈利质量：毛利率、EBIT 利润率、自由现金流表现、资本开支强度和稀释风险。
  • 业务质量：竞争地位、定价权、客户集中度、技术迭代风险、周期性和关键里程碑。
  • 首选来源：公司 IR 新闻稿或演示材料、财报电话会、SEC 文件、一致预期数据提供商、行业 TAM 报告以及信誉良好的金融数据来源。
对于美国上市公司，应以 SEC 文件作为已报告基本面数据的基准。
edgartools
是可选辅助工具，可用于获取最新的 10-K、10-Q、8-K、XBRL 财务报表、文件文本、内部人交易和持股文件。
如果环境中尚未安装，可使用 
pip install edgartools
或 
uv pip install edgartools
安装。导入包名称是 
edgar
，而不是 
edgartools
。访问 SEC 需要身份信息；请在环境中设置 
EDGAR_IDENTITY="Name email@example.com"
，或在请求前调用 
from edgar import set_identity; set_identity("name@example.com")
。
最小使用模式：
python
from edgar import Company

company = Company("AAPL")
financials = company.get_financials()
income = financials.income_statement()
cashflow = financials.cashflow_statement()
使用 SEC 数据支持以下分析：
  • Revenue 规模、业务板块构成、毛利率、EBIT 利润率、自由现金流、资本开支强度、债务与现金、稀释情况以及股份数量趋势
  • 客户集中度、定价相关表述、积压订单或订单评论、供应限制、技术风险和周期性披露
  • 当 8-K 财报新闻稿或指引披露包含最新的公司报告输入时，将其用于分析
不要仅依赖 SEC 数据判断 Forward PE、EPS CAGR、一致预期修正、当前估值、TAM 规模、TAM CAGR 或竞争市场份额预测。应将 SEC 报告事实与预测及行业假设明确区分，并在使用 SEC 证据时注明文件类型和日期。
如果公司处于亏损状态或盈利波动极大，导致 PE 或 EPS CAGR 没有实际意义，应将 PE/PEG 标记为失真，并改用正常化盈利、EV/Sales、里程碑情景或期权式框架。

Core Formula

核心公式

Calculate:
text
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.
计算：
text
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
计算时，应将 EPS CAGR 作为百分数数值填入分母。例如，如果 Forward PE 为 40，调整后增长率为 50%，则 
TAM-Adj-PEG = 40 / 50 = 0.8
。
不要将 TAM CAGR 直接加到 EPS CAGR 上。EPS CAGR 通常已经反映了部分 TAM 扩张；TAM 主要用于调整增长持续时间和确定性。

TAM Runway Factor

TAM Runway Factor

Use TAM Runway Factor to correct for how long high growth can continue:
text
TAM Runway Factor = sqrt(Growth Duration / 5)
Rough scoring:
High-growth durationFactorInterpretation
2 years0.6Short-cycle growth
3 years0.75Growth exists, but runway is short
5 years1.0Standard growth stock
8 years1.25Long-runway compounder
10 years1.4High-quality long runway
15 years1.7Super long-cycle opportunity
20+ years2.0 capRare supercycle, platform, or monopoly-like asset
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.
使用 TAM Runway Factor 修正高增长能够持续的时间：
text
TAM Runway Factor = sqrt(Growth Duration / 5)
粗略评分：
高增长持续期系数解释
2 年0.6短周期增长
3 年0.75存在增长，但 runway 较短
5 年1.0标准成长股
8 年1.25长 runway 复利企业
10 年1.4高质量长 runway
15 年1.7超长周期机会
20 年以上2.0 上限罕见的超级周期、平台或类垄断资产
不要仅根据行业标签分配 runway。当需求正在结构性扩张、公司控制难以复制的瓶颈，并且每一代技术都会强化其地位时，AI 驱动的半导体瓶颈可以获得 15–20 年以上的 runway。反之，如果前沿 AI 模型可能压缩工作流价值、使功能商品化、削弱按席位定价能力，或将利润池转移至模型和基础设施提供商，那么 SaaS 或平台公司不应自动获得较长的 runway。

Quality Factor

Quality Factor

Use Quality Factor to correct for whether growth can remain in the company's income statement:
Quality FactorCompany Type
0.3-0.5Early-stage, loss-making, unproven orders, or high dilution risk
0.5-0.7Cyclical, customer-concentrated, or high execution risk
0.7-0.9High growth but competitive, with unstable margins
0.9-1.1Normal high-quality growth company
1.1-1.3Strong moat, pricing power, and customer stickiness
1.3-1.5Monopoly-like, platform, or ecosystem asset
1.5+Rare super-platform or AI-era bottleneck asset; use cautiously
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?
使用 Quality Factor 修正增长能否持续反映在公司的利润表中：
Quality Factor公司类型
0.3–0.5早期阶段、亏损、订单尚未验证或存在较高稀释风险
0.5–0.7周期性较强、客户集中或执行风险较高
0.7–0.9高增长但竞争激烈，利润率不稳定
0.9–1.1正常的高质量成长公司
1.1–1.3护城河强大、具备定价权且客户粘性高
1.3–1.5类垄断、平台或生态系统资产
1.5 以上罕见的超级平台或 AI 时代瓶颈资产；谨慎使用
评估以下九个问题：
  1. TAM 增长能否真正归属于这家公司？
  2. 公司是否拥有定价权？
  3. 客户集中度是否较高？
  4. 频繁的技术迭代是否要求持续重新认证？
  5. 毛利率和 EBIT 利润率是否可持续？
  6. 增长是否需要大量资本开支？
  7. 竞争对手能否迅速追赶或成为第二、第三供应来源？
  8. 增长是否依赖融资或股份发行？
  9. 前沿 AI 模型是否会侵蚀该产品的工作流价值、定价模式或分销护城河？

Result Interpretation

结果解读

TAM-Adj-PEGValuation View
< 0.5Very cheap, but verify forecasts are not overly optimistic
0.5-0.8Clearly attractive
0.8-1.2Reasonable to slightly cheap
1.2-1.8Reasonable to slightly expensive; execution must continue
1.8-2.5Expensive unless the company has a super-long runway
> 2.5Very expensive, or EPS/PE inputs are distorted
Not applicableLoss-making, early-stage, or earnings too volatile; use option framework
TAM-Adj-PEG估值观点
< 0.5非常便宜，但需核实预测是否过度乐观
0.5–0.8明显具有吸引力
0.8–1.2合理至略便宜
1.2–1.8合理至略贵；必须持续兑现执行
1.8–2.5昂贵，除非公司拥有超长 runway
> 2.5非常昂贵，或 EPS/PE 输入失真
不适用亏损、早期阶段或盈利波动过大；使用期权框架

Special Cases

特殊情况

Loss-Making Companies

亏损公司

  • 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.
  • 不要直接使用 PE。
  • 将 PE/PEG 标记为失真。
  • 使用正常化 EPS、EV/Sales、里程碑情景或期权式分析。
  • 重点关注关键里程碑以及融资和稀释风险。

Cyclical Companies

周期型公司

  • 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.
  • 不要机械地使用周期顶部的 EPS。
  • 使用正常化 EPS。
  • 根据周期性下调 Quality Factor。
  • TAM runway 可以提供支撑，但必须扣除供需周期风险。
  • 对于 AI 半导体超级周期，应将结构性需求 runway 与库存、产能和利润率周期风险区分开来。如果半导体龙头是持久稳固的瓶颈，可以获得较长的 TAM Runway Factor；周期性惩罚应主要体现在正常化 EPS 和 Quality Factor 中，而不是自动设置较短 runway 上限。

Turnarounds

困境反转

Show two versions:
ScenarioTreatment
Base caseScore current earnings power
Turnaround successScore normalized profit 2-3 years out
This avoids misclassifying a turnaround as a normal growth stock.
展示两个版本：
情景处理方式
基准情景对当前盈利能力进行评分
困境反转成功对 2–3 年后的正常化利润进行评分
这样可以避免将困境反转企业误判为普通成长股。

Position-Type Framework

仓位类型框架

TypeTAM-PEG TraitsPosition Framing
Core compounderTAM-PEG 0.5-1.2 with high Quality FactorCandidate for long-term core exposure
High-beta growthTAM-PEG 0.8-1.5 with high growth and volatilityMedium exposure, track results closely
TurnaroundCurrent TAM-PEG high, success-case TAM-PEG lowerSmall to medium exposure, milestone-driven
Option-likePE/PEG distorted, large TAM, early executionSmall exposure, accept binary outcomes
CyclicalLow PEG but discounted Quality FactorTrade supply/demand cycle, avoid linear extrapolation
类型TAM-PEG 特征仓位定位
核心复利股TAM-PEG 为 0.5–1.2，且 Quality Factor 较高可作为长期核心敞口的候选
高 beta 成长股TAM-PEG 为 0.8–1.5，且增长与波动性较高中等敞口，密切跟踪结果
困境反转当前 TAM-PEG 较高，成功情景下 TAM-PEG 较低小到中等敞口，以里程碑驱动
期权式PE/PEG 失真、TAM 较大、处于早期执行阶段小额敞口，接受二元结果
周期股PEG 较低，但 Quality Factor 被下调交易供需周期，避免线性外推

Mermaid Visualizations

Mermaid 可视化

For a full report, include 2-4 Mermaid diagrams when they materially improve comprehension. A short answer or data-limited analysis may use fewer. Do not create a diagram merely to meet a quota.
Prioritize these views:
  1. A 
    flowchart
    showing how EPS CAGR, TAM Runway Factor, and Quality Factor produce adjusted growth and TAM-Adj-PEG.
  2. A 
    quadrantChart
    comparing runway and quality for the company and peers only when at least three entities use comparable evidence and scales; retain the comparison table.
  3. An 
    xychart-beta
    comparing raw EPS growth with adjusted growth, or base and turnaround-success valuation outputs, only when the values share a clear unit.
Apply these rules to every diagram:
  • Use fenced 
    mermaid
    blocks, match the report language, keep node IDs in simple ASCII, and keep labels short.
  • Prefer broadly supported 
    flowchart
    , 
    pie
    , and 
    stateDiagram
    syntax. Use 
    xychart-beta
    , 
    quadrantChart
    , or 
    timeline
    only as progressive enhancement and retain the adjacent Markdown table as the fallback.
  • Use only evidence and values already stated in the report. Keep percentages, factor scales, valuation units, and scenario labels consistent with the surrounding tables; never fill missing data for visual completeness.
  • Place each diagram beside the analysis it explains and follow it with a one-sentence takeaway. Keep citations, URLs, dates, and detailed caveats outside the diagram.
  • Keep a diagram focused: normally no more than 12 nodes or 8 plotted values. Diagrams supplement rather than replace formulas, assumptions, risk adjustments, and source trails.
对于完整报告，只有在能够实质性提升理解时，才应包含 2–4 个 Mermaid 图。简短回答或数据有限的分析可以使用更少的图。不要仅为满足数量要求而创建图。
优先采用以下视图：
  1. 使用 
    flowchart
    展示 EPS CAGR、TAM Runway Factor 和 Quality Factor 如何生成调整后增长率与 TAM-Adj-PEG。
  2. 仅当至少三个实体采用可比的证据和量表时，才使用 
    quadrantChart
    比较公司与同行的 runway 和 quality；同时保留对比表。
  3. 仅当数值具有明确统一单位时，才使用 
    xychart-beta
    比较原始 EPS 增长与调整后增长，或基准情景与困境反转成功情景的估值结果。
每个图都应遵循以下规则：
  • 使用带围栏的 
    mermaid
    代码块，与报告语言保持一致，节点 ID 使用简单 ASCII，标签保持简短。
  • 优先使用广泛支持的 
    flowchart
    、
    pie
    和 
    stateDiagram
    语法。
    xychart-beta
    、
    quadrantChart
    或 
    timeline
    仅作为渐进增强使用，并保留相邻的 Markdown 表格作为后备方案。
  • 仅使用报告中已经陈述的证据和数值。确保百分比、系数刻度、估值单位和情景标签与周围表格一致；绝不能为了视觉完整性而填补缺失数据。
  • 将每个图放在其所解释的分析旁边，并附上一句话结论。将引用、URL、日期和详细注意事项放在图外。
  • 每个图应保持聚焦：通常不超过 12 个节点或 8 个绘制值。图是公式、假设、风险调整和来源记录的补充，而不是替代。

Output Format

输出格式

Use this structure for every ticker:
markdown
undefined
每个股票代码均使用以下结构：
markdown
undefined

TICKER: TAM-Adj-PEG 估值分析

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：
  1. 增长拆解
  • 未来 EPS CAGR：
  • Revenue CAGR：
  • TAM CAGR：
  • 当前收入 / TAM：
  • 高速增长 runway：
  1. TAM Runway Factor
  • 估计值：
  • 原因：
  1. Quality Factor
  • 估计值：
  • 加分项：
  • 扣分项：
  1. 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：
加入 Mermaid flowchart 展示三个输入如何传导到修正后增长率和最终估值；保留完整公式与计算。
如有可比公司或双情景的同口径数据，可加入 runway—quality 矩阵或增长对比 xychart，并保留数据表。
  1. 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：
undefined
公司：XXX 股票代码：XXX
  1. 当前估值
  • 当前 PE：
  • Forward PE：
  • 传统 PEG：
  1. 增长拆解
  • 未来 EPS CAGR：
  • Revenue CAGR：
  • TAM CAGR：
  • 当前收入 / TAM：
  • 高速增长 runway：
  1. TAM Runway Factor
  • 估计值：
  • 原因：
  1. Quality Factor
  • 估计值：
  • 加分项：
  • 扣分项：
  1. 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：
加入 Mermaid flowchart 展示三个输入如何传导到修正后增长率和最终估值；保留完整公式与计算。
如有可比公司或双情景的同口径数据，可加入 runway—quality 矩阵或增长对比 xychart，并保留数据表。
  1. 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：
undefined

Detailed Reference

详细参考

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.
When the reference format differs, preserve its analytical intent but follow this SKILL.md's current output and visualization rules.
当任务需要完整的中文框架文本、所有评分表或 TAM-Adj-PEG 逻辑的原始说明时，阅读 
references/original-framework.md
。
当参考格式存在差异时，应保留其分析意图，但遵循本 SKILL.md 当前的输出和可视化规则。