Qinhuangdao Port Co (601326) Fair Value & Analysis
Industrials · CN · Market cap 19.3B CNY
Analysis
Qinhuangdao Port Co (601326) currently trades at ¥3.31, while our model-based Fair Value estimate is ¥6.28 — implying the stock looks roughly 89.7% undervalued today. We read business quality at 89/100 (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
Qinhuangdao Port Co., Ltd. provides integrated port services in Mainland China. The company offers highly integrated and comprehensive port services, including stevedoring, stacking, warehousing, transportation, discharging, container stacking, container load, and logistics services; and handles various types of cargoes comprising coal, metal ores, oil and liquefied chemicals, containers, and general cargoes. It also provides ancillary port services, such as tallying and trans-shipping services. In addition, the company offers value-added services, consisting of tallying, coal blending and bonded warehouse, and export supervisory warehouse services; terminal facilities for vessels; and loading and unloading services. Further, it leases and repairs harbor facilities, equipment and machinery, cargo weighing, port tallying; provision of power and electrical engineering services; and labor dispatch services. The company was founded in 1898 and is headquartered in Qinhuangdao, China. Qin…
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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.