Bright Sheland International Co (4556) Fair Value & Analysis
Industrials · TW · Market cap 2.8B TWD
Fair value as of: Jun 24, 2026
Analysis
Bright Sheland International Co (4556) currently trades at 73.10 TWD, while our model-based Fair Value estimate is 19.36 TWD — implying the stock looks roughly 73.5% 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: high).
About the company
Bright Sheland International Co., Ltd. researches, develops, manufactures, markets, and sells water filters and compressed air separation systems under the Filtrafine brand in Taiwan and internationally. The company offers depth, string wound, activated carbon, pleated, membrane, glass fiber, high flow, and stainless steel cartridges; filter bag; and plastic, single SS, multiple SS, bag, high flow, sanitary, gas and steam, and customized filter housings. It also provides UV disinfection and TOC reduction units, spare parts; melt brown fabric; PP stable fiber; and laboratory services for filtration. The company serves microelectronics, oil and gas, water treatment, and food and beverage industries. Bright Sheland International Co., Ltd. was founded in 1985 and is based in Taipei, Taiwan.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is Bright Sheland International Co (4556) undervalued?
What is the fair value of 4556?
What is the quality score of 4556?
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.