MAYO Human Capital Inc (6738) Fair Value & Analysis
Technology · TW · Market cap 2.4B TWD
Fair value as of: Jun 24, 2026
Analysis
MAYO Human Capital Inc (6738) currently trades at 65.70 TWD, while our model-based Fair Value estimate is 35.01 TWD — implying the stock looks roughly 46.7% 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: low).
About the company
MAYO Human Capital Inc. provides cloud-based human resources solutions services, cloud-based employee welfare integration services, electronic information supply services, and data processing primarily in Taiwan and Vietnam. The company offers apollo human resources management system, payroll outsourcing services, group-style operation solutions, high-tech manufacturing solutions, food and beverage/retail/service solutions, software/project/remote solutions, Taiwanese business multinational management solutions, foreign investor local management solutions, growth-oriented startup solutions, professional services solutions, and cloud-based paperless solutions. It also provides STAYFUN, an employee benefits integration platform that offers a variety of options for gifts and employee benefits. In addition, the company offers Cornerstone, an integrated cloud platform. MAYO Human Capital Inc. was founded in 2013 and is headquartered in Taipei, Taiwan.
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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.