OPNET Technologies Co (8034) Fair Value & Analysis
Technology · TW · Market cap 1.3B TWD
Fair value as of: Jun 24, 2026
Analysis
OPNET Technologies Co (8034) currently trades at 23.00 TWD, while our model-based Fair Value estimate is 28.46 TWD — implying the stock looks roughly 23.7% 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
OPNET Technologies Co., Ltd. designs, manufactures, and markets telecommunication network access and optical transport equipment in Taiwan, Turkey, and internationally. It operates through Access Network and Broadband Equipment, Transmission Equipment, and Other segments. The company engages in research, development, production, manufacturing, and sales of fiber optic broadband user access network systems, synchronous and asynchronous digital transmission multiplexers, high-speed, asymmetric and symmetric digital user loop systems, broadband modems, routers and access systems, broadband wireless communication equipment, digital data and voice integrated access equipment, fiber optic communication systems, and the system planning, construction, and after-sales service. It also offers access network products, transmission network products, enterprise network, distribution network, and fiber optic sensor solution. It serves incumbent fixed-network operators, mobile operators, cable TV …
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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.