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SMARTGEN (Zhengzhou) Technology Co (301361) Fair Value & Analysis

Industrials · CN · Market cap 3.9B CNY

Price¥34.15
Fair Value¥14.51
Upside-57.5%
Quality95/100
Evidence: High Range ¥10.71 – ¥17.78

Analysis

SMARTGEN (Zhengzhou) Technology Co (301361) currently trades at ¥34.15, while our model-based Fair Value estimate is ¥14.51 — implying the stock looks roughly 57.5% 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: high).

About the company

SMARTGEN (Zhengzhou) Technology Co., Ltd. engages in the research and development, manufacturing, sales, and service of control systems in China. It offers genset controller, new energy controller, ATSE controller, marine diesel controller, engine controller, marine generator control module, expansion module, charger, voltage regulator, control panel, ATS, heater, cloud monitoring modem, module, and product accessories. The company also provides genset control, low-voltage distribution solutions, marine products, engineering machinery, and new energy solutions. It serves mining and oil extraction, AI data centers, ships, offshore islands, smart buildings, zero-carbon industrial parks, telecommunications, infrastructure, and commercial and industrial energy storage industries. The company was founded in 1998 and is based in Zhengzhou, 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.