Axalta Coating Systems Ltd (AXTA) Fair Value & Analysis
Basic Materials · US · Market cap $6.7B
Analysis
Axalta Coating Systems Ltd (AXTA) currently trades at $33.64, while our model-based Fair Value estimate is $16.90 — implying the stock looks roughly 49.8% overvalued today. We read business quality at 94/100 (high quality), in the Basic Materials 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
Axalta Coating Systems Ltd., through its subsidiaries, manufactures, markets, and distributes high-performance coatings systems in North America, Europe, the Middle East, Africa, the Asia Pacific, and Latin America. The company operates through two segments, Performance Coatings and Mobility Coatings. It also offers water and solvent-borne products and systems to repair damaged vehicles for independent body shops, multi-shop operators, and original equipment manufacturers (OEM) dealership body shops. In addition, the company provides functional and decorative liquid, and powder coatings for building materials, cabinet, wood and luxury vinyl flooring, and furniture applications under the Imron Industrial, Tufcote Industrial, Corlar Industrial, Strenex Industrial, PercoTop, Voltatex, AquaEC, Durapon, Hydropon, UNRIVALED, Ceranamel, Alesta, Teodur, Nap-Gard, Abcite, and Plascoat brands. Further, it develops and supplies electrocoat, primer, the basecoat, and clearcoat products for OEMs…
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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.