WITS Corp (4953) Fair Value & Analysis
Technology · TW · Market cap 9.7B TWD
Fair value as of: Jun 24, 2026
Analysis
WITS Corp (4953) currently trades at 128.50 TWD, while our model-based Fair Value estimate is 173.33 TWD — implying the stock looks roughly 34.9% 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: high) — always confirm before acting.
About the company
WITS Corp., together with its subsidiaries, provides information technology (IT) services in Taiwan, Mainland China, Japan, the United States, and internationally. The company offers software research and development, and testing; system operations and maintenance; and software and technology consulting services that delivers artificial intelligence, big data, blockchain, cloud services, IoT, and information security. It also provides digital transformation consultation and solution services; integration of digital tools and platforms; carbon neutrality solutions; business process outsourcing services for telemarketing, client service centers, data centers, financial and HR operations, member applications and services, and search engine optimization services; centralized management system; and transactional processing, including data extraction, data input and correction, data annotation, and data review. In addition, the company offers product globalization services comprising mult…
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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.