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Youon Technology Co (603776) Fair Value & Analysis

Technology · CN · Market cap 5.6B CNY

Price¥21.38
Fair Value¥2.58
Upside-87.9%
Quality94/100
Evidence: Medium Range ¥1.79 – ¥3.37

Analysis

Youon Technology Co (603776) currently trades at ¥21.38, while our model-based Fair Value estimate is ¥2.58 — implying the stock looks roughly 87.9% overvalued today. We read business quality at 94/100 (high quality), in the Technology 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

Youon Technology Co.,Ltd engages in the research and development, sale, construction, and operation services based on the Internet of Things and data cloud technology, hydrogen energy, and data platform business in China and internationally. It offers micro-solar hydrogen recharge-body machines, hydrogen energy bicycles, and fuel cells; and sale and service of locking systems and other products. In addition, the company provides public bicycle and shared travel services; smart life services, including smart door locks and smart home service system products; and other services through the Yonganxing app., as well as distributes hydrogen energy data platform business. The company was formerly known as Changzhou Youon Public Bicycle System Co., Ltd. and changed its name to Youon Technology Co.,Ltd in March 2018. Youon Technology Co.,Ltd was founded in 2010 and is based in Changzhou, 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.