Asahi India Glass Limited (ASAHIINDIA) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹230B
Fair value as of: Jun 29, 2026
Analysis
Asahi India Glass Limited (ASAHIINDIA) currently trades at ₹898.90, while our model-based Fair Value estimate is ₹226.57 — implying the stock looks roughly 74.8% 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
Asahi India Glass Limited, together with its subsidiaries, manufactures and sells glass products in India and internationally. It operates through two segments, Automotive Glass and Float Glass. The company offers automotive glass products, including laminated glass for car windscreens; tempered glass for sidelites, backlites, and car windscreens; sunroof; sub-assemblies; value-added glass products; and white goods. It also provides architectural glass products comprising annealed, decorative, float, processed, fire-resistant, energy-efficient, window, and designer glass products, as well as coated glass products for exteriors and interiors. In addition, the company offers consumer glass products for doors, windows, staircases, balustrades, canopies, and infinity pools; and industrial glass products for consumer durables, and construction and farm equipment. Further, it provides automotive glass repair and replacement services, as well as sunroof glass replacement services; and prof…
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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.