Tien Wah Press Holdings (7374) Fair Value & Analysis
Industrials · MY · Market cap 108M MYR
Fair value as of: Jun 24, 2026
Analysis
Tien Wah Press Holdings (7374) currently trades at 0.7650 MYR, while our model-based Fair Value estimate is 0.9800 MYR — implying the stock looks roughly 28.1% undervalued today. We read business quality at 95/100 (high quality), in the Industrials 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
Tien Wah Press Holdings Berhad, an investment holding company, provides rotogravure and photolithography printing services in Singapore, Indonesia, Korea, Australasia, Malaysia, Vietnam, the Middle East, and internationally. The company offers printed cartons and labels to customers in the tobacco and other fast-moving consumer goods industries. Its product portfolio includes flat unglued blanks; crash bottom or autolock cartons; labelled cartons; cartons with peelable labels/stickers; clamshells and trays; uv coated cartons; glued skillet cartons; multi wall cartons comprising innerframers; carton with CD inserts; and barrier coated carton for grease/moisture resistance. The company also engages in packing and packaging services; food and beverages; event management; manufacture of packing and packaging materials; trading of cigarette packaging boxes; and supply of printing products, as well as offers paper services. Tien Wah Press Holdings Berhad was founded in 1960 and is based i…
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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.