Dimet (Siam) Public Company (DIMET) Fair Value & Analysis
Basic Materials · TH · Market cap 135M THB
Fair value as of: Jun 26, 2026
Analysis
Dimet (Siam) Public Company (DIMET) currently trades at 0.0700 THB, while our model-based Fair Value estimate is 0.0490 THB — implying the stock looks roughly 30.0% 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
Dimet (Siam) Public Company Limited, together with its subsidiaries, manufactures and distributes paints in Thailand. The company operates through four segments: Manufacture and Distribution of Paints; Provision of Construction Service; Sale of Construction Materials; and Wholesale General Products. It designs, develops, manufactures, sells, and distributes coating products and related products, including paints for buildings, wood coatings, furniture finishes, and gas cylinder spray paints for protection, wood, industrial, marine, automotive, architectural, and waterproof coating works. The company also manufactures and trades in medical and industrial gloves, as well as information technology products/services and office equipment; and distributes heat-resistance coating for automotive and electrical appliance components. In addition, it engages in consumer goods distribution; renewable energy businesses; and turnkey engineering and construction contracting services. The company 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.