IHI Corporation (IHICY) Fair Value & Analysis
Industrials · US · Market cap $19.1B
Fair value as of: Jun 24, 2026
Analysis
IHI Corporation (IHICY) currently trades at $16.63, while our model-based Fair Value estimate is $10.26 — implying the stock looks roughly 38.3% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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
IHI Corporation designs and builds engineering solutions in Japan and internationally. The company operates through four segments: Resources, Energy and Environment; Social Infrastructure; Industrial Systems and General-Purpose Machinery; and Aero Engine, Space and Defense. The company engages in the manufacturing, sale, and provision of services related to power systems plants for land use and power systems for ships; carbon solutions comprising boilers and storage facilities; components for nuclear power plants; bridges and water gates, transport systems, shield systems, and concrete construction materials; vehicular turbochargers, parking, heat treatment and surface engineering; transport machineries; logistics and industrial systems; and rotating machineries comprising compressors, separation systems, and turbochargers for ships. It also offers gas turbine power generation systems, co-generation systems, medium sized engines, gas engine power generation systems, propulsion units…
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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.