Advantest Corporation (ADTTF) Fair Value & Analysis
Technology · US · Market cap $109B
Analysis
Advantest Corporation (ADTTF) currently trades at $195.31, while our model-based Fair Value estimate is $61.35 — implying the stock looks roughly 68.6% overvalued today. We read business quality at 97/100 (high quality), in the Technology 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
Advantest Corporation, together with its subsidiaries, manufactures and sells semiconductors, component test systems, and mechatronics-related products in Japan, rest of Asia, the Americas, and Europe. The company offers automated test equipment, including system on chip, power device, and memory test systems, as well as burn-in and SSD test systems; and metrology and SEM tools. It also provides component test systems, such as die level, SoC, and memory test handlers, as well as change kits, and pressure sensor stimulus; device interface for memory; test cell and automation solutions; system level test systems; device certification test systems; semiconductor failure analysis systems; and interconnect solutions, including test interface boards, substrates, test sockets, and thermal control units. In addition, the company offers cloud solutions comprising digital twin software, real-time data infrastructure, dynamic parametric test, and test engineering; and SiConic offerings, such a…
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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.