Birla Corporation (BIRLACORPN) Fair Value & Analysis
Basic Materials · IN · Market cap ₹77.2B
Fair value as of: Jun 29, 2026
Analysis
Birla Corporation (BIRLACORPN) currently trades at ₹1,004, while our model-based Fair Value estimate is ₹1,077 — implying the stock looks roughly 7.3% 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
Birla Corporation Limited manufactures and sells cement and clinker in India and internationally. It operates through three segments: Cement, Jute, and Others. The company offers ordinary Portland, Portland Pozzolana, and Portland slag cement under the MP Birla Cement Perfect Plus, MP Birla Cement Samrat Advanced, MP Birla Cement Ultimate Ultra, MP Birla Cement Unique, MP Birla Cement Samrat, MP Birla Cement Ultimate, MP Birla Cement Chetak, MP Birla Cement PSC, MP Birla Cement Multicem, and MP Birla Cement Concrecem brands used in bridges, dams, railway sleepers, reservoirs, industrial buildings, marine structures, cooling towers, metro lines, and airport runways. It also manufactures various jute products, such as jute yarn, floor and wall coverings, lino hessian, decorative fabrics, nursery cloths, scrims, jute carpets, non-woven jute felts, hydrocarbon-free bags/cloths, canvas, carpet backing cloths, which are used in mats, yarns, ropes, bags, carpets, and panama. In addition, t…
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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.