KEI Industries Limited (KEI) Fair Value & Analysis
Industrials · IN · Market cap ₹510B
Analysis
KEI Industries Limited (KEI) currently trades at ₹5,576, while our model-based Fair Value estimate is ₹2,017 — implying the stock looks roughly 63.8% 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
KEI Industries Limited manufactures, markets, and sells wires and cables in India and internationally. It operates in three segments: Cable & Wires; Engineering, Procurement and Construction; and Stainless Steel Wire. The company offers extra-high voltage, high tension, and low-tension power cables; control and instrumentation cables; specialty, single-core, and multi-core flexible cables; elastomeric/rubber and solar cables; fire survival/resistant cables; flat, EV charging, ESP, and medium voltage covered conductor cables; conflame green + wires; communication and thermocouple cables; and submersible marine and offshore cables, as well as stainless steel, winding, and house wires. It also provides engineering, procurement, and construction solutions in the areas of gas-insulated GIS, and air-insulated substations AIS; overhead and underground power transmission and distribution systems; and railway electrification/substation on a turnkey basis, as well as project management servic…
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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.