Arvind Limited (ARVIND) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹145B
Fair value as of: Jun 29, 2026
Analysis
Arvind Limited (ARVIND) currently trades at ₹547.25, while our model-based Fair Value estimate is ₹347.43 — implying the stock looks roughly 36.5% overvalued today. We read business quality at 95/100 (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
Arvind Limited, together with its subsidiaries, manufactures, markets, retails, supplies, and exports textiles in India and internationally. It operates through Textiles, Advanced Material, and Others segments. The company offers denim fabrics, woven and knitted fabrics, and voiles and garments products. It also provides a range of specialized clothing and accessories for factory workers, fire-fighters, construction crew, soldiers, and healthcare and security personnel; hot-gas and liquid filtration products; automotive interiors and seating solutions; and composites and coated fabrics. In addition, the company offers water treatment, industrial waste water, and sewage treatment solutions for industries, as well as zero liquid discharge solutions. Further, it is involved in the e-commerce, agriculture produce, engineering, telecommunication, technical textiles, and other businesses, as well as provision of EPABX and one to many radio solutions; and building residential, commercial, …
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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.