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Ning Xia Yin Xing Energy Co (000862) Fair Value & Analysis

Industrials · CN · Market cap 5.4B CNY

Price¥5.22
Fair Value¥2.36
Upside-54.8%
Quality94/100
Evidence: High Range ¥1.30 – ¥3.43

Analysis

Ning Xia Yin Xing Energy Co (000862) currently trades at ¥5.22, while our model-based Fair Value estimate is ¥2.36 — implying the stock looks roughly 54.8% overvalued today. We read business quality at 94/100 (high quality), in the Industrials sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).

About the company

Ning Xia Yin Xing Energy Co.,Ltd engages in the energy power generation and equipment manufacturing businesses in China. It operates wind farms and photovoltaic power stations with a total installed capacity of 341.80 MW. The company also engages in the energy equipment, including wind power generation and solar photovoltaic power generation; energy equipment engineering, which includes tower manufacturing, wind turbine assembly, and gearbox repair; provision of after-sales services; wind farm design, construction, and operation consulting; replacement, operation and maintenance, inspection and testing, hoisting and engineering construction for wind farms and photovoltaic power stations; maintenance capabilities for mainstream wind turbine speed increasers and various imported reducers; and maintenance of coal mining equipment. Ning Xia Yin Xing Energy Co.,Ltd was founded in 1959 and is based in Yinchuan, 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.