Bajaj Consumer Care Limited (BAJAJCON) Fair Value & Analysis
Consumer Defensive · IN · Market cap ₹75.5B
Fair value as of: Jun 29, 2026
Analysis
Bajaj Consumer Care Limited (BAJAJCON) currently trades at ₹578.45, while our model-based Fair Value estimate is ₹246.77 — implying the stock looks roughly 57.3% overvalued today. We read business quality at 97/100 (high quality), in the Consumer Defensive 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
Bajaj Consumer Care Limited manufactures, markets, distributes, and sells hair care, cosmetics, toiletries, and other personal care products in India and internationally. The company offers hair oil and serum, shampoo, body lotion, and soap under the Bajaj Almond Drops brand name; and castor, coconut, virgin coconut, olive, kalonji, and jojoba oil under the Bajaj 100% Pure brand. It also provides face scrub, face wash, hand sanitizer, soap, cream, and face serum under the Bajaj Nomarks brand name; and hair masque, hair oil, argan oil, hair serum, and almond oil under the Natyv Soul brand name. In addition, the company offers hair oil under the Bajaj Jasmine and Bajaj Zero Grey brands, as well as Bajaj multipurpose sanitizer products; and other consumer care products under the Bajaj Gulab Jal, Bajaj 100% Pure Henna, Sarson Amla, Brahmi Amla, and Amla Aloe Vera brands. It serves customers in hair care, hair styling, and skin care categories through retail outlets serviced by its distr…
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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.