Fresnillo plc (FNLPF) Fair Value & Analysis
Basic Materials · US · Market cap $30.2B
Fair value as of: Jun 24, 2026
Analysis
Fresnillo plc (FNLPF) currently trades at $38.15, while our model-based Fair Value estimate is $32.64 — implying the stock looks roughly 14.4% overvalued today. We read business quality at 86/100 (high quality), in the Basic Materials 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: medium).
About the company
Fresnillo plc mines, develops, and produces non-ferrous minerals in Mexico. It operates through seven segments: Fresnillo, Saucito, Ciénega, Herradura, Noche Buena, San Julián, and Juanicipio. The company primarily explores for silver, gold, lead, and zinc concentrates. Its projects include the Fresnillo silver mine located in the state of Zacatecas; Saucito mine situated in the state of Zacatecas; Ciénega mine located in the state of Durango; Herradura mine located in the state of Sonora; Noche Buena mine located in the state of Sonora; San Julián mine situated on the border of Chihuahua/Durango states; and Juanicipio mine located in the state of Zacatecas. The company also leases mining equipment; produces lead, silver and zinc concentrates and silver precipitates; produces gold/silver doré bars; mines projects; and provides exploration and administrative services. Fresnillo plc was founded in 1887 and is headquartered in Mexico City, Mexico. Fresnillo plc is a subsidiary of Indus…
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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.