Mercuries Data Systems Ltd (2427) Fair Value & Analysis
Industrials · TW · Market cap 4.5B TWD
Fair value as of: Jun 24, 2026
Analysis
Mercuries Data Systems Ltd (2427) currently trades at 22.40 TWD, while our model-based Fair Value estimate is 29.34 TWD — implying the stock looks roughly 31.0% 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
Mercuries Data Systems Ltd., together with its subsidiaries, engages in the sales, leasing, and maintenance of financial automation service machines in Taiwan. The company offers financial software systems, such as whitelist management, deposit machine management, device management, E-APT batching machine centralized management, multimedia reception service, teller safe management, and BTS financial branch terminal systems, as well as ATM operation integration platform; and financial automation products, including foreign exchange banknote exchange machine, professional payment kiosk, deposit machine, recycling cash dispenser, and automatic passbook printer. It also provides train dispatching radio systems; RF system for government; information technology services comprising medical information services, government procurement section, solutions for insurance industry, enterprise performance management solution, search and rescue dispatch system, 911 dispatch systems and emergency i…
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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.