Changzhou Tronly New Electronic Materials Co (300429) Fair Value & Analysis
Basic Materials · CN · Market cap 8.5B CNY
Analysis
Changzhou Tronly New Electronic Materials Co (300429) currently trades at ¥15.96, while our model-based Fair Value estimate is ¥3.62 — implying the stock looks roughly 77.3% 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: low).
About the company
Changzhou Tronly New Electronic Materials Co., Ltd. engages in the research, development, manufacture, and sale of electronic special materials and plastic products in China and internationally. It offers bisimidazole photoinitiator used in dry film and solder resist ink for the manufacture of PCB, as well as other UV curing formulation systems; oxime ester photoinitiator use in RGB and BM photoresist for LCD, semiconductor packaging materials, pigmented UV curing inks, coatings, and adhesives; and PAG for semiconductor photoresist that are used in semiconductor integrated circuit photoresists and semiconductor packaging materials. The company also provides acrylate monomer for dry film and liquid photoimageable etching resist; monomer for semiconductor photoresist; fluorene monomer used as raw material for high transparent and refringence resin, heat-resisting resin, active diluent for UV curing, RGB and BM photoresist resin, etc.; OLED organic material; triazine series used for ph…
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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.