Nipro Corporation (NPRRF) Fair Value & Analysis
US · Market cap $1.6B
Analysis
Nipro Corporation (NPRRF) currently trades at $9.96, while our model-based Fair Value estimate is $3.89 — implying the stock looks roughly 60.9% overvalued today. We read business quality at 95/100 (high quality). 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
Nipro Corporation, together with its subsidiaries, engages in the medical devices, pharmaceuticals, and pharma packaging businesses. Its Medical Device business develops, manufactures, and sells medical equipment for injection-infusion and dialysis treatment, and products related to diabetes and cell cultures, as well as the sale of artificial organ-related products. The company's Pharmaceutical business provides pharmaceutical combination products, including dual chamber bags, pre-filled syringes, and half-type kits; and contract manufacturing services for orally administered drugs, injectables, and external preparations, as well as logistic and distribution services. Its Pharma Packaging business offers glass products and other comprehensive pharmaceutical packaging, such as glass vials, ampoules, and syringes; tube glass; and other parts of pharmaceutical packaging, such as rubber plugs, as well as provides glass for thermos bottles, and lighting and containers. The company also …
Open the full interactive analysis →
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.