Chengdu Jiafaantai Education Technology Co (300559) Fair Value & Analysis
Consumer Defensive · CN · Market cap 4.2B CNY
Analysis
Chengdu Jiafaantai Education Technology Co (300559) currently trades at ¥10.90, while our model-based Fair Value estimate is ¥2.99 — implying the stock looks roughly 72.6% overvalued today. We read business quality at 93/100 (high quality), in the Consumer Defensive 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 Jiafaantai Education Technology Co.,Ltd. engages in research, development, production, and sale of educational digital products in China. The company offers smart recruitment products, including an online inspection system, an identity verification system, a cheating prevention and control system, smart security gates, a patrol command system, an English listening and speaking assessment solution, multifunctional intelligent security door, paperless physical examination, test paper circulation system, intelligent confidentiality rooms, and educational examination comprehensive management platform. It also provides smart education solutions comprising a comprehensive solution for teaching and examination coordination, a smart campus and smart sport overall solution, new college entrance examination solution, and regional smart education solutions. In addition, the company offers career services, a career planning education cloud platform system, a career education and trainin…
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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.