Fairvalue-Calculator Fairvalue-Calculator
EN DE

Syntec Technology Co (7750) Fair Value & Analysis

Industrials · TW · Market cap 162B TWD

Price2,370 TWD
Fair Value668.30 TWD
Upside-71.8%
Quality95/100
Evidence: High Range 501.23 TWD – 1,158 TWD

Analysis

Syntec Technology Co (7750) currently trades at 2,370 TWD, while our model-based Fair Value estimate is 668.30 TWD — implying the stock looks roughly 71.8% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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: high).

About the company

Syntec Technology Co., Ltd. engages in the research and development, manufacturing, sales, and maintenance of industrial electronic automation controllers in Taiwan, Asia, and internationally. The company also offers design and technical service of maintenance for factory machinery automation systems. Its products include controllers, motors, and encoders, servo products for metalworking, woodworking, laser and other industries. In addition, the company offers machine tools, electronic control equipment, laser equipment, and electrical machinery. Syntec Technology Co., Ltd. was founded in 1995 and is based in Hsinchu City, Taiwan.

Open the full interactive analysis →

Similar stocks

Contemporary Amperex Technology Co (CYATY) -38% ABB Ltd (ABLZF) -65% Delta Group (DELTA) -90% Vertiv Holdings (VRT) -68% Mitsubishi Electric Corporation (MIELY) -53% LG Energy Solution, Ltd (373220) -86%

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.