Monadelphous Group (MND) Fair Value & Analysis
Industrials · AU · Market cap A$3.1B
Analysis
Monadelphous Group (MND) currently trades at A$30.12, while our model-based Fair Value estimate is A$17.57 — implying the stock looks roughly 41.7% 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
Monadelphous Group Limited, an engineering group, provides construction, maintenance, and industrial services to resources, energy, and infrastructure sectors in Australia, China, Mongolia, Papua New Guinea, China, Vietnam, the Philippines, and internationally. It operates through two segments, Engineering Construction, and Maintenance and Industrial Services. The company offers fabrication, modularization, offsite pre-assembly, procurement, and installation of structural steel, tankage, mechanical and process equipment, piping, demolition, and remediation works; multi-disciplined construction services; plant commissioning; electrical and instrumentation services; engineering, procurement, and construction services; process and non-process maintenance services; and front-end scoping, shutdown planning, management, and execution services. It also provides water and wastewater asset construction and maintenance; transmission pipelines and facilities construction; power and water asset…
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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.