Vp plc (VP) Fair Value & Analysis
Industrials · GB · Market cap 187M GBX
Fair value as of: Jun 24, 2026
Analysis
Vp plc (VP) currently trades at p4.80, while our model-based Fair Value estimate is p5.46 — implying the stock looks roughly 13.8% 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
Vp plc provides equipment rental and related services in the United Kingdom and internationally. The company provides materials handling solutions, including telehandlers and plant and equipment for residential housebuilding; and supports upstream projects with pipeline, infrastructure maintenance, and well testing services, as well as downstream projects, including industrial shutdowns and space monitoring solutions. It also offers rail services comprising track renewals, maintenance, and other projects, as well as plant and tools for rail; undertakes pipeline, sewer rehabilitation, reservoir and facility enhancement, and treatment plant upgrade projects; and provides pipeline solutions and site access through portable roadways, as well as survey, test and measurement, and groundwork services. In addition, the company undertakes rail, highways, utilities, and other infrastructure projects; supports non-residential construction projects, including commercial offices, warehousing, an…
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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.