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Baolingbao Biology Co (002286) Fair Value & Analysis

Healthcare · CN · Market cap 3.5B CNY

Price¥8.98
Fair Value¥7.79
Upside-13.3%
Quality95/100
Evidence: High Range ¥4.61 – ¥10.39

Analysis

Baolingbao Biology Co (002286) currently trades at ¥8.98, while our model-based Fair Value estimate is ¥7.79 — implying the stock looks roughly 13.3% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare 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

Baolingbao Biology Co.,Ltd. researches and develops, manufactures, and sells a range of functional sugars in China. The company offers prebiotics, such as isomaltooligosaccharides, galactooligosaccharides, fructooligosaccharides, bagasse trisaccharides, and xylooligosaccharides; sugar alcohols and new sugar source products, including erythritol, trehalose, crystalline fructose, alodonose, and maltose; dietary fiber products comprising polydextrose and resistant dextrin; modified, waxy maize, and corn starch products; starch sugar products, including oligomaltose, fructose syrup, solid corn syrup, maltodextrin, and glucose syrup; and animal nutrition products comprising baolekang and fubaokang. Its products are used in various applications, such as dairy products, drinks, snacks, health products and dietary supplements, candy, special food items, chemicals for daily use, and animal nutrition. The company was founded in 1997 and is based in Yucheng, 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.