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Meta Cloud News: Implications for US ‘Time to Power‘ Stocks

发布日期: 2026-07-07研究机构: Morgan Stanley公司 / 股票: WRT1V.HE,CAT.N,DLR.N,EQIX.O,BE.N,CEG.O,CIFR.O,CMI.N,CVX.N,ENR1n.DE,EQT.N,GEV.N,GLXY.O,HAL.N,INIO.O,LBRT.N,META.O,NEE.N,SCHN.PA,SEI.N,TLN.O,VST.N,WMB.N,WULF.O,XOM.N报告页数: 27原文语言: English证据页码: 7

研报英文原文证据摘录

Meta Cloud News: Implications for US ‘Time to Power‘ Stocks

Global FoundationM

North American Midstream & Renewable Energy

Infrastructure: High Conviction in WMB (OW)

We are Overweight-rated on WMB, with our $98 unlevered DCF-derived price target

reflecting +36.9% one-year, potential total-return upside (including 2.9% dividend yield).

WMB is rapidly emerging as one of the foremost providers of behind-the-meter power

solutions for hyperscalers building AI-focused data centers, offering integrated natural

gas pipeline and power generation infrastructure. WMB has differentiated itself in

creating comprehensive power solutions to hyperscalers looking to quickly scale AI-

focused data center infrastructure. With these projects, WMB provides tailored, turnkey

solutions that can include natural gas pipeline laterals, natural gas supply (including

upstream production and gathering/ processing volumes in some cases), behind the meter

gas-fired generation, fiber optic cable, batteries (for load balancing), and carbon capture

and sequestration. Power generation is the most notable differentiator from midstream

infrastructure peers and, while a step out from the core infrastructure that WMB

provides, offers greater project scale and is highly contractually protected with high

quality counterparties to insulate construction and operational risks. Expanding the value

chain from natural gas pipeline infrastructure to power, in our view, resembles in some

ways the vertical integration and margin multiplier benefits seen with natural gas/NGL

infrastructure. As investors increasingly seek out the companies that will establish

dominant AI infrastructure growth moats, we view WMB as one of the safest

expressions of a positive view on AI development through long-term contracted natural

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