Hiap Huat Holdings (0160) Fair Value & Analysis
Energy · MY · Market cap 41.5M MYR
Fair value as of: Jun 26, 2026
Analysis
Hiap Huat Holdings (0160) currently trades at 0.1050 MYR, while our model-based Fair Value estimate is 0.1600 MYR — implying the stock looks roughly 52.4% undervalued today. We read business quality at 95/100 (high quality), in the Energy 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
Hiap Huat Holdings Berhad, together with its subsidiaries, manufactures, recycles, and refines petroleum-based products in Malaysia, Singapore, Vietnam, Finland, and Italy. The company offers fuel and base oils, diesel, and bitumen; mixed aromatic and alcohol solvents, as well as glycol; refined used cooking, palm acid, tyre pyrolysis, pome, and plastic pyrolysis oils, as well as refined brown grease; and recycled metal/PVC drum and IBC. It also provides scheduled waste management, including collection, treatment, and conversion of hazardous waste; liquid bulk terminal solutions and storage options for petroleum, petrochemicals, and biofuels; petroleum, petrochemical, and sustainable products refining; and laboratory and testing services. In addition, the company engages in the manufacturing, recycling, and refining of various industrial paints; leasing of machinery and equipment; and physical refining, processing, pre-treatment, recovery, reuse, and trading of waste and residues, a…
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Frequently asked questions
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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.