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Cathie Wood Goes Bargain Hunting: She Just Loaded Up on 2 Cheap Magnificent Seven Stocks and an AI Player That's Dropped 60% From Its Peak.

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Cathie Wood Goes Bargain Hunting: She Just Loaded Up on 2 Cheap Magnificent Seven Stocks and an AI Player That's Dropped 60% From Its Peak.

On Nov. 25 Cathie Wood's Ark Innovation ETF added material positions: 23,769 shares of Meta (now the fund's 25th-largest holding, trading at ~25x forward earnings), 113,276 shares of Alphabet (42nd-largest, ~30x forward earnings), and 358,999 shares of CoreWeave (31st-largest), with ~10,000 more added the following day. CoreWeave, which IPO'd in late March and operates GPU-as-a-service for AI workloads, has fallen ~60% from its June peak and remains unprofitable despite rapid revenue growth; Wood's purchases signal a value-driven bet on AI exposure across established ad/ cloud incumbents and a high-growth AI-infrastructure name.

Analysis

Market structure: Ark’s buys (META, GOOGL, CRWV) underscore a winners-take-most dynamic in AI where specialized GPU capacity and platform control capture pricing power; expect sustained upward pressure on GPU spot rents and Nvidia (NVDA) pricing for 6–12 months unless supply ramps faster than consensus. Advertising incumbents (META, GOOGL) benefit from AI-driven engagement monetization while smaller ad-dependent peers and traditional IT services risk margin compression as AI redirects enterprise spend. Cross-asset: a re-acceleration in AI adoption would steepen the yield curve modestly (10–30bp over 3 months on growth surprise), raise equity vols in semiconductors/cloud, strengthen USD vs EMs on tech outperformance, and incrementally raise power and copper demand for data centers.

Risk assessment: Tail risks include US/China export controls on high-end GPUs, major regulatory action on ad-targeting (FTC/DOJ) and a rapid hyperscaler price war that collapses GPU-as-a-service margins — each could cut implied valuations 20–50% in 3–12 months. Short-term (days-weeks) risks are ETF flow reversals and headline-driven volatility; medium-term (3–12 months) risks center on execution (CoreWeave capacity financing) and ad-revenue cyclicality; long-term (3+ years) hinges on monetization of AI features and total addressable market capture. Hidden dependencies: CoreWeave is highly dependent on Nvidia supply and spot pricing; META/GOOGL depend on ad budgets and successful model monetization. Catalysts: NVDA earnings (next 30–60 days), Google Cloud/Alphabet AI product roadmap, CoreWeave quarterly cadence and any GPU export rule changes.

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