Ag Growth International Inc (AFN) Fair Value & Analysis
Industrials · CA · Market cap C$426M
Fair value as of: Jun 25, 2026
Analysis
Ag Growth International Inc (AFN) currently trades at C$20.61, while our model-based Fair Value estimate is C$52.27 — implying the stock looks roughly 153.6% undervalued today. We read business quality at 94/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: low) — always confirm before acting.
About the company
Ag Growth International Inc., together with its subsidiaries, provides equipment solutions for bulk agriculture commodities Canada, the United States, and internationally. It operates through Farm and Commercial segments. The company offers grain, bolted, hopper, and smooth wall bins; temporary storage; unloads and sweeps systems; water tanks; secondary containment systems; liquid storage tanks; and accessories, as well as mixed flow dryers, fans and heaters, aeration products, aeration floors, vents and exhausters, and stirring systems. It also provides portable handling equipment, such as augers, conveyors, grain vacs, post pounders, seed treaters, and related accessories; and permanent handling equipment, comprising bucket elevators, chain and belt conveyors, enclosed belt conveyers, distributors, feed handling, screw feeders and conveyors, and spouts and connectors. In addition, the company offers towers, catwalks, and ladders, as well as all-steel buildings; batch blenders, bul…
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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.