Takamatsu Construction Group (TAKMF) Fair Value & Analysis
Industrials · US · Market cap $681M
Analysis
Takamatsu Construction Group (TAKMF) currently trades at $19.55, while our model-based Fair Value estimate is $38.01 — implying the stock looks roughly 94.4% undervalued today. We read business quality at 97/100 (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
Takamatsu Construction Group Co., Ltd. engages in the construction business in Japan. The company operates in Architecture, Civil Engineering, and Real Estate Segments. It is involved in construction for-lease apartments, condominium, public facilities, educational and cultural facilities, commercial facilities, accommodation and leisure facilities, logistics facilities, warehouses, factories, medical and welfare facilities, waste disposal plants, and skyscrapers, etc. The company also develops infrastructure, including rivers, roads, railways, ports, airports, dams, tunnels, bridges, residential land development, water supply and sewerage systems, soil and water conservation, ocean civil engineering, underwater civil engineering, and renewable energy works. In addition, it engages in the purchase, brokerage, and sales of other real estate services; and operation of serviced nursing-care facilities for the elderly. Further, the company provides maintenance and preservation of fishin…
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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.