Yangfan New Materials (Zhejiang) Co (300637) Fair Value & Analysis
Basic Materials · CN · Market cap 2.4B CNY
Fair value as of: Jun 24, 2026
Analysis
Yangfan New Materials (Zhejiang) Co (300637) currently trades at ¥10.51, while our model-based Fair Value estimate is ¥1.72 — implying the stock looks roughly 83.6% overvalued today. We read business quality at 95/100 (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
Yangfan New Materials (Zhejiang) Co., Ltd., together with its subsidiaries, engages in the research, development, production, and sale of ultraviolet (UV) curing products, sulfur-containing fine chemicals, and related new materials in China and internationally. The company offers 4-fluoro thiophenol, diphenyl sulfide, diphenyl disulfide, cyclopropanesulfonyl amide, and thioacetamide; and intermediates, including thiophenol, phenyl sulfide, thioanisole, thiofuran, pyridine and aniline, sulfone and sulfoxide, and other products. It also provides photoinitiators; and light-curable materials, such as HRI monomers and dispersions, high refractive index UV adhesives, optically bonding and electronic assembly UV adhesives, industrial bonding UV adhesives, and photosensitive resins for special applications. The company's products are used in medicine, pesticides, dyes, and other fields. It also exports its products. In addition, the company provides technical services. The company was forme…
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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.