Zhonglu.Co.,Ltd (600818) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 1.8B CNY
Fair value as of: Jun 24, 2026
Analysis
Zhonglu.Co.,Ltd (600818) currently trades at ¥5.54, while our model-based Fair Value estimate is ¥8.73 — implying the stock looks roughly 57.6% undervalued today. We read business quality at 86/100 (high quality), in the Consumer Cyclical sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: low) — always confirm before acting.
About the company
Zhonglu.Co.,Ltd manufactures and sells bicycles in China. The company offers bicycles and parts, power-assisted bicycles, baby carriages, manual wheelchairs, electric wheelchairs, and spare parts, electric tricycles, motorcycles and mopeds, other special vehicles, and other supporting products related to bicycles. It also involved in import and export of goods; research, production, and sales of bowling equipment and related products; sales of polyurethane plastic related materials; rental of bicycles and power-assisted bicycles; and general cargo warehousing services. In addition, the company engages in energy technology research and technology development services; wind energy prime mover equipment manufacturing; and software wholesale, leasing of non-residential real estate, as well as post-investment management of equity investments. It also exports its products. Zhonglu.Co.,Ltd was founded in 1940 and is based in Shanghai, China.
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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.