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TangShan Port Group (601000) Fair Value & Analysis

Industrials · CN · Market cap 25.1B CNY

Price¥4.09
Fair Value¥6.71
Upside+64.1%
Quality82/100
Evidence: Medium Range ¥4.84 – ¥8.85

Analysis

TangShan Port Group (601000) currently trades at ¥4.09, while our model-based Fair Value estimate is ¥6.71 — implying the stock looks roughly 64.1% undervalued today. We read business quality at 82/100 (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

TangShan Port Group Co.,Ltd, together with its subsidiaries, provides transportation and warehousing services in China. The company offers port loading and unloading storage, transportation logistics, bonded warehousing, port comprehensive services, and other related business types. It also provides bulk cargo transportation for ore, coal, steel, sand, gravel, and water slag. In addition, the company is involved in retail business, as well as harbor tugboat operation; operates in loading and unloading and transport agency industry; and provision of logistics, property, ship repair, communication engineering design and installation, testing and identification, and software and information technology services. TangShan Port Group Co.,Ltd was formerly known as Jingtang Port Co., Ltd. and changed its name to TangShan Port Group Co.,Ltd in March 2008. The company was founded in 2003 and is headquartered in Tangshan, China.

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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.