De Nora India Limited (DENORA) Fair Value & Analysis
Industrials · IN · Market cap ₹4.9B
Fair value as of: Jun 29, 2026
Analysis
De Nora India Limited (DENORA) currently trades at ₹929.40, while our model-based Fair Value estimate is ₹289.98 — implying the stock looks roughly 68.8% 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
De Nora India Limited manufactures, sells, and services electrolytic products in India and internationally. The company offers anodes for chlorine and oxygen evolution; cathodes for hydrogen evolution; disinfection systems; electrodes for metal winning; electrodes and accessories for cathodic protection; membrane technologies; and water technology products. It is also involved in the manufacturing and recoating of anodes and cathodes for electrolytic processes in the chlor-alkali industry. In addition, it provides chlorate cells; Sanilec and Seaclor for seawater systems; Seaclor Mac, a brine-based system; LIDA MMO coated titanium anodes for ICCP; platinized anodes for surface finishing; and Solar Mac, a system that produces clean water from clean energy. It serves the energy transition; non-ferrous metal recovery; oil and gas offshore; pulp and paper; mining and metal refining and recovery; surface finishing, planting, and galvanizing; and plumbing and decorative industries. The com…
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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.