DCM Shriram Limited (DCMSHRIRAM) Fair Value & Analysis
Industrials · IN · Market cap ₹161B
Fair value as of: Jun 29, 2026
Analysis
DCM Shriram Limited (DCMSHRIRAM) currently trades at ₹1,046, while our model-based Fair Value estimate is ₹936.96 — implying the stock looks roughly 10.4% overvalued today. We read business quality at 96/100 (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
DCM Shriram Limited, together with its subsidiaries, engages in chemicals and vinyl, sugar, and value-added businesses in India and internationally. The company operates through Chemicals and Vinyl, Sugar and Ethanol, Fenesta building system, Shriram Farm solutions, Fertiliser, Bioseed, and Others segments. It offers caustic soda lye and flakes, chlorine, compressed hydrogen, and hydrogen peroxide, as well as associated chemicals comprising hydrochloric acid, stable bleaching powder, aluminium chloride, and sodium hypochlorite; and poly-vinyl chloride, carbide, and chlor alkali products. The company also manufactures PVC resins and compounds, and calcium carbide; urea; potash; windows, doors, and facade systems under the Fenesta brand; provides solutions in uPVC and system aluminium windows, WPC and engineered wood doors, and façade systems; sugar and ethanol, as well as engages in the co-generation of power; and produces cement. In addition, it offers a range of agri-inputs, such a…
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Frequently asked questions
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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.