Wangsu Science & Technology Co (300017) Fair Value & Analysis
Technology · CN · Market cap 36.3B CNY
Analysis
Wangsu Science & Technology Co (300017) currently trades at ¥15.35, while our model-based Fair Value estimate is ¥4.67 — implying the stock looks roughly 69.6% 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: high).
About the company
Wangsu Science & Technology Co.,Ltd. provides edge intelligence and security services worldwide. The company offers Edge computing and Edge AI, such as Edge infrastructure and Edge PaaS; CDN and network products, including web acceleration, platform infrastructure services, streaming delivery, network infrastructure service, file CDN, and SD-WAN; and web security, SASE, security service, and infrastructure service. It also provides cloud video products comprising cloud video, media process, cloud VOD, IVCS, and WS-RTC; computing, storage, cloud consultation management, and database products; computing and storage services for AI, gaming, surveying and mapping, gene sequencing, rendering, and industrial simulation scenarios. In addition, the company offers enterprise global solutions, security acceleration solutions, and remote office solutions; and finance, public sector, e-commerce, retail, education, media convergence, automobile, and game industry solutions. Wangsu Science & Tech…
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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.