Changshu Tongrun Auto Accessory Co (603201) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 3.5B CNY
Analysis
Changshu Tongrun Auto Accessory Co (603201) currently trades at ¥20.39, while our model-based Fair Value estimate is ¥19.03 — implying the stock looks roughly 6.7% overvalued today. We read business quality at 93/100 (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
Changshu Tongrun Auto Accessory Co., Ltd. engages in the research, development, manufacture, and sale of various hydraulic jacks. It provides garage series, tool cabinet and cart, work bench, jobsite box, tool box, and tool cabinet with tools; bottle jacks, floor jacks, jack stands, engine stand, engine crane, auto equipment and accessories, screw jacks, auto tools and storage, motorcycle equipment, other jacks, log splitter, wheel dolly, hydraulic shop press, transmission jacks, lifting table cart, and portable pow; and e-vehicle battery lift table and other e-vehicle tools. The company also offers post hydraulic lift, brake lathe, wheel alignment, scissor hydraulic lift, single-post car lift, tire balancer and changer, tire expander, tire vulicanizing machine, car jacks, emergency hand brakes, and spare tire jacks. It offers its products under the BIGRED, BLACK JACK, TCE, YELLOW JACKET, and ROAD DAWG brand names. The company was founded in 1954 and is headquartered in Changshu, Ch…
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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.