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Zhejiang Chinastars New Materials Group (301077) Fair Value & Analysis

Consumer Cyclical · CN · Market cap 4.1B CNY

Price¥22.74
Fair Value¥15.72
Upside-30.9%
Quality95/100
Evidence: High Range ¥12.59 – ¥20.74

Analysis

Zhejiang Chinastars New Materials Group (301077) currently trades at ¥22.74, while our model-based Fair Value estimate is ¥15.72 — implying the stock looks roughly 30.9% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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

Zhejiang Chinastars New Materials Group Co., Ltd. engages in production, designing, research and development, and sales of reflective materials and their products. It offers reflective materials, such as reflective fabrics for PPE, industrial washing tapes, reflective tapes, heat transfer vinyl and logo, reflective ribbons and piping, reflective yarns, and prismatic tapes. The company also provides outdoor reflective fabrics, which includes rainbow reflective, silver reflective, gradient reflective, reflective printing, color reflective, and perforated reflective fabrics. In addition, it offers safety vest, jackets, pants, raincoats, shirts and sweatshirts, and coveralls. The company exports its products to approximately 100 countries. Zhejiang Chinastars New Materials Group Co., Ltd. was founded in 2003 and is based in Hangzhou, 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.