Shionogi & Co (SGIOF) Fair Value & Analysis
Healthcare · US · Market cap $16.0B
Analysis
Shionogi & Co (SGIOF) currently trades at $18.80, while our model-based Fair Value estimate is $26.49 — implying the stock looks roughly 40.9% undervalued today. We read business quality at 97/100 (high quality), in the Healthcare sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Shionogi & Co., Ltd. engages in the research, development, manufacture, and distribution of pharmaceuticals, diagnostic reagents, and medical devices in Japan and internationally. It is also involved in consumer healthcare business; manufacturing, sale, analytical testing, and pharmaceutical engineering of medicinal drugs and investigational drugs; contracted monitoring of epidemiological components in sewage; promotion of implementation in social infrastructure; and business related to providing data and information; develops and sells foothold; and research and development of mucosal vaccines. In addition, the company provides contract support services for experimental research; contract testing of agricultural production materials; solutions for education and healthcare, system development, human resource development, and training business; marketing support services; and IT services for medical and healthcare-related issues. The company was formerly known as Shionogi Shoten Co.,…
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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.