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MicroVision Second Quarter 2025 Earnings: EPS Beats Expectations, Revenues Lag
MicroVision (NASDAQ:MVIS) Second Quarter 2025 Results
Key Financial Results
- Net loss: US$14.2m (loss narrowed by 41% from 2Q 2024).
- US$0.056 loss per share (improved from US$0.12 loss in 2Q 2024).
All figures shown in the chart above are for the trailing 12 month (TTM) period
MicroVision EPS Beats Expectations, Revenues Fall Short
Revenue missed analyst estimates by 74%. Earnings per share (EPS) exceeded analyst estimates by 7.7%.
Looking ahead, revenue is forecast to grow 89% p.a. on average during the next 3 years, compared to a 8.1% growth forecast for the Electronic industry in the US.
Performance of the American Electronic industry.
The company's share price is broadly unchanged from a week ago.
Risk Analysis
We don't want to rain on the parade too much, but we did also find 4 warning signs for MicroVision (1 can't be ignored!) that you need to be mindful of.
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Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) simplywallst.com.
This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
About NasdaqGM:MVIS
MicroVision
Develops and commercializes perception solutions for autonomy and mobility applications.
Flawless balance sheet with low risk.
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StevenM on Excellon Resources ·
Interesting analysis, but the price trajectory assumed for the baseline metals is problematic. These assumptions form the foundation for the entire case, and when compared against historical pricing, don’t appear to be grounded in any reasonable precedent. Even accounting for past commodity super-cycles, inflationary periods, or supply constraints, the forecasted pricing for gold, silver, zinc, and lead are well outside what history would suggest is plausible over comparable timeframes. That creates a fragile premise as the conclusions are driven by aggressive inputs rather than underlying market behavior that is realistic. The analysis would be materially stronger if the price assumptions were anchored to historical ranges and prior cycle peaks, with explicit rationale where the model intentionally departs from those patterns. As it stands, the trajectory feels more aspirational than analytical.
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