Aida Engineering, Ltd (ADERY) Fair Value & Analysis
Industrials · US · Market cap $363M
Fair value as of: Jun 25, 2026
Analysis
Aida Engineering, Ltd (ADERY) currently trades at $66.75, while our model-based Fair Value estimate is $108.22 — implying the stock looks roughly 62.1% 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
Aida Engineering, Ltd. manufactures and sells press machines, auto-processing lines, industrial robots, auto-conveyers, and dies in Japan, China, rest of Asia, the Americas, and Europe. It offers general-purpose servo, mid-size and large servo, general-purpose, mid-size and large, precision forming, high speed automatic, and cold forging presses, as well as transfer equipment, coil feeders, and tooling dies. The company also provides troubleshooting/spare parts, retrofit/modernization, routine inspection, and overhaul/machine relocation services. In addition, it offers piling systems, servo motors, servo drive technologies, material feeders, die-forming methods, servo die cushions, and line synchronization control technologies. The company was formerly known as AIDA Ironworks and changed its name to Aida Engineering, Ltd. in 1970. Aida Engineering, Ltd. was founded in 1917 and is headquartered in Sagamihara, Japan.
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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.