Envista Holdings (NVST) Fair Value & Analysis
Healthcare · US · Market cap $3.7B
Analysis
Envista Holdings (NVST) currently trades at $25.26, while our model-based Fair Value estimate is $14.98 — implying the stock looks roughly 40.7% overvalued today. We read business quality at 95/100 (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
Envista Holdings Corporation, together with its subsidiaries, develops, manufactures, markets, and sells dental products in the United States, China, and internationally. The company operates in two segments, Specialty Products & Technologies, and Equipment & Consumables. The Specialty Products & Technologies segment offers dental implant systems, guided surgery systems, biomaterials, and prefabricated and custom-built prosthetics to oral surgeons, prosthodontists and periodontists, and general dentist; and brackets and wires, tubes and bands, archwires, clear aligners, digital orthodontic treatments, retainers, and other orthodontic laboratory products, as well as provides DTX Studio Clinic, a software package offered with its imaging products. This segment offers its products under the Nobel Biocare, Alpha-Bio Tec, Implant Direct, Nobel Procera, Ormco, Spark, Orascoptic, Damon, Insignia, AOA brands. The Equipment & Consumables segment provides dental equipment and supplies, includ…
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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.