Data I/O Corporation (DAIO) Fair Value & Analysis
Technology · US · Market cap $34.9M
Fair value as of: Jun 24, 2026
Analysis
Data I/O Corporation (DAIO) currently trades at $3.85, while our model-based Fair Value estimate is $4.40 — implying the stock looks roughly 14.3% undervalued today. We read business quality at 95/100 (high quality), in the Technology 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: low) — always confirm before acting.
About the company
Data I/O Corporation, together with its subsidiaries, engages in the design, manufacture, and sale of programming and security deployment systems and services for electronic device manufacturers in the United States, Germany, China, Mexico, and Korea. The company offers PSV systems off-line automated programming systems; PSV7000 high-mix automated programming system; and PSV5000 compact automated programming system, as well as LumenX and FlashPAK III programming non-automated systems. It offers its products for automotive electronics, medical devices, industrial controls, military/aerospace, semiconductor, consumer products, internet of things, wireless devices, edge AI, EMS and contract manufacturers, and programming centers industries. The company markets and sells its products to original equipment manufacturers in automotive and consumer electronics, internet of things, and industrial, as well as electronic manufacturing service contract manufacturers through direct sales, indir…
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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.