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Kangping Technology (Suzhou) Co (300907) Fair Value & Analysis

Industrials · CN · Market cap 4.6B CNY

Price¥51.53
Fair Value¥10.46
Upside-79.7%
Quality88/100
Evidence: Medium Range ¥7.85 – ¥13.08

Fair value as of: Jun 24, 2026

Analysis

Kangping Technology (Suzhou) Co (300907) currently trades at ¥51.53, while our model-based Fair Value estimate is ¥10.46 — implying the stock looks roughly 79.7% overvalued today. We read business quality at 88/100 (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: medium).

About the company

Kangping Technology (Suzhou) Co., Ltd. engages in the research and development, design, production, and sale of motors and related products. The company offers motors, power tools, complete machines, precision hardware, plastic parts, etc. for the power tools industry. It also provides machining, injection molding, sports tricycle, and battery pack products. The company was founded in 2004 and is based in Suzhou, China.

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Frequently asked questions

Is Kangping Technology (Suzhou) Co (300907) undervalued?
As of Jun 24, 2026, our model estimates a fair value of ¥10.46 versus a price of ¥51.53 — about −80% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 300907?
Our 21-model fair value for Kangping Technology (Suzhou) Co is ¥10.46 (as of Jun 24, 2026), built from audited fundamentals. The current price is ¥51.53.
What is the quality score of 300907?
Kangping Technology (Suzhou) Co has a Quality Score of 88/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.