Forterra plc (FORT) Fair Value & Analysis
Basic Materials · GB · Market cap 284M GBX
Fair value as of: Jun 24, 2026
Analysis
Forterra plc (FORT) currently trades at p1.32, while our model-based Fair Value estimate is p2.20 — implying the stock looks roughly 66.4% undervalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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
Forterra plc, together with its subsidiaries, provides building products made from clay and concrete for the construction sector in the United Kingdom. It operates through Bricks and Blocks; and Bespoke Products segments. The company offers fletton, extruded wirecut, soft mud, semi-dry pressed, and special shaped bricks; aircrete and aggregate blocks; façade systems, such as lightweight and brick slip cladding systems, prefabricated walling systems, and retained brick slip systems; precast concrete products, such as Jetfloor insulated ground floors, hollowcore and solid floors, beam and block floors, stairs and landings, and diesel transfer slabs; box culverts, bridge decks and retaining walls for infrastructure, crosswall frames, stadia components, and columns and beams for structural projects; chimney pots, clay ridge tiles, finials, gas flue terminals, and flue systems; and permeable block pavings. It sells its products under the London Brick, Butterley, Ecostock, Cradley, Omnia,…
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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.