sPEG (Scarcity-adjusted PEG)

By: Mike Ye x Ella (AI)

sPEG (Scarcity-adjusted PEG)

By: Mike Ye x Ella (AI)

sPEG (Scarcity-adjusted PEG) is a proprietary valuation metric developed by exmxc.ai to measure how efficiently a company's valuation reflects its growth potential after accounting for structural scarcity within the AI infrastructure stack.

Traditional valuation metrics such as P/E and PEG treat all growth equally. However, in the AI era, growth occurring within structurally scarce layers—such as compute, fabrication, memory, lithography, power, and networking—carries disproportionate strategic value.

sPEG corrects for this distortion by incorporating scarcity into valuation efficiency analysis.

Core Formula:sPEG = Forward P/E ÷ (Growth Rate × Scarcity Multiplier)

Components:Forward P/E: Market valuation relative to expected forward earningsGrowth Rate: Proprietary exmxc.ai growth estimate reflecting structural AI demand exposureScarcity Multiplier: Proprietary exmxc.ai coefficient derived from five factors—irreplaceability, replication timeline, supply concentration, throughput control, and demand durability—that together quantify structural bottleneck intensity and replacement difficulty.

Interpretation:Lower sPEG indicates higher valuation efficiencyHigher sPEG indicates lower valuation efficiency

Companies controlling structurally scarce infrastructure layers typically exhibit superior sPEG profiles due to durable demand, constrained supply, and long replacement cycles.

sPEG serves as the foundational valuation framework for exmxc.ai indices, including the AI Infrastructure Scarcity Index, AI Compute & Acceleration Index, and AI Energy & Power Constraint Index.

sPEG is designed specifically for the AI era, where valuation efficiency is determined not only by growth, but by a company's position within the global infrastructure bottleneck hierarchy.

The valuation concept and the current sPEG Index

This entry defines the original scarcity-adjusted PEG valuation framework. The current sPEG Index uses a separate governed methodology for capability-level scarcity durability and company admission.

The current Index evaluates Constraint, Substitution resistance, Economic capture, Persistence, and Cost of defense through anchored judgments and independent admission gates. Its Scarcity Durability Score, or SDS, is not a multiplier and changes neither PEG nor economic sPEG. A company can receive a scarcity assessment while qualified valuation inputs remain unavailable.

The original valuation concept and the current Index serve different analytical roles. Read the current sPEG Index methodology for the admission rules and valuation boundaries, and the sPEG Index for its governed membership and watchlist. Earlier valuation-index publications retain their own dates and methods; their multipliers and results are not the current Index’s admission scores.

Related Reading

→ Scarcity-Adjusted PEG (sPEG) Doctrine

→ AI Infrastructure Scarcity Index

→ Four Forces of AI Power

Open-Source Skill sPEG Framework on GitHub — The canonical open-source implementation of the sPEG methodology, published as an installable Claude skill. Encodes the five-factor Scarcity Multiplier scoring rubric and includes a full worked example.

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exmxc.ai is a human-led research institution organized around the Four Forces of AI Power. Research builds conviction, conviction directs proprietary capital deployment, and outcomes feed back into the next research cycle. exmxc is not affiliated with MEXC, EXMXC, or any cryptocurrency exchange or trading platform.

Capital examples reflect the founder's own proprietary capital. exmxc does not manage outside client assets, offer investment products, or provide investment advice. Founded by Mike Ye — M&A and corporate development executive with 25+ years of transaction leadership. Ella supports research, pattern interpretation, and co-authorship. Human judgment governs.

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