Cencora, Inc (C1CO34) Fair Value & Analysis
Healthcare · BR · Market cap R$276B
Fair value as of: Jun 24, 2026
Analysis
Cencora, Inc (C1CO34) currently trades at R$707.04, while our model-based Fair Value estimate is R$79.88 — implying the stock looks roughly 88.7% overvalued today. We read business quality at 91/100 (high quality), in the Healthcare sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Cencora, Inc. sources and distributes pharmaceutical products in the United States and internationally. The company's U.S. Healthcare Solutions segment distributes generic and injectable pharmaceuticals, over-the-counter healthcare products, home healthcare supplies and equipment, and related services to acute care hospitals and health systems, independent and chain retail pharmacies, mail order pharmacies, medical clinics, long-term care and alternate site pharmacies, and other customers; distributes plasma and other blood products, vaccines, and other specialty pharmaceutical products; provides pharmacy management, staffing, and other consulting services; supply management software to retail and institutional healthcare providers; packaging solutions to institutional and retail healthcare providers; clinical trial support, product post-approval, and commercialization support services; data analytics, outcomes research, and other services for biotechnology and pharmaceutical manufa…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.