Toyo Gosei Co (TYGIF) Fair Value & Analysis
Basic Materials · US · Market cap $260M
Fair value as of: Jun 25, 2026
Analysis
Toyo Gosei Co (TYGIF) currently trades at $32.74, while our model-based Fair Value estimate is $20.33 — implying the stock looks roughly 37.9% overvalued today. We read business quality at 97/100 (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
Toyo Gosei Co.,Ltd. manufactures and sells photosensitive materials and polymer products primarily in Japan. The company offers negative photosensitive materials for use as a cross-linking agent for photo-curing resins; positive photosensitive materials for microfabrication of semiconductor integrated circuits and liquid crystal displays; chemically amplified photoacid generator for microfabrication of semiconductor integrated circuits; and acrylic polymer for resist. It also provides chemicals products, such as alcohols, aldehydes, acids, ketones, esters, ethers, hydrocarbons, and nitrogen compounds. In addition, the company offers logistic services, including ship receiving systems; shipping systems; chemical transport services; and storage equipment comprising fully automated dangerous goods 3d automatic warehouse, drum filling station, dangerous goods refilling equipment, blending equipment, temperature control system, analysis room, distillation purification and synthesis techn…
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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.