The Supreme Industries Limited (SUPREMEIND) Fair Value & Analysis
Industrials · IN · Market cap ₹458B
Fair value as of: Jun 24, 2026
Analysis
The Supreme Industries Limited (SUPREMEIND) currently trades at ₹3,532, while our model-based Fair Value estimate is ₹1,577 — implying the stock looks roughly 55.4% overvalued today. We read business quality at 97/100 (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 Supreme Industries Limited manufactures and sells plastic products in India. The company offers plastic piping systems, including uPVC pipes, injection-molded PVC and handmade fittings; polypropylene random co-polymer pipe systems; HDPE and CPVC pipe systems; inspection chambers; manholes; bath fittings and sanitaryware; roto-molded tanks and fittings; solvents; industrial piping systems; DWC pipe system; PERT pipe system; O-PVC pipe system; and fire sprinkler systems. It also provides industrial products, such as industrial components, material handling system and pallets, roto moulded crates, pallets, and garbage bins and composite LPG cylinders. In addition, the company provides packaging products comprising flexible packaging film products, protective packaging products, and cross-laminated film and products; and furniture. Further, the company offers fabricated and customised windows from uPVC profile. It also exports its products. The Supreme Industries Limited was incorpo…
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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.