West Fraser Timber Co (WFG) Fair Value & Analysis
Basic Materials · US · Market cap $5.4B
Analysis
West Fraser Timber Co (WFG) currently trades at $69.05, while our model-based Fair Value estimate is $7.50 — implying the stock looks roughly 89.1% overvalued today. We read business quality at 95/100 (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: low).
About the company
West Fraser Timber Co. Ltd., a diversified wood products company, engages in manufacturing, selling, marketing, and distributing lumber, engineered wood products, northern bleached softwood kraft pulp, newsprint, paper, wood chips and other residuals. It operates through four segments: Lumber, North America Engineered Wood Products, Pulp & Paper, and Europe Engineered Wood Products. The Lumber segment produces spruce, pine, fir and southern yellow pine lumber, douglas fir, hemlock, wood chips, and other residuals. The North America Engineered Wood Products segment manufactures oriented strand board, laminated veneer lumber, medium-density fibreboard, plywood, and particleboard, with OSB products marketed under brands such as Durastrand pointSIX, Pinnacle Stabledge, TruFlor pointSIX and TruFlor, Rimboard, SteadiTred, QuakeZone, Windstorm, TallWall and Trubord, and SolarBord, Trubord, TruDeck, StableDeck and StableWall, DuraSmart, Stable RVand NorCore; and MDF products under Ranger, W…
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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.