Biocon Limited (BIOCON) Fair Value & Analysis
Healthcare · IN · Market cap ₹668B
Analysis
Biocon Limited (BIOCON) currently trades at ₹423.20, while our model-based Fair Value estimate is ₹57.67 — implying the stock looks roughly 86.4% overvalued today. We read business quality at 91/100 (high quality), in the Healthcare 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
Biocon Limited, together with its subsidiaries, manufactures and sells biotechnology products and research services in India, the United States, Ireland, rest of the European Union, and internationally. It operates through Generics, Biosimilars, and Research segments. The company offers generic formulations and API products, including cardiovascular, anti-diabetics, obesity, multiple sclerosis, anti-fungal, anti-cancer, immunosuppressants, and specialty molecules; and biosimilars products consisting of pegfilgrastim, trastuzumab, bevacizumab, adalimumab, etanercept, ustekinumab, glargine, aspart, insulins, and aflibercept. It also provides integrated discovery, development, and manufacturing services to pharmaceutical, biotechnology, animal healthcare, consumer goods, and agrochemical companies. In addition, the company offers enzyme, biopharmaceutical, and medicinal goods; contract research and manufacturing services, and other research and development in the fields of pharmaceutic…
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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.