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Wonders Information Co (300168) Fair Value & Analysis

Technology · CN · Market cap 7.0B CNY

Price¥4.83
Fair Value¥2.22
Upside-54.0%
Quality95/100
Evidence: Low Range ¥1.67 – ¥2.78

Analysis

Wonders Information Co (300168) currently trades at ¥4.83, while our model-based Fair Value estimate is ¥2.22 — implying the stock looks roughly 54.0% overvalued today. We read business quality at 95/100 (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: low).

About the company

Wonders Information Co., Ltd operates as a smart city solution provider in China. The company offers medical and health, smart government affairs, market supervision, people's livelihood protection, culture, traffic management, urban safety, smart education, information and communication technology (ICT) information technology, and health management services; and construction and operation of smart city public services platforms. It also provides integration, operation and maintenance, consulting, security, and value-added ICT services; Information technology applications, cloud computing, big data, artificial intelligence, network security, and digital parks; artificial intelligence services; and internet of things services. The company has approximately 3,300 software products and technologies with intellectual property rights. Wonders Information Co., Ltd was founded in 1995 and is headquartered in Shanghai, 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.