IBASE Technology Inc (8050) Fair Value & Analysis
Technology · TW · Market cap 11.5B TWD
Fair value as of: Jun 24, 2026
Analysis
IBASE Technology Inc (8050) currently trades at 55.40 TWD, while our model-based Fair Value estimate is 21.17 TWD — implying the stock looks roughly 61.8% overvalued today. We read business quality at 86/100 (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: medium).
About the company
IBASE Technology Inc. designs, manufactures, packages, tests, and sells industrial PCs in Taiwan and internationally. The company offers x86- and RISC-based industrial motherboards, single board computers, embedded fanless systems, edge computers, panel PCs, digital signage players, and network appliances for applications in the AIoT, industrial automation, smart retail, intelligent transportation, networking and communication, and medical sectors. It also provides original design manufacturing; joint design manufacturing; and design-in services, including hardware/software design, manufacturing, validation, and after-sales services, as well as outdoor panel PC and tablet. The company was incorporated in 2000 and is headquartered in Taipei, Taiwan.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is IBASE Technology Inc (8050) undervalued?
What is the fair value of 8050?
What is the quality score of 8050?
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.