Parade Technologies, Ltd (4966) Fair Value & Analysis
Technology · TW · Market cap 56.2B TWD
Fair value as of: Jun 24, 2026
Analysis
Parade Technologies, Ltd (4966) currently trades at 661.00 TWD, while our model-based Fair Value estimate is 714.13 TWD — implying the stock looks roughly 8.0% 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
Parade Technologies, Ltd., operates as a fabless semiconductor company in South Korea, China, Taiwan, Japan, and internationally. It engages in research and development, and marketing, and sale of high-speed interface standards, and touch controller and display processing integrated circuit (IC) chips for products used in computers, consumer electronics, and display panels. The company's products portfolio comprises datacenter active copper cables, high-speed interface ICs, including PCI Express/SATA, USBs, DisplayPorts, HDMIs, and protocol converters; display and touch integrated system ICs, such as touch embedded TCONs and source drivers, touch and gate level shifters, embedded DisplayPort timing controllers, display panel source drivers, Tcons with embedded source drivers and touch, touch and display driver integrated products, and DisplayPort LCD monitor controllers; truetouch touch screen controllers; and automotive ICs, such as touch with embedded drivers, USB, display protoco…
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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.