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Jiangsu Baichuan High-Tech New Materials Co (002455) Fair Value & Analysis

Basic Materials · CN · Market cap 6.1B CNY

Price¥8.18
Fair Value¥7.44
Upside-9.0%
Quality93/100
Evidence: High Range ¥5.58 – ¥9.30

Analysis

Jiangsu Baichuan High-Tech New Materials Co (002455) currently trades at ¥8.18, while our model-based Fair Value estimate is ¥7.44 — implying the stock looks roughly 9.0% overvalued today. We read business quality at 93/100 (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: high).

About the company

Jiangsu Baichuan High-Tech New Materials Co., Ltd. engages in the production and sale of chemical products in China and internationally. It offers n-butanol, octanol, mixed aldol, n-butyraldehyde, isobutyraldehyde, propane, n-butyl acetate, ethyl acetate, n-propyl acetate, alcohol ethers and their derivatives, anhydrides and their derivatives, neopentyl glycol, trimethylolpropane, ditrimethylolpropane, sodium formate, cyclic trimethylolpropane, acrylate, and insulating resin. It also provides needlecoke, anode material, cathode material, and Resource Utilization of Used Lithium Batteries. The company was formerly known as Wuxi Baichuan Chemical Industrial Co.,Ltd and changed its name to Jiangsu Baichuan High-Tech New Materials Co., Ltd. in March 2018. Jiangsu Baichuan High-Tech New Materials Co., Ltd. was founded in 2002 and is based in Jiangyin, 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.