Jiangsu Guoxin Corp (002608) Fair Value & Analysis
Utilities · CN · Market cap 34.4B CNY
Analysis
Jiangsu Guoxin Corp (002608) currently trades at ¥8.20, while our model-based Fair Value estimate is ¥15.59 — implying the stock looks roughly 90.1% undervalued today. We read business quality at 80/100 (high quality), in the Utilities 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
Jiangsu Guoxin Corp. Ltd., together with its subsidiaries, produces and sells electricity and heat in China. It operates through Energy Business, Financial Business, and Other segments. The company is involved in coal-fired power generation and gas-fired power generation; development, production, and processing of fly ash; sale of steam and hot water; general cargo loading and unloading; warehousing services within the port area; freight distribution; power generation equipment installation and maintenance; commodity distribution; engineering construction; property management; water production and supply; procurement, storage, transportation, and sale of fuel for electricity and natural gas; procurement, transmission, and distribution of electricity; coal and natural gas trading; investment and consulting services for energy projects, such as coal financing; thermal power equipment installation and technical services; wholesale and retail of coal; and investment, development, and op…
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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.