MRF Limited (MRF) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹524B
Fair value as of: Jun 24, 2026
Analysis
MRF Limited (MRF) currently trades at ₹131,350, while our model-based Fair Value estimate is ₹125,849 — implying the stock looks roughly 4.2% overvalued today. We read business quality at 97/100 (high quality), in the Consumer Cyclical 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
MRF Limited, together with its subsidiaries, engages in the manufacture and sale of rubber products in India and internationally. The company provides tires for passenger cars, two wheelers, fighter aircraft, farm, trucks, OTR, SCV, LCV, pick up, three wheeler, MCV, ICV, and tubes and valves products; rubber products, such as tubes, flaps, and tread rubber products; and manufactures specialty coatings. It also involved in the paints and coats, sports goods, and motorsports businesses. In addition, the company operates MRF T&S that provide computerized nitrogen inflation, tubeless repair, wheel alignment, wheel balancing and tire changing; MRF TireTok which offers robotic wheel alignment, vehicle safety test lane, diagnostic wheel balancing, semi-automatic tyre changer, A/C recovery and recharging, electronic headlight aligner, nitrogen generator membrane type, and special two-wheeler tire changer; MRF Tyredrome; MRF FASST that offers wheels removal and refitment, and tire mounting 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.