Allwinner Technology Co (300458) Fair Value & Analysis
Technology · CN · Market cap 30.1B CNY
Analysis
Allwinner Technology Co (300458) currently trades at ¥35.58, while our model-based Fair Value estimate is ¥5.28 — implying the stock looks roughly 85.2% 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
Allwinner Technology Co.,Ltd., together with its subsidiaries, engages in the research, design, development, manufacture, and sale of intelligent application system-on-a-chip (SoC), analog components, and wireless connectivity integrated circuits in China and internationally. The company also provides a customer service platform that provides comprehensive product package download and online technical support services for chip agents, solution providers, channel partners, and enterprise customers. In addition, it engages in trading and software development activities. The company's products are used in tablets, business displays, smart industry, smart electric power, automotive electronics, robot vacuums/robots, OTT boxes, projectors/smart TVs, HMI/PND/display control, security cameras/smart doorbell cameras, and wireless Internet of Things applications, as well as in smart hardware, smart home appliances, network set-top boxes, power supply analog devices, and wireless communicatio…
Open the full interactive analysis →
Similar stocks
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.