Business-intelligence of Oriental Nations Corporation (300166) Fair Value & Analysis
Technology · CN · Market cap 17.6B CNY
Analysis
Business-intelligence of Oriental Nations Corporation (300166) currently trades at ¥19.62, while our model-based Fair Value estimate is ¥15.10 — implying the stock looks roughly 23.0% 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
Business-intelligence of Oriental Nations Corporation Ltd. offers big data and cloud platform solutions in China and internationally. The company offers cirro data database, big data governance platform, enterprise big data platform, marketing, data, and sales cloud, turning mind, turning customer service turning bot, turning composer, turning robot market turning market, large model engineering kit BONDroid factory, naked computing power platform model metal, large model training platform ModelDeck, large model inference platform ModelRT, corpus annotation management platform ModelKitchen, 5G extended and integrated pico base station, intrinsically safe 5G integrated pico base station module, 5G integrated high-power base station, 5G rapid deployment system, 5G high power CPE, Cloudiip-iMine, Cloudiip, data science cloud, and BI build. It serves communications, finance, smart mine, medical, agriculture, new retail, government, and other industries. The company was incorporated in 1…
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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.