Narayana Hrudayalaya Limited (NH) Fair Value & Analysis
Healthcare · IN · Market cap ₹400B
Fair value as of: Jun 24, 2026
Analysis
Narayana Hrudayalaya Limited (NH) currently trades at ₹1,927, while our model-based Fair Value estimate is ₹865.05 — implying the stock looks roughly 55.1% overvalued today. We read business quality at 97/100 (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
Narayana Hrudayalaya Limited provides medical and healthcare services in India and the Cayman Islands. It operates through the Medical and Healthcare Related Services; and Others segments. The company offers oncology, anesthesiology, audiology, blood bank, oncoplastic surgery, cardiac surgery, cardiology, clinical genetics, clinical immunology, clinical nutrition and dietetics, clinical psychology, congenital adult heart disease, cosmetology, cranio-maxillofacial surgery, critical care medicine, dental, dermatology, pediatrics, diabetology, ENT, emergency medicine, endocrinology, family medicine, general and GI surgery, general medicine and surgery, geriatric medicine, gynecology, hematology, headache and facial pain management, transplant, infectious diseases, neurology, radiology, hepatobiliary surgery, gastroenterology, minimal access GI and bariatric surgery, neonatology, nephrology, neuro-otology, neuro-rehabilitation, neurosurgery and spine surgery, and nuclear medicine servic…
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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.