Focus Universal Inc (FCUV) Fair Value & Analysis
Technology · US · Market cap $1.6M
Fair value as of: Jun 24, 2026
Analysis
Focus Universal Inc (FCUV) currently trades at $4.11, while our model-based Fair Value estimate is $2.75 — implying the stock looks roughly 33.1% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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: low).
About the company
Focus Universal Inc. develops and commercializes universal smart technologies and instruments in the United States. The company operates in two segments, Perfecular & Lusher and Corporate & IoT. It offers Ubiquitor, a handheld, fully modular system with a universal sensor node and gateway system; and smart home installation, such as smart devices for lighting control, air conditioner control, sprinkler control, garden light control, garage door control, and heating control. The company is also involved in the research and development of device on a chip technology; 5G ultra-narrowband technology; ultra-narrowband power line communication technology; user interface machine auto generation platform; and universal smart instrumentation hardware and software platform. In addition, the company develops scientific sensors, including quantum photosynthetic active radiation sensors, TDS sensors, pH sensors, total dissolved oxygen sensors, pressure sensors, ORP sensors, temperature sensors, …
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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.