Tetra Tech, Inc (TTEK) Fair Value & Analysis
Industrials · US · Market cap $7.3B
Analysis
Tetra Tech, Inc (TTEK) currently trades at $28.04, while our model-based Fair Value estimate is $27.20 — implying the stock looks roughly 3.0% overvalued today. We read business quality at 95/100 (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: high).
About the company
Tetra Tech, Inc. provides consulting and engineering services focusing on water, environment, and sustainable infrastructure in the United States and internationally. The company operates through two segments, Government Services Group (GSG) and Commercial/International Services Group (CIG). The GSG segment offers consulting and engineering services, including water resources analysis and water management, environmental monitoring, data analytics, government consulting, waste management, and civil infrastructure master planning and resilient engineering design for facilities, as well as transportation and local development projects primarily to government clients, including federal, state, and local, as well as international development agencies. It also offers sustainable solutions, such as energy management consulting, and greenhouse gas inventory assessment, certification, reduction, and management services. The CIG segment provides consulting and engineering services, including …
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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.