Melrose Industries PLC (MRO) Fair Value & Analysis
Industrials · GB · Market cap 5.8B GBX
Analysis
Melrose Industries PLC (MRO) currently trades at p4.75, while our model-based Fair Value estimate is p5.11 — implying the stock looks roughly 7.6% 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
Melrose Industries PLC, together with its subsidiaries, designs and delivers aerospace components and systems for civil and defence markets in the United Kingdom, rest of Europe, North America, and internationally. The company operates through Engines and Airframes segments. The Engines segment offers structural engineered components; parts repair; commercial and aftermarket contracts; engine mount structures; fan cases and turbine cases; and shafts and rotating components to engines original equipment manufacturers. The Airframes segment provides civil and defence air frames, including lightweight composite and metallic structures; electrical distribution systems and components; wing structures; empennage; fuselage; electrical wiring interconnection systems ("EWIS"); landing gear and ice protection systems; and aircraft transparencies to airframe original equipment manufacturers. The company was formerly known as New Melrose Industries PLC and changed its name to Melrose Industries…
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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.