Chengdu Information Technology of Chinese Academy of Sciences Co (300678) Fair Value & Analysis
Technology · CN · Market cap 6.9B CNY
Analysis
Chengdu Information Technology of Chinese Academy of Sciences Co (300678) currently trades at ¥23.73, while our model-based Fair Value estimate is ¥12.31 — implying the stock looks roughly 48.1% 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
Chengdu Information Technology of Chinese Academy of Sciences Co.,Ltd provides information solutions, intelligent engineering, and related products and technical services to tobacco, banknote printing, and detection, oil and gas, government and other industries. The company offers a digital conference system, which includes electoral, voting, register, CPPCC, and other conference systems. It also offers statistical and big data solutions. In addition, the company provides IOT, operating room, digital scientific research, medical education, and data integration solutions. Further, it offers smart manufacturing services comprising printing and coinage, associated gas, oil and gas production, tobacco manufacturing services, and banknote printing inspection products. Chengdu Information Technology of Chinese Academy of Sciences Co.,Ltd was founded in 1958 and is based in Chengdu, 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.