Chin Hin Group (7187) Fair Value & Analysis
Consumer Cyclical · MY · Market cap 1.5B MYR
Fair value as of: Jun 24, 2026
Analysis
Chin Hin Group (7187) currently trades at 1.06 MYR, while our model-based Fair Value estimate is 0.9000 MYR — implying the stock looks roughly 15.1% overvalued today. We read business quality at 94/100 (high quality), in the Consumer Cyclical 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
Chin Hin Group Property Berhad, together with its subsidiaries, engages in the property development business in Malaysia. It operates through Commercial Vehicles and Bodyworks; Property Development; Construction; and Others segments. The company engages in rental of commercial vehicles; property construction; and activities, manufactures, assembles, and trades in rebuilt and new commercial vehicles, as well as manufactures and trades in rebuilt and new commercial vehicles. It also provides management, fleet management, and other related services, as well as sells and rents commercial vehicles. In addition, the company engages in import, export, buys, sale, hire, and deals in new, used, and second hand vehicles and other related goods and services; rent, hire, repair, and deals in forklifts, heavy equipment, machineries, component parts, and attachments and accessories; manufacture of trailers and semi-trailers; housing development; and manufacture of bodies for motor vehicles. The c…
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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.