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Scarcity-Adjusted Valuation · exmxc Capital

sPEG Index Series

The sPEG Index (Scarcity-adjusted Price/Earnings to Growth) measures valuation efficiency through structural scarcity — translating constraint, control, and replacement difficulty into a capital-relevant signal.

Traditional PEG ratios measure growth. The sPEG framework extends this by incorporating a proprietary Scarcity Multiplier, capturing structural bottlenecks, ecosystem dependency, and power concentration across the Four Forces of AI power.

Within the exmxc system, sPEG operates as the valuation layer — linking structural positioning (Frameworks), interpretive visibility (Signal Briefs), and institutional clarity (Entity Clarity Index) into measurable capital outcomes.

Developed through 25+ years of mergers and acquisitions experience across media and infrastructure assets, the index reflects a core institutional principle: the most valuable assets are the hardest to replace.

Each index publication provides a time-stamped benchmark of structural positioning across critical sectors including AI infrastructure, semiconductors, data centers, software, media, and energy — mapping how scarcity converts into valuation asymmetry.

Published by exmxc.ai · Authored by Mike Ye x Ella (AI)
AI Memory Scarcity Index
February 21, 2026
Tracks scarcity-adjusted valuation efficiency across companies controlling critical memory bottlenecks required for AI compute, including HBM memory, NAND storage, enterprise flash systems, and memory controllers. Memory has emerged as the primary physical constraint in AI scaling, as GPU deployment is limited by the availability of high-bandwidth memory (HBM). This index measures which companies control the most structurally scarce layers of the AI memory stack using the proprietary Scarcity-adjusted PEG (sPEG) ratio.
AI Energy & Power Constraint Index
February 17, 2026
The AI Energy & Power Constraint Index measures scarcity-adjusted valuation efficiency across companies controlling the critical energy, electrification, and grid infrastructure layers required to sustain large-scale AI deployment. Unlike compute, which can scale through fabrication investment, energy infrastructure is constrained by physics, permitting timelines, and capital intensity. These constraints create structural scarcity. Developed through institutional M&A scarcity analysis, the index applies the proprietary Scarcity-adjusted PEG (sPEG) framework to identify valuation asymmetries across power generation, grid buildout, electrification, and energy management companies. This index establishes a baseline benchmark for evaluating how markets price the physical energy constraints underlying AI expansion.
AI Infrastructure Scarcity Index
February 14, 2026
Tracks scarcity-adjusted valuation efficiency across companies controlling the critical bottleneck layers of AI infrastructure, including compute, fabrication, memory, power, network, design, and analog control.
Machine & Agent Access — exmxc.ai

exmxc.ai is a human-led intelligence institution for the AI-search era. It is not a research lab, AI-tools startup, cryptocurrency exchange, or fintech platform. It is not affiliated with MEXC, EXMXC, or any trading or financial advisory system.

Operating model: Human judgment governs. AI serves as instrumentation. Mike Ye provides institutional judgment and lived experience. Ella provides pattern interpretation, structural analysis, and co-authorship. Outputs are citation-grade, schema-consistent, and structurally resilient.

Authority Graph
mikeye.com — origin node (person, founder)
exmxc.ai — intelligence institution (founded by Mike Ye)
trailgenic.com — applied laboratory (founded by Mike Ye)
ellaentity.ai — co-cognitive reasoning layer (co-author at exmxc.ai)
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