Bhansali Engineering Polymers Limited (BEPL) Fair Value & Analysis
Basic Materials · IN · Market cap ₹24.5B
Fair value as of: Jun 29, 2026
Analysis
Bhansali Engineering Polymers Limited (BEPL) currently trades at ₹99.01, while our model-based Fair Value estimate is ₹119.12 — implying the stock looks roughly 20.3% undervalued today. We read business quality at 97/100 (high quality), in the Basic Materials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Bhansali Engineering Polymers Limited operates a petrochemical company in India and internationally. The company manufactures and sells acrylonitrile butadiene styrene (ABS) and styrene acrylate (SAN) resins. Its products include general purpose, heat resistant, flame retardant, and extrusion ABS resins for automotive, home appliances, stationery and toys, kitchenware, packaging, electronics, healthcare, and electrical, as well as construction applications. The company also provides general purpose, heat resistant, weather resistant, and direct metalizing acrylonitrile styrene acrylate (ASA) resins for automotive, pillar garnish, mirror housing, and construction applications; and heat resistant, extrusion, and paintable polycarbonate-ABS resins for automotive, electronics, household, healthcare, packaging, and construction applications. In addition, it offers specialized grade tailor made products for metallic specialty, pearl specialty, low and high gloss specialty, ASA/PMMA, and A…
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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.