Afrimat Limited (AFT) Fair Value & Analysis
Basic Materials · ZA · Market cap 4.9B ZAC
Fair value as of: Jun 26, 2026
Analysis
Afrimat Limited (AFT) currently trades at 28.37 ZAC, while our model-based Fair Value estimate is 18.49 ZAC — implying the stock looks roughly 34.8% overvalued today. We read business quality at 96/100 (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: high).
About the company
Afrimat Limited operates as a mining and materials company primarily in the southern African region. The company operates through five segments: Construction Materials, Industrial Minerals, Bulk Commodities, Future Materials and Metals, and Services. The Construction Materials segment provides aggregates products, including sand, gravel, and crushed stone; and concrete-based products made from rock, sand, water, cement, and readymix cement. This segment also processes and sells fly-ash; and manufactures and supplies cement. The Industrial Minerals segment offers limestone, dolomite, and industrial sand. The Bulk Commodities segment provides iron ore and anthracite. The Future Materials and Metals segment produces phosphate and rare earths. The Services segment offers IT, consulting, and external logistical; and mining services, such as mobile crushing, screening, drilling, blasting, mining, and loading and hauling services. The company was founded in 1963 and is based in Bellville, …
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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.