Shibaura Machine Co (TSHMF) Fair Value & Analysis
Industrials · US · Market cap $585M
Analysis
Shibaura Machine Co (TSHMF) currently trades at $24.75, while our model-based Fair Value estimate is $60.69 — implying the stock looks roughly 145.2% undervalued today. We read business quality at 91/100 (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
Shibaura Machine Co.,Ltd. engages in the manufacture and sale of various machines in Japan and internationally. It operates through three segments: Molding Machinery, Machine Tools, and Control Systems. The company offers injection molding machines, die-casting machines, extrusion machines, nano processing systems, machine tools, Board Type PLC, servo motors, industrial robots, and IoT+m products, as well as provides additive manufacturing systems and engineering solutions. It also provides high precision machine tools, micro pattern imprinting machines, high precision glass mold press machines, and electronic control system. In addition, the company provides machine tools that include double column type machining centers, horizontal boring machines, vertical lathes, and other machine tools. Furthur, it is involved in the castings, heat treatment, and machining work activities. The company was formerly known as Toshiba Machine Co., Ltd. and changed its name to Shibaura Machine Co.,L…
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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.