Exide Industries Limited (EXIDEIND) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹331B
Fair value as of: Jun 29, 2026
Analysis
Exide Industries Limited (EXIDEIND) currently trades at ₹389.80, while our model-based Fair Value estimate is ₹221.08 — implying the stock looks roughly 43.3% overvalued today. We read business quality at 97/100 (high quality), in the Consumer Cyclical 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
Exide Industries Limited designs, manufactures, markets, and sells lead acid batteries and accumulators in India and internationally. It offers automotive, infrastructural, genset, solar, inverter, institutional uninterrupted power supply (UPS), and submarine batteries, as well as home UPS systems, integrated power back-up systems, and e-rickshaw vehicles. The company also manufactures and supplies recycled lead and lead alloys; offers lithium-ion batteries; produces and distributes industrial battery chargers and rectifiers; and provides energy storage solutions, as well as engages in the non-conventional energy business. It sells batteries under the Exide, Index, Dynex, SF Sonic, Chloride, Dagenite, Jupiter, Black panther, and CEIL brand names through a distribution network of dealers. The company was formerly known as Chloride Industries Ltd. and changed its name to Exide Industries Limited in August 1995. Exide Industries Limited was founded in 1916 and is headquartered in Kolka…
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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.