AI Infrastructure Scarcity Index

By: Mike Ye x Ella (AI)
February 14, 2026
0.75
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.

• Memory layer demonstrates strongest scarcity-adjusted valuation efficiency.

• Fabrication and lithography remain structurally constrained bottlenecks.

• Compute layer remains scarce but valuation reflects recent capital inflows.

• Analog and design layers show fully priced scarcity premium.

• Index Average sPEG: 0.75

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Company Date Stock Price Scarcity Layer sPEG
SK Hynix Feb 13, 2026 $610.50 Memory 0.25
Micron Feb 13, 2026 $411.66 Memory 0.29
Taiwan Semiconductor Feb 13, 2026 $366.36 Fabrication 0.51
ASML Feb 13, 2026 $1406.61 Lithography 0.59
NVIDIA Feb 13, 2026 $182.78 Compute 0.63
Arista Networks Feb 13, 2026 $141.59 Network Infrastructure 0.69
Vertiv Feb 13, 2026 $234.53 Power & Cooling 0.80
Synopsys Feb 13, 2026 $437.09 Chip Design 1.15
Cadence Feb 13, 2026 $299.46 Chip Design 1.17
Analog Devices Feb 13, 2026 $337.10 Analog Control 1.41

The sPEG (Scarcity-adjusted Price/Earnings to Growth) ratio measures valuation efficiency relative to both growth and structural scarcity.

Formula:

sPEG = Forward P/E Ć· (Growth Rate Ɨ Scarcity Multiplier)

Lower sPEG values indicate stronger structural positioning, where growth is supported by durable scarcity and bottleneck control.

The Scarcity Multiplier and Growth Rate are proprietary measure developed by exmxc.ai to quantify the degree of structural constraint, replacement difficulty, and bottleneck control a company possesses within a given technological or infrastructure stack.

This proprietary methodology reflects structural positioning, ecosystem dependence, switching costs, supply constraints, and the degree to which a company regulates expansion of the broader system.

The AI Infrastructure Scarcity Index includes companies controlling critical bottleneck layers required for the design, manufacture, deployment, and operation of AI systems.

The Index is updated periodically as structural conditions, growth rates, and valuation levels evolve.

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