Kuraray Co (KURRF) Fair Value & Analysis
Basic Materials · US · Market cap $3.7B
Fair value as of: Jun 24, 2026
Analysis
Kuraray Co (KURRF) currently trades at $11.00, while our model-based Fair Value estimate is $10.85 — implying the stock looks roughly 1.4% overvalued today. We read business quality at 94/100 (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
Kuraray Co., Ltd., together with its subsidiaries, engages in the production and sale of resins, chemicals, fibers, and other-related materials in Japan, the United States, China, Europe, Asia, and internationally. The company operates through five segments: Vinyl Acetate, Isoprene, Functional Materials, Fibers, and Trading. It offers PVOH, PVB, and EVOH resins and films; methacrylic resins; heat-resistant polyamide resins; isoprene chemicals, thermoplastic elastomers; medical and dental products; activated carbon; membranes and systems for water treatment; lipids; PVA and polyester fibers; artificial leather; nonwoven fabrics; hook-and-loop fasteners; CMP pads; and plastic hose. The company is also involved in the manufacturing and sale of molded products; logistics; temporary staffing/recruitment; consulting; travel agency; insurance; and lodging and food service facilities. Its products are used in adhesives and sealants, agriculture and fishery, air and water treatment, architec…
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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.