Kajima Corporation (KAJMY) Fair Value & Analysis
Industrials · US · Market cap $17.2B
Analysis
Kajima Corporation (KAJMY) currently trades at $36.69, while our model-based Fair Value estimate is $37.88 — implying the stock looks roughly 3.2% undervalued today. We read business quality at 96/100 (high quality), in the Industrials 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
Kajima Corporation engages in civil engineering, building construction, real estate development, architectural and civil design, and other businesses. It is involved in the construction of power stations, railways, roads, airports, and seaports, as well as water purification and wastewater treatment plants, steel works, and chemical production facilities; and research and development in various fields, including skyscrapers, nuclear power plants, long span bridges, and deep underground tunnels. It also offers specialized technologies and services for production and R&D facilities, logistic facilities, plant factories, cell culture facilities, and other applications; and develops and maintains social infrastructure using various technologies related to zero energy bildings, green infrastructure, soil and underground water remediation, water and sewer treatment facilities, and final disposal sites, as well as wind power generators, other renewable energy facilities, biomass utilizatio…
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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.