The Weir Group (WEIGF) Fair Value & Analysis
Industrials · US · Market cap $8.3B
Analysis
The Weir Group (WEIGF) currently trades at $31.43, while our model-based Fair Value estimate is $16.28 — implying the stock looks roughly 48.2% 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
The Weir Group PLC, together with its subsidiaries, produces and sells highly engineered original equipment worldwide. The company operates in two segments, Minerals and ESCO. The Minerals segment offers engineering, manufacturing, and service processing technology for the use in abrasive and high-wear mining applications; and differentiated technology for the use in infrastructure and general industrial markets. This segment provides cloud-based artificial intelligence solutions to the mining industry. The ESCO segment provides ground engaging tools for mining machines. In addition, the company offers aftermarket products, wear parts, equipment attachments, and processing equipment. Further, it provides field services comprising commissioning and ongoing support services; rebuild and repair services; digital services; and process optimization services. The company offers its products and services under the Cavex, Enduron, ESCO, GEHO, Linatex, Motion Metrics, Next, Warman, Accumin, …
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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.