Formosa Prosonic Industries Berhad, (9172) Fair Value & Analysis
Technology · MY · Market cap 251M MYR
Fair value as of: Jun 25, 2026
Analysis
Formosa Prosonic Industries Berhad, (9172) currently trades at 0.8850 MYR, while our model-based Fair Value estimate is 1.95 MYR — implying the stock looks roughly 120.3% undervalued today. We read business quality at 95/100 (high quality), in the Technology 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: high) — always confirm before acting.
About the company
Formosa Prosonic Industries Berhad, together with its subsidiaries, manufactures and sells speaker system products in Malaysia. The company offers consumer and home entertainment products, including portable and outdoor speakers, sound bars, home theater systems, ambient room wireless and bookshelf speakers, and TV stands. It also provides musical instrument solutions comprising acoustic pianos, guitar amplifiers, drum sets, and synthesizers. In addition, the company offers automotive solutions consisting of car speakers and subwoofers solutions. Further, it provides furniture solutions, such as study desks, cupboards, pet homes, and TV cabinets. Additionally, the company offers engineering and design services, plastic components, and transducers, as well as manufactures and sells speaker driver units; and provides in-house assembly and woodworking. Formosa Prosonic Industries Berhad was incorporated in 1988 and is headquartered in Port Klang, 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.