China Master Logistics Co (603967) Fair Value & Analysis
Industrials · CN · Market cap 4.2B CNY
Analysis
China Master Logistics Co (603967) currently trades at ¥11.26, while our model-based Fair Value estimate is ¥16.24 — implying the stock looks roughly 44.2% undervalued today. We read business quality at 88/100 (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: medium) — always confirm before acting.
About the company
China Master Logistics Co., Ltd. operates as an integrated logistics company in China. It operates through Cross-Border Container Logistics; Engineering Logistics; and Resource Transshipment Logistics segments. The company offers freight forwarding services comprising booking agency, freight forwarding, TCR logistics, air parcel, customs clearance, supply chain management, over-seas network, and consultation solutions. It also provides container management, depot service, container leasing, container technical services, LCL logistics, and bonded logistics services; and international shipping agency, emergency rescue and tugging, issuing B/L on behalf of carrier, chartering and booking, and spare parts logistics services. In addition, the company offers coastal transportation services, such as foreign trade feeder services, domestic cargo transportation, coastal empty re-position, break bulk transportation, special cargo shipping solution, and out of gauge (OOG) containers; projects …
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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.