ESAB India Limited (ESABINDIA) Fair Value & Analysis
Industrials · IN · Market cap ₹88.8B
Fair value as of: Jun 29, 2026
Analysis
ESAB India Limited (ESABINDIA) currently trades at ₹5,760, while our model-based Fair Value estimate is ₹2,325 — implying the stock looks roughly 59.6% 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
ESAB India Limited manufactures and sells welding and cutting equipment and consumables in India and internationally. The company offers gas equipment, such as cutting machines, H/VAC and plumbing, outfits, regulators, safety accessories, torches, and wear parts; arc gouging and exothermic cutting; manual plasma cutting products; filler metals, including aluminum, copper, hard facing, low alloy, mild steel, nickel, stainless steel, and other; cutting automation products comprising controls, cutting machines, gas cutting torches, plasma systems, process tools, and software; general supplies; plasma and welding equipment accessories; PPE products and accessories consisting of helmets and head protection products, gloves, clothes, eye protection products, and accessories; cobots; robotic feeders, power sources, torch cleaning stations, and torches, as well as weld data monitoring and software; standard, and air and water cooled torches; welders and wire feeders; power supplies; welding…
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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.