Guangzhou Guangri Stock Co (600894) Fair Value & Analysis
Industrials · CN · Market cap 7.1B CNY
Analysis
Guangzhou Guangri Stock Co (600894) currently trades at ¥8.47, while our model-based Fair Value estimate is ¥9.50 — implying the stock looks roughly 12.2% undervalued today. We read business quality at 91/100 (high quality), in the Industrials 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: high) — always confirm before acting.
About the company
Guangzhou Guangri Stock Co.,Ltd. manufactures and sells elevators and related parts in China. The company engages in the design, production, installation, repair, and maintenance of elevators, escalators, and moving walkways; and design and production of elevator electrical components and related electrical products, elevator guide rails, and related spare parts. It also provides third-party logistics services, including transportation, distribution, warehousing, packaging, and processing. In addition, The company is involved in the digital intelligence business; smart parking services, such as vertical lift, planar moving, lift-and-slide, and simple lift, as well as parking garage solutions; smart lighting business, including smart street, tunnel, landscape, industrial and, and mining, as well as high-power drive power supplies. The company was formerly known as Guangzhou Iron and Steel Co.,Ltd. The company is based in Guangzhou, China. Guangzhou Guangri Stock Co.,Ltd. is a subsidi…
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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.