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Pesquisa aprofundada da equipe QuantAbundancia. Metodologia, mergulhos em bolhas, e análise de fluxo de capital ancorada nos dados ao vivo da plataforma.
Sete dos portfólios institucionais mais acompanhados arquivaram seus 13F do T1 2026 esta semana. Cada posição principal mapeada na taxonomia de bolhas QuantAbundancia — onde o smart money está concentrado, onde diverge, e quais gargalos de IA a tape realmente possui.
VST, CEG, NRG, GEV, ETR, SO, AEP — the IPPs and utilities feeding hyperscaler AI campuses. ~0.55 residualized correlation. Pure exposure to GW-scale PPAs, not to NVDA's margin trajectory.
SNDK, LITE, INTC, COHR, BE — the disclosed positions inside Aschenbrenner's AI-supercycle hedge fund. Mapped to the QuantAbundancia bubble taxonomy: every name lives in a validated AI-infrastructure bottleneck.
Editorial taxonomies tell you what stocks SHOULD trade together. Correlation tells you what stocks ACTUALLY trade together. Most of the time, those are different lists.
MSFT, GOOGL, AMZN, META, ORCL look like an AI capex bloc. The data says no. Raw correlation 0.65 collapses to ~0.05 under residualization. SPY in a costume.
QBTS, RGTI, IONQ, ARQQ, QUBT — five pre-revenue stocks with the highest residualized correlation in the AI taxonomy. Why they trade as one, and how to size the bet.
Doze bolhas editoriais no superciclo da IA. Medimos todas elas com correlações residualizadas de 252 dias. Metade são reais. Metade é SPY fantasiado.
The market beta hidden in 'AI bubbles' makes correlation matrices useless until you strip it. Worked example: why Hyperscalers fail the test and Quantum passes.
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