Godex International Co (4987) Fair Value & Analysis
Technology · TW · Market cap 2.6B TWD
Fair value as of: Jun 24, 2026
Analysis
Godex International Co (4987) currently trades at 81.60 TWD, while our model-based Fair Value estimate is 124.27 TWD — implying the stock looks roughly 52.3% undervalued today. We read business quality at 95/100 (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: high) — always confirm before acting.
About the company
Godex International Co., Ltd engages in the research and development, manufacture, and sale of barcode label printers and peripheral parts worldwide. It offers desktop, industrial, and mobile printers; tube labeling systems; print mechanisms; accessories; specialty products; accessories; and ribbons, including wax, wax/resin, resin, and near-edge ribbons. The company also provides software solutions under the GoRibbon, GoLabel, GoLabel PDF, QLabel, GoAPP, and GoUtility names. Its products are used in the healthcare, retail, logistics and transportation, manufacturing, government, travel and leisure, and special material applications. The company offers its products through a network of value-added resellers. Godex International Co., Ltd was founded in 1993 and is headquartered in New Taipei City, Taiwan.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is Godex International Co (4987) undervalued?
What is the fair value of 4987?
What is the quality score of 4987?
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.