Raffles Medical Group (RAFLF) Fair Value & Analysis
Healthcare · US · Market cap $1.5B
Analysis
Raffles Medical Group (RAFLF) currently trades at $0.7500, while our model-based Fair Value estimate is $0.6500 — implying the stock looks roughly 13.3% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare 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
Raffles Medical Group Ltd provides private healthcare services in Singapore, Greater China, Vietnam, Cambodia, and Japan. It operates through four segments: Healthcare Services, Hospital Services, Investment Holdings, and Insurance Services. The company operates Raffles Hospital that offers 24-hour acute and critical care; ambulance services and mobile medical calls to home, hotels, worksites, and onboard ships; and triage, emergency consultation, and inpatient ward admission services. Its hospital also provides various services, including covid 19 test, health screening, executive medical centre, statutory health check, dental, and chinese medicine; and specialist centers for cancer, children, counselling, diabetes and endocrine, dialysis, eye, fertility, heart, internal medicine, neuroscience, nuclear medicine, orthopaedic, pain management, rehabilitation, skin and aesthetics, surgery, urology, and woman, as well as ear, nose, and throat. In addition, the company offers health scr…
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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.