Beijing Originwater Technology Co (300070) Fair Value & Analysis
Industrials · CN · Market cap 12.5B CNY
Fair value as of: Jun 24, 2026
Analysis
Beijing Originwater Technology Co (300070) currently trades at ¥3.40, while our model-based Fair Value estimate is ¥0.3500 — implying the stock looks roughly 89.7% overvalued today. We read business quality at 89/100 (high quality), in the Industrials 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
Beijing Originwater Technology Co., Ltd. engages in the water treatment business in China and internationally. The company offers sewage treatment technical solutions. It also provides recycling with membrane technology, such as scheme and engineering design, electronic control and system integration technology, system installation and engineering technology commissioning, technical support, and managed operation services; and solid waste treatment, atmospheric environment treatment, ecological engineering, and restoration technology related services. In addition, the company offers light environment construction, municipal, water supply, and drainage related services, as well as produces membranes, membrane modules, membrane materials and elements, membrane module systems, and membrane equipment used in household water purifiers and drinking water. Further, it engages in the municipal sewage and industrial wastewater treatment, tap water treatment, seawater desalination, civil wate…
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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.