SIG plc (SIIGF) Fair Value & Analysis
Industrials · US · Market cap $185M
Fair value as of: Jun 26, 2026
Analysis
SIG plc (SIIGF) currently trades at $0.1600, while our model-based Fair Value estimate is $0.4600 — implying the stock looks roughly 187.5% undervalued today. We read business quality at 91/100 (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: medium) — always confirm before acting.
About the company
SIG plc supplies specialist insulation and sustainable construction products and solutions in the United Kingdom, Ireland, France, Germany, Poland, and Benelux. The company offers insulation and interiors products, including structural and technical insulations, construction accessories and fixings, cladding and façade systems, dry lining, ceiling tiles and grids, partition walls and door sets, and floor coverings, as well as tools and fixings, ventilation, access equipment, and safety products. It provides roofing and exterior products, such as tiles, slates, membranes, battens for pitched roofs, single-ply flat roof systems, industrial roofing products, cladding systems, room-in-roof panel systems, and photovoltaic panels, as well as industrial painting, coating, and repair services. It serves developers, specialist contractors, specialist installers, and independent merchants. The company was formerly known as Sheffield Insulations Limited. SIG plc was founded in 1957 and is base…
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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.