BOMESC Offshore Engineering Company (603727) Fair Value & Analysis
Energy · CN · Market cap 4.3B CNY
Analysis
BOMESC Offshore Engineering Company (603727) currently trades at ¥17.42, while our model-based Fair Value estimate is ¥4.39 — implying the stock looks roughly 74.8% overvalued today. We read business quality at 93/100 (high quality), in the Energy 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
BOMESC Offshore Engineering Company Limited provides engineering, procurement, and construction (EPC) services for offshore oil and gas industries. The company provides design and construction EPC services for electronic modules, life modules, chemical injection modules, sledges, ocean engineering modules, and modules used in LNG mining, refinery, and chemical plants. It also engages in the resource fabrication yard, project management, design, and procurement activities. In addition, the company offers marine engineering and platform equipment; marine engineering design; production equipment manufacturing ; deep-sea oil drilling equipment manufacturing; real estate leasing; instruments and meters; metal materials; engineering supervision; steel structure design; ship-related technology development and technical services; warehousing and import/export of goods; agency services; asset and investment management; investment, financial, economic and business information, and enterprise …
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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.