Indorama Ventures Public Company (IVL) Fair Value & Analysis
Basic Materials · TH · Market cap 127B THB
Analysis
Indorama Ventures Public Company (IVL) currently trades at 21.10 THB, while our model-based Fair Value estimate is 24.90 THB — implying the stock looks roughly 18.0% undervalued today. We read business quality at 92/100 (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: medium) — always confirm before acting.
About the company
Indorama Ventures Public Company Limited, together with its subsidiaries, manufactures and distributes petrochemical products in Thailand, the United States, Brazil, and internationally. It operates through four segments: Combined PET, Indovida, Indovinya, and Fibers. The Combined PET segment manufactures and distributes polyethylene terephthalate (PET) value chain comprising paraxylene, purified terephthalic acid, PET, and recycling; and specialty PET-related chemicals, such as purified isophthalic acid and naphthalene dicarboxylate. The Indovida segment manufactures and distributes packaging. The Indovinya segment offers specialty chemical solutions including home and personal care, crop solutions, coatings, and energy and resources; supply ethylene oxide to the Combined PET business; and manufactures and distributes integrated downstream surfactants. The Fibers segment offers polyester, rayon, nylon, polypropylene, composites, and worsted wool fibers for the home, apparel, hygien…
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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.