3239 (3239) Fair Value & Analysis
Industrials · MY · Market cap 755M MYR
Fair value as of: Jun 26, 2026
Analysis
3239 (3239) currently trades at 0.3000 MYR, while our model-based Fair Value estimate is 0.1000 MYR — implying the stock looks roughly 66.7% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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: medium).
About the company
Berjaya Assets Berhad, an investment holding company, primarily engages in the property development and investment business in Malaysia and internationally. It operates through Property Development and Property Investment; Gaming and Related Activities; and Recreation and Others segments. The company engages in the investment, development, management, and leasing of properties; operation of a hotel, theme park, and car park; management of a ferry terminal; leasing of theatre; vehicle assembly and manufacture and sale of engines and transmissions; and general trading and commission agent operations, as well as operates number forecast lotteries. It also offers lottery consultancy, automotive engineering, and vehicle assembly and parts supply services. The company was formerly known as Matrix International Berhad and changed its name to Berjaya Assets Berhad in August 2009. Berjaya Assets Berhad was incorporated in 1960 and is headquartered in Kuala Lumpur, Malaysia.
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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.