Eveready Industries India Limited (EVEREADY) Fair Value & Analysis
Industrials · IN · Market cap ₹26.6B
Fair value as of: Jun 29, 2026
Analysis
Eveready Industries India Limited (EVEREADY) currently trades at ₹364.50, while our model-based Fair Value estimate is ₹288.10 — implying the stock looks roughly 21.0% 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
Eveready Industries India Limited manufactures and markets dry cell batteries, flashlights, and lighting and electrical products in India and internationally. The company offers zinc carbon, alkaline, coin cell, and rechargeable batteries, as well as chargers; and plastic light-emitting diode (LED), brass, aluminum, and rechargeable torches; and portable lanterns. It also provides consumer lighting products, such as LED bulbs, LED battens, emergency LEDs, LED panels, LED downlights and spotlights, and outdoor and festive lighting; professional lighting, including indoor architectural, commercial, industrial, facade, and flood lighting; electrical accessories comprising surge protectors, extension reels, multi-plugs, doorbells, plug tops, immersion heaters, and dry irons; and mosquito racquets. In addition, the company is involved in distribution of electrical products; and trading of raw materials. It sells its products under the Eveready, PowerCell, Ultima, Shakti, and Uniross bran…
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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.