Vaisala Oyj (VAIAS) Fair Value & Analysis
Technology · FI · Market cap €2.0B
Fair value as of: Jun 24, 2026
Analysis
Vaisala Oyj (VAIAS) currently trades at €54.20, while our model-based Fair Value estimate is €33.68 — implying the stock looks roughly 37.9% 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: high).
About the company
Vaisala Oyj provides weather, environmental, and industrial measurement for weather and industrial markets in North and South America, Europe, the Middle East, Africa, and the Asia Pacific. It offers Origo, a modular HVAC transmitters; Vaisala Circular, a probe recalibration and reuse service; Elements Lite for weather intelligence; and WindCube 2.1 XP that delivers wind resource data. The company also provides carbon dioxide, cloud height, dew point, dissolved gas in oil, humidity, hydrogen, lightning, liquid concentration, methane, moisture in oil, precipitation, pressure, road and runway surface condition, solar irradiation, structural moisture, temperature, vaporized hydrogen peroxide, visibility and present weather, data loggers, handhelds, HVAC and industrial transmitters, monitoring systems, power transformer monitoring, probes and OEM modules, process refractometers, radiosondes and sounding systems, weather and environmental sensors, weather API and mapping, weather station…
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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.