Sanlien Technology Corp (5493) Fair Value & Analysis
Technology · TW · Market cap 4.1B TWD
Fair value as of: Jun 24, 2026
Analysis
Sanlien Technology Corp (5493) currently trades at 90.00 TWD, while our model-based Fair Value estimate is 102.32 TWD — implying the stock looks roughly 13.7% undervalued today. We read business quality at 80/100 (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: medium) — always confirm before acting.
About the company
Sanlien Technology Corp. manufactures and sells specialty chemical for the semiconductor industry in Taiwan, Asia, and internationally. It operates through Automatic Monitoring Business, Electronic Material Business, Overseas Sensing and Equipment Business, and Other segments. The company offers smart seismic switch, accelerometer, vibrating wire converter, piezometer, rebar strain gauge, arc-weldable strain gauge, spot-weldable strain gauge, standard/inclinometer casing, annular/solid load cell, embedment strain gauge, crackmeter, earth pressure cell, tiltmeter, multi-point liquid level meter, in-place inclinometer, and load cell. It also provides onsite control and display interface, earthquake central data logger and control unit, dynamic datalogger, vibrating wire sensor and wheatsone bridge datalogger, inclination sensor, rainfall datalogger; and web monitoring tool and software, including SanDAS, dot cloud, and web monitoring system. In addition, the company offers force, grea…
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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.