Wasion Holdings (WSIOF) Fair Value & Analysis
Industrials · US · Market cap $3.4B
Fair value as of: Jun 25, 2026
Analysis
Wasion Holdings (WSIOF) currently trades at $3.31, while our model-based Fair Value estimate is $3.15 — implying the stock looks roughly 4.7% overvalued today. We read business quality at 80/100 (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: medium).
About the company
Wasion Holdings Limited, an investment holding company, engages in the research and development, production, and sale of energy metering and energy efficiency management solutions for energy supply industries. The company operates through three segments: Smart grid solutions, AI-integrated energy efficiency solutions, and Digital energy services. Its Smart grid solutions segment offers power metering infrastructure to provides full-stack intelligent solutions for power grid planning, operation, monitoring, maintenance, and optimization by leveraging intelligence technologies, such as artificial intelligence and machine learning. The AI-integrated energy efficiency solutions segment is involved in the manufacture, sale of communications and fluid metering products with deeply integrates digitalization and intelligent technologies, incorporates AI algorithms, and provides customers with comprehensive energy efficiency analysis, management, and optimization services. Its Digital energy…
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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.