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medmix AG (MDMXF) Fair Value & Analysis

Industrials · US · Market cap $708M

Price$17.40
Fair Value$6.62
Upside-62.0%
Quality95/100
Evidence: High Range $3.34 – $7.83

Analysis

medmix AG (MDMXF) currently trades at $17.40, while our model-based Fair Value estimate is $6.62 — implying the stock looks roughly 62.0% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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

medmix AG designs, produces, and sells high-precision devices and services in Switzerland and internationally. It operates through the Healthcare, and Consumer and Industrial segments. The company offers dispensers, cartridges, mixers, tips, syringes, pen, and auto injectors for delivery of dental materials; delivery devices and mixing for bone repair and tissue treatment, which are used for prosthetics, restoratives, anesthetics, and aesthetics; the pen and auto injectors, which are used in fertility and growth hormone treatments, treatment of diabetes, osteoporosis, and other diseases; and the delivery and mixing devices, which are used by tissue banks and medical device OEMs. It also produces and markets dispensers, cartridges, and mixers for two-component adhesives and sealants for use in construction, transportation, electronics, infrastructure, and general industrial sectors; and micro-brushes and applicators for eyes, eyelashes, lips, and facial make-up. The company offers it…

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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.