Bhageria Industries Limited (BHAGERIA) Fair Value & Analysis
Basic Materials · IN · Market cap ₹9.6B
Fair value as of: Jun 29, 2026
Analysis
Bhageria Industries Limited (BHAGERIA) currently trades at ₹219.13, while our model-based Fair Value estimate is ₹179.49 — implying the stock looks roughly 18.1% overvalued today. We read business quality at 96/100 (high quality), in the Basic Materials 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
Bhageria Industries Limited, together with its subsidiaries, manufactures and trades specialty dyes and dye intermediates in India and internationally. It operates through Chemicals, Solar Power, Pharma, and Others segments. The company offers organic and inorganic chemicals, such as pigment and pigment intermediates, dyestuffs, h-acid, gamma acid, and vinyl sulphone. It also generates and distributes solar power; produces active pharmaceutical ingredients; and engages in trading activities, as well as engineering, procurement, and commissioning/construction contractor services. The company exports its products to Mexico, the United States, Spain, Turkey, Bahrain, Indonesia, China, Thailand, Japan, South Korea, Taiwan, Germany, and other European and African countries. It serves various sectors, including electronics and IT, food, textile and leather, paint and coatings, construction and infrastructure, and healthcare. The company was formerly known as Bhageria Dye Chem Limited and …
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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.