Chung Hwa Pulp Corporation (1905) Fair Value & Analysis
Basic Materials · TW · Market cap 14.2B TWD
Fair value as of: Jun 25, 2026
Analysis
Chung Hwa Pulp Corporation (1905) currently trades at 17.35 TWD, while our model-based Fair Value estimate is 9.80 TWD — implying the stock looks roughly 43.5% overvalued today. We read business quality at 86/100 (high quality), in the Basic Materials 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: low).
About the company
Chung Hwa Pulp Corporation manufactures, sells, and distributes pulp, paper, paperboard, chemical products, and fertilizers in Taiwan and Mainland China. The company is involved in the cultivation and sales of seedlings, afforestation, logging, and other forestry activities; tape, specialty chemicals, and forestry and agriculture products; and production and sales of non-long fiber pulp, long fiber pulp, and writing. It engages in the trading, printing, and sales of various paper products related to the operation of paper industry business management; fertilizer, food retail, cultivation, refractory material manufacturing industry, cement, and concrete products manufacturing; building materials and refractory materials batches, human dispatch industry, and chemical raw material retail industry; and wholesale business. Further, the company is involved in the sales of paper products; research, development, production and sales of thin film transistor liquid crystal displays; import an…
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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.