The Scotts Miracle-Gro Company (SMG) Fair Value & Analysis
Basic Materials · US · Market cap $3.6B
Analysis
The Scotts Miracle-Gro Company (SMG) currently trades at $63.49, while our model-based Fair Value estimate is $26.95 — implying the stock looks roughly 57.6% 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: high).
About the company
The Scotts Miracle-Gro Company, together with its subsidiaries, engages in the manufacture, marketing, and sale of products for lawn, garden care, and indoor and hydroponic gardening in the United States and internationally. The company provides lawn care products, comprising lawn fertilizers, clover and grass seed products, spreaders, and other durable products, as well as lawn-related weed, pest, and disease control products; and gardening and landscape products, which include water-soluble and continuous-release plant foods, potting mixes, garden soils, mulches and ground cover products, plant-related pest and disease control products, organic garden products, and live goods and seeding solutions. It also offers hydroponic products that help users to grow plants, flowers, and vegetables using little or no soil; lighting systems and components; insect, rodent, and weed control products for home areas; and non-selective weed killer products. The company sells its products under the…
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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.