Bangkok Dusit Medical Services Public Company (BDUUF) Fair Value & Analysis
Healthcare · US · Market cap $10.2B
Analysis
Bangkok Dusit Medical Services Public Company (BDUUF) currently trades at $0.6400, while our model-based Fair Value estimate is $0.6600 — implying the stock looks roughly 3.1% undervalued today. We read business quality at 91/100 (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
Bangkok Dusit Medical Services Public Company Limited, together with its subsidiaries, operates hospitals in Thailand and internationally. It operates through two segments Hospital Operations; and Other Businesses That Support Hospital Business. The company operates hospitals under the Bangkok Hospital Group, Samitivej Hospital Group, BNH Hospital, Phyathai Hospital Group, Paolo Hospital, and Royal Hospital Group names; and BDMS Wellness Clinic. It also offers medical laboratory, holistic clinical wellness, accounting, technology and information, training, investment and asset management, air transportation, skin and aesthetics telemedicine, and genomic medicine services; operates hotels and pharmacies; provides health insurance and insurance brokerage services; retails medicine and pharmaceutical products; and distributes health products and cosmetic products, as well as facility management services. In addition, the company is involved in production and distribution of medicines, …
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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.