/tam-adj-peg

name: tam-adj-peg
description: Evaluate a stock's valuation using TAM-Adj-PEG, adjusting traditional PEG by growth runway and quality. Use when the user provides a ticker or asks whether a growth stock's valuation is cheap, expensive, TAM-supported, runway-supported, quality-adjusted, or suitable as core growth, high-beta growth, turnaround, option-like, or cyclical exposure.

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:

| High-growth duration | Factor | Interpretation | | ---: | ---: | --- | | 2 years | 0.6 | Short-cycle growth | | 3 years | 0.75 | Growth exists, but runway is short | | 5 years | 1.0 | Standard growth stock | | 8 years | 1.25 | Long-runway compounder | | 10 years | 1.4 | High-quality long runway | | 15 years | 1.7 | Super long-cycle opportunity | | 20+ years | 2.0 cap | Rare 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.

Quality Factor

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

| Quality Factor | Company Type | | ---: | --- | | 0.3-0.5 | Early-stage, loss-making, unproven orders, or high dilution risk | | 0.5-0.7 | Cyclical, customer-concentrated, or high execution risk | | 0.7-0.9 | High growth but competitive, with unstable margins | | 0.9-1.1 | Normal high-quality growth company | | 1.1-1.3 | Strong moat, pricing power, and customer stickiness | | 1.3-1.5 | Monopoly-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 c