Ambipar Emergency Response (AMBIQ) Fair Value & Analysis
Industrials · US · Market cap $5.5M
Fair value as of: Jun 26, 2026
Analysis
Ambipar Emergency Response (AMBIQ) currently trades at $0.0900, while our model-based Fair Value estimate is $0.0724 — implying the stock looks roughly 19.6% overvalued today. We read business quality at 82/100 (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
Ambipar Emergency Response provides environmental, emergency response and industrial field service in Brazil and internationally. The company provides emergency response and industrial field service, including response to accidents involving hazardous and non-hazardous chemical and non-chemical products and waste and natural disasters, as well as tank cleaning, silo cleaning, asbestos removal, vessel and container cleaning, waste transportation and disposal, soil remediation, turnaround, and decommissioning. It also offers biological emergency management and response services, such as epidemics and pandemics; consulting services, including accident prevention and environmental licensing; and training services to preventing, fighting, and remediating emergencies. The company is headquartered in São Paulo, Brazil. Ambipar Emergency Response is a subsidiary of Ambipar Participações e Empreendimentos S.A. On October 20, 2025, Ambipar Emergency Response a voluntary petition for reorganiz…
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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.