Turbo Energy, S.A (TURB) Fair Value & Analysis
Technology · US · Market cap $16.5M
Fair value as of: Jun 24, 2026
Analysis
Turbo Energy, S.A (TURB) currently trades at $1.37, while our model-based Fair Value estimate is $0.4500 — implying the stock looks roughly 67.2% 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
Turbo Energy, S.A. designs, develops, and distributes equipment for the generation, management, and storage of photovoltaic energy in Spain, rest of Europe, and internationally. The company offers lithium-ion batteries; inverters; photovoltaic modules; Go Solar, a portable photovoltaic product; and Sunbox, an AI based software system that monitors the generation, use, and management of photovoltaic energy. It is also involved in the acquisition, distribution, and sale of electrical and electronic materials for the development of renewable energy projects, such as solar panels, inverters, chargers, regulators, batteries, and structures. The company sells its products to installers and distributors for residential consumers. The company has a strategic partnership with Xiamen HiTHIUM Energy Storage Technology Co. Ltd. for the deployment of software-defined energy storage infrastructure across commercial and industrial applications in Europe and Latin America. The company was incorpora…
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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.