Kaiyuan Education Technology Group (300338) Fair Value & Analysis
Technology · CN · Market cap 1.3B CNY
Fair value as of: Jun 23, 2026
Analysis
Kaiyuan Education Technology Group (300338) currently trades at ¥3.19, while our model-based Fair Value estimate is ¥0.8400 — implying the stock looks roughly 73.7% 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: low).
About the company
Kaiyuan Education Technology Group Co., Ltd. engages in the vocational education business in the People's Republic of China. The company provides education and training related services, such as improvement in the quality and technical skills of workers to adapt to the latest standards and requirements of various industries. It also engages in providing academic qualifications intermediary services; exploration and development of internet education; launching an industrial internet platform; and AI intelligent adaptive learning platform. It provides its services to learners at multiple levels, including employed persons, job seekers, college students, and vocational colleges. The company formerly known as Changsha Kaiyuan Instrument Co., Ltd. and changed its name to Kaiyuan Education Technology Group Co., Ltd. Kaiyuan Education Technology Group Co., Ltd. was founded in 1992 and is headquartered in Changsha, the People's Republic of 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.