Andes Technology Corporation (6533) Fair Value & Analysis
Technology · TW · Market cap 10.2B TWD
Fair value as of: Jun 24, 2026
Analysis
Andes Technology Corporation (6533) currently trades at 204.50 TWD, while our model-based Fair Value estimate is 71.85 TWD — implying the stock looks roughly 64.9% overvalued today. We read business quality at 95/100 (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
Andes Technology Corporation provides embedded system application solutions. The company offers AndeStar Architecture, a patented 32-bit/64-bit RISC-style CPU architecture; AndesCore, a series of 32-bit/64-bit CPUs for use in embedded applications; AndesAIRE, a solutions designed for edge and end-point inference; AndeShape platform, a system development platform for various processors; AndeSight IDE, an eclipse-based embedded applications for compilers and linux support applications; and AndeSoft SW Stack, which provides a set of software components, such as real-time operating system, Linux kernel and drivers, libraries, middleware, and application frameworks. It is also involved in research, design, development, manufacturing, and sales of embedded microprocessor core intellectual property and related hardware; software development platforms and toolchains; silicon intelligence licenses; and silicon intelligence maintenance, as well as silicon intellectual property maintenance, cu…
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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.