Nissui Corporation (NISUF) Fair Value & Analysis
Consumer Defensive · US · Market cap $2.2B
Fair value as of: Jun 24, 2026
Analysis
Nissui Corporation (NISUF) currently trades at $7.23, while our model-based Fair Value estimate is $6.28 — implying the stock looks roughly 13.1% overvalued today. We read business quality at 93/100 (high quality), in the Consumer Defensive 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
Nissui Corporation engages in marine, food products, fine chemicals, distribution, and marine-related/engineering businesses in Japan and internationally. The company is involved in the provision of salmon, Alaska pollock, yellowtail, shrimp, tuna, crab, and yellowtail products, as well as fish feed, oil, and meal products. It also produces and sells frozen foods for household and food service use, shelf-stable foods, fillet fish, and fish sausage and surimi-based products, as well as chilled foods. In addition, the company produces and supplies fine chemical products, such as eicosapentaenoic acid (EPA) for pharmaceuticals; and ingredients for functional foods, health products, supplements, and other health-related foods that contain EPA. The company was formerly known as Nippon Suisan Kaisha, Ltd. and changed its name to Nissui Corporation in December 2022. Nissui Corporation was founded in 1911 and is headquartered in Tokyo, Japan.
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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.