China Automotive Systems, Inc (CAAS) Fair Value & Analysis
Consumer Cyclical · US · Market cap $135M
Fair value as of: Jun 25, 2026
Analysis
China Automotive Systems, Inc (CAAS) currently trades at $4.37, while our model-based Fair Value estimate is $3.99 — implying the stock looks roughly 8.6% overvalued today. We read business quality at 88/100 (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
China Automotive Systems, Inc., through its subsidiaries, manufactures and sells automotive systems and components in the People's Republic of China, the United States, and internationally. The company produces rack and pinion power steering gears for cars and light-duty vehicles; integral power steering gears for heavy-duty vehicles; power steering parts for light duty vehicles; sensor modules; automobile steering systems and columns; and automobile electronics and systems and parts. It also provides automotive motors and electromechanical integrated systems; polymer materials; and intelligent automotive technology research and development services. In addition, the company offers after sales services, and research and development support services; and inspection and testing of automotive products, as well as markets automotive parts in North America. It primarily sells its products to the original equipment manufacturing customers. China Automotive Systems, Inc. is headquartered i…
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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.