104 Corporation (3130) Fair Value & Analysis
Industrials · TW · Market cap 7.4B TWD
Fair value as of: Jun 24, 2026
Analysis
104 Corporation (3130) currently trades at 222.50 TWD, while our model-based Fair Value estimate is 258.01 TWD — implying the stock looks roughly 16.0% undervalued today. We read business quality at 95/100 (high quality), in the Industrials 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
104 Corporation engages in the information technology, general advertising, employment, and human resource consultancy services in Taiwan and internationally. It offers online recruitment, advertising, learning, HR Salary management system, HR assessment, and executive search services. The company provides career placement and career service, educational services for career development, employer branding and customized integrated recruitment, talent acquisition and recruitment, personal career analysis and career counseling, executive and key talent pool, and platform for seniors, as well as HR system tools and solutions. In addition, it offers IT software, electronic information, talent dispatching, and data processing services. Further, the company develops network technologies and computer software; sell products; and provides technical advice and services, as well as management consultancy. The company was formerly known as Fu-Hwa International Market Development Consultant Ltd.…
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is 104 Corporation (3130) undervalued?
What is the fair value of 3130?
What is the quality score of 3130?
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.