Granite Construction Incorporated (GVA) Fair Value & Analysis
Industrials · US · Market cap $6.2B
Analysis
Granite Construction Incorporated (GVA) currently trades at $150.08, while our model-based Fair Value estimate is $91.01 — implying the stock looks roughly 39.4% overvalued today. We read business quality at 94/100 (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
Granite Construction Incorporated provides infrastructure solutions for public and private clients in the United States. It operates through Construction and Materials segments. The Construction segment engages in the construction and rehabilitation of roads, pavement preservation, bridges, rail lines, airports, marine ports, dams, reservoirs, aqueducts, infrastructure, and site development for use by the public and water-related construction for municipal agencies, commercial water suppliers, industrial facilities, and energy companies; and construction of various complex projects, including infrastructure and site development, mining, public safety, tunnel, solar, battery storage, and power related projects. The Materials segment produces and delivers aggregates, asphalt concrete, liquid asphalt, and recycled materials for internal use in construction projects and sale to third parties. It also provides site preparation, mining, and infrastructure services for railways, residentia…
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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.