China BlueChemical Ltd (CBLUF) Fair Value & Analysis
Basic Materials · US · Market cap $1.7B
Analysis
China BlueChemical Ltd (CBLUF) currently trades at $0.3300, while our model-based Fair Value estimate is $0.3500 — implying the stock looks roughly 6.1% undervalued today. We read business quality at 88/100 (high quality), in the Basic Materials 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: medium) — always confirm before acting.
About the company
China BlueChemical Ltd., together with its subsidiaries, engages in the processing of natural gas and the development, production, and sale of chemical fertilizers and chemical products in the People's Republic of China and internationally. The company operates through Urea, Methanol, Phosphorus and Compound Fertiliser, Acrylonitrile, and Others segments. It offers urea; methanol; phosphorus fertilizers, including mono-ammonium phosphate and di-ammonium phosphate; compound fertilizers; and acrylonitrile and related products. The company also manufactures and sells chemical fertilizers, and woven plastic bags. In addition, it is involved in port operations; provision of transportation services and overseas shipping services; and trading of fertilizers, chemicals, and coal and coal products, as well as mining of coal. Further, the company engages in mining and processing phosphorus; manufacturing and sales of phosphorus ore and chemical products; manufacture and sale of methanol; Manu…
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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.