Jiangsu Chuanzhiboke Education Technology Co (003032) Fair Value & Analysis
Basic Materials · CN · Market cap 2.6B CNY
Fair value as of: Jun 25, 2026
Analysis
Jiangsu Chuanzhiboke Education Technology Co (003032) currently trades at ¥5.80, while our model-based Fair Value estimate is ¥1.50 — implying the stock looks roughly 74.1% overvalued today. We read business quality at 90/100 (high quality), in the Basic Materials 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: medium).
About the company
Jiangsu Chuanzhiboke Education Technology Co., LTD. provides digital talent vocational educational services in China. The company offers digital talent vocational training, such as digital professional courses, Hongmeng application development, artificial intelligence development, python+big data, JavaEE, HTML and JS + front-end, software testing; architect, integrated circuit application development comprising embedded, etc. under the Dark Horse Programmer and Boxue Valley brand names. It also provides digital application courses, including new media + short video live broadcast operation, product manager, and e-commerce visual design. In addition, the company offers human resource, and digital talent education and training services; and engages in the radio and television program production and consulting activities. Jiangsu Chuanzhiboke Education Technology Co., LTD. was founded in 2012 and is based in Beijing, 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.