IOI Corporation (IOIOF) Fair Value & Analysis
Consumer Defensive · US · Market cap $4.8B
Fair value as of: Jun 24, 2026
Analysis
IOI Corporation (IOIOF) currently trades at $0.7585, while our model-based Fair Value estimate is $0.5500 — implying the stock looks roughly 27.5% overvalued today. We read business quality at 92/100 (high quality), in the Consumer Defensive 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
IOI Corporation Berhad, an investment holding company, primarily engages in the plantation business in Malaysia, Europe, North America, Asia, and internationally. The company operates through two segments, Plantation and Resource-Based Manufacturing. It cultivates oil palm, softwood timber, rubber, and coconut; refines and processes crude palm, crude coconut, and palm kernel oils; and manufactures specialty oils and fats. The company also manufactures and exports fatty acids, soap noodles, glycerin, fatty esters, and other related products. In addition, it is involved in the commercialization of clonal ramets, tissue culturing process and biotechnology related research and development activities; provision of management and marketing services; production and supply of palm-based renewable energy; and trading of palm oil commodities, oilseeds, and edible oils and fats; and the processing of raw materials for the edible oils and fats industry. Further, the company engages in the prope…
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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.