CarTrade Tech Limited (CARTRADE) Fair Value & Analysis
Consumer Cyclical · IN · Market cap ₹129B
Fair value as of: Jun 29, 2026
Analysis
CarTrade Tech Limited (CARTRADE) currently trades at ₹2,694, while our model-based Fair Value estimate is ₹789.41 — implying the stock looks roughly 70.7% overvalued today. We read business quality at 90/100 (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: medium).
About the company
CarTrade Tech Limited operates a multi-channel online automotive platform in India and internationally. The company provides services, including buying, selling, marketing, valuation, and financing of new and pre-owned vehicles. It also offers new car original equipment manufacturers (OEM) solutions that provides OEMs with consumer insights and data-driven solutions for building their digital marketing strategies; new car dealer solutions, which offers customers content and research tools, such as car reviews, on road prices, car specifications, car images, car finance offers, and others; used car dealer solutions to buy and sell used cars; and technology solutions for OEMs and dealers, including dealer management systems and auto finance solutions. In addition, the company provides new two-wheeler OEM and dealer solutions; online and offline auctioning of vehicles comprising cars, bikes, trucks, farm equipment, and construction equipment; inspection and valuation services for banks…
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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.