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Shanghai Sinyang Semiconductor Materials Co (300236) Fair Value & Analysis

Technology · CN · Market cap 31.5B CNY

Price¥109.11
Fair Value¥19.19
Upside-82.4%
Quality95/100
Evidence: High Range ¥13.36 – ¥23.99

Analysis

Shanghai Sinyang Semiconductor Materials Co (300236) currently trades at ¥109.11, while our model-based Fair Value estimate is ¥19.19 — implying the stock looks roughly 82.4% 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: high).

About the company

Shanghai Sinyang Semiconductor Materials Co., Ltd. engages in the research and development, production, sale, and service of electronic materials and their surface treatment equipment in China. It offers traditional encapsulation of semiconductors, including Automatic Chemical Immersion Line, High Pressure Water Jet, Automatic Rack Plating Line, Automatic Plating Line, High Speed Plating Line, Deflashing, Electroplating solutions, as well as Wafer Level Wet Process Bench and Wafer Processing solutions. The company also offers aerospace aircraft electronic chemical materials. It serves the electronic industry, semiconductor manufacturing, packaging test and assembly, solar cell manufacturing, and aerospace electronics industries. Shanghai Sinyang Semiconductor Materials Co., Ltd. was founded in 1999 and is based in Shanghai, 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.