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Inner Mongolia MengDian HuaNeng Thermal Power Corporation (600863) Fair Value & Analysis

Utilities · CN · Market cap 44.4B CNY

Price¥5.28
Fair Value¥5.73
Upside+8.5%
Quality80/100
Evidence: Medium Range ¥3.86 – ¥7.16

Analysis

Inner Mongolia MengDian HuaNeng Thermal Power Corporation (600863) currently trades at ¥5.28, while our model-based Fair Value estimate is ¥5.73 — implying the stock looks roughly 8.5% 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

Inner Mongolia MengDian HuaNeng Thermal Power Corporation Limited engages in thermal power generation and heating businesses in China. The company is involved in the production, supply, sale, maintenance, and management of steam and hot water, wind and solar power, and other energy power generation assets; and development, construction, operation, and management of coal, coal chemical, and deep coal processing projects. It also invests in limestone and raw materials related to power production; engages in railway supporting infrastructure; and provision of management and consulting services. The company was founded in 1993 and is headquartered in Hohhot, China. Inner Mongolia MengDian HuaNeng Thermal Power Corporation Limited operates as a subsidiary of Northern United Electric Power Co., Ltd.

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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.