Civmec Limited (CVL) Fair Value & Analysis
Industrials · AU · Market cap A$897M
Analysis
Civmec Limited (CVL) currently trades at A$1.99, while our model-based Fair Value estimate is A$1.75 — implying the stock looks roughly 11.8% 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
Civmec Limited, an investment holding company, provides construction and engineering services to the energy, resources, infrastructure, marine, and defense sectors in Australia. It undertakes fabrication projects, such as structural steel, plateworks, tanks, vessels, materials handling equipment, subsea and offshore structures, and pipe spooling services. It offers modularization services; shipbuilding services; site civil works, including earthworks, reinforcing steel works, formworks, detailed civil works, concrete placement, and backfill and compaction to final handover services; and reinforced concrete products comprising prestressed beams, parapets, structural foundations, caissons, floor slabs and retaining walls, suspended slab sections, purpose-built facilities, and breakwater systems. In addition, the company undertakes structural, mechanical, and piping works consisting of structural erection, mechanical installations and alignments, piping installation and pre-commissioni…
Open the full interactive analysis →
Similar stocks
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.