Orbia Advance Corporation (MXCHF) Fair Value & Analysis
Industrials · US · Market cap $2.7B
Analysis
Orbia Advance Corporation (MXCHF) currently trades at $1.30, while our model-based Fair Value estimate is $1.64 — implying the stock looks roughly 26.2% undervalued today. We read business quality at 88/100 (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
Orbia Advance Corporation, S.A.B. de C.V., together with its subsidiaries, provides polymer solutions in the United States, Northwest Europe, Southwest Europe, Africa, the Middle East, Asia, Brazil, Mexico, Central and Eastern Europe, Colombia, Central America, Peru, Southeast Europe, Canada, Ecuador, Israel, Argentina, Chile, and internationally. It operates in five segments: Polymer Solutions, Building and Infrastructure, Precision Agriculture, Connectivity Solutions, and Fluor and Energy Materials. The company offers derivatives comprising ethylene, salt, chlorine, caustic soda, methyl and ethyl chloride, hydrochloric acid, and sodium hypochlorite; general-purpose and specialty polyvinyl chloride resins; and plastic compounds. It also provides plastic piping systems and solutions; high-density polyethylene conduit, accessories, and other connectivity infrastructure products; digital education and fiber-optic network design services; sprinklers, micro-sprinklers, drippers, drip li…
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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.