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Jiangxi Special Electric Motor Co (002176) Fair Value & Analysis

Industrials · CN · Market cap 19.4B CNY

Price¥11.26
Fair Value¥7.80
Upside-30.7%
Quality95/100
Evidence: Low Range ¥5.85 – ¥9.75

Analysis

Jiangxi Special Electric Motor Co (002176) currently trades at ¥11.26, while our model-based Fair Value estimate is ¥7.80 — implying the stock looks roughly 30.7% overvalued today. We read business quality at 95/100 (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: low).

About the company

Jiangxi Special Electric Motor Co.,Ltd, together with its subsidiaries, researches, develops, produces, and sells motor products in China and internationally. It operates through Motor Industry, Lithium Industry, and Other segments. The company offers lithium carbonate and lithium ore mining products; construction machinery, hoisting and metallurgical, wind power supporting, servo, special equipment, and new energy vehicle motors; and machinery products, electric vehicles, buses, and other products. It also engages in lithium ore processing; mineral washing, and processing; manufacture of basic chemical raw materials; business services; sales and trade; exploration; research and development; e-commerce cultural; planting and breeding; accommodation industry; and commodity trading activities. Jiangxi Special Electric Motor Co.,Ltd was founded in 1958 and is headquartered in Yichun, 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.