Mattr Corp (MATR) Fair Value & Analysis
Energy · CA · Market cap C$799M
Fair value as of: Jun 24, 2026
Analysis
Mattr Corp (MATR) currently trades at C$12.30, while our model-based Fair Value estimate is C$8.55 — implying the stock looks roughly 30.5% overvalued today. We read business quality at 95/100 (high quality), in the Energy 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
Mattr Corp. operates as a materials technology company that serves the infrastructure markets, including electrification, transportation, mining, energy, communication and water management markets in Canada, the United States, Europe, the Middle East, Africa, and the Asia Pacific. It operates in two segments: Composite Technologies and Connection Technologies. The Composite Technologies segment manufactures flexible composite pipes used for oil and gas gathering lines and other applications under the Flexpipe brand; and fiberglass reinforced plastic fuel and water underground storage tanks, as well as HydroChain stormwater management products, including infiltration chambers for the retail fuel, water, stormwater and wastewater, and oil and gas markets under the Xerxes brand. The Connection Technologies segment manufactures heat-shrinkable products, including thin, medium, and heavy-walled tubing; sleeves and molded products, as well as heat-shrink accessories and equipment; manufac…
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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.