Técnicas Reunidas, S.A (TNISY) Fair Value & Analysis
Industrials · US · Market cap $2.8B
Analysis
Técnicas Reunidas, S.A (TNISY) currently trades at $7.25, while our model-based Fair Value estimate is $9.21 — implying the stock looks roughly 27.0% undervalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Técnicas Reunidas, S.A., an engineering and construction company, designs and manages industrial plant projects worldwide. It operates through Upstream & Refining, Natural gas, Petrochemical, Low-carbon technologies, and Other segments. The Refining segment offers management, engineering, procurement, construction and commissioning services for facilities along the entire value chain to produce fuels. The Natural gas segment provides direction, management, engineering, procurement, construction and commissioning services for facilities throughout the supply chain, from natural gas production to regasification terminals; and treatment and processing plants, compressor and liquefaction stations, storage tanks, and final regasification facilities. The Petrochemical segment provides direction, management, engineering, procurement, construction and startup services for facilities dedicated to the production of basic chemical materials used in water distribution, pharmaceuticals, health, …
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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.