MARTAS Precision Slide Co (6705) Fair Value & Analysis
Industrials · TW · Market cap 1.7B TWD
Fair value as of: Jun 24, 2026
Analysis
MARTAS Precision Slide Co (6705) currently trades at 97.00 TWD, while our model-based Fair Value estimate is 50.23 TWD — implying the stock looks roughly 48.2% 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
MARTAS Precision Slide Co.,Ltd manufactures ball bearing slides for various applications in Asia. Its products are used in server rails, cabinets, and cloud computing devices; tool cabinets, fire cabinets, ATM machines, vending machines, POS machines, and upright open showcases; and office furniture, computer desks, copy machines, and fax machines, as well as in kitchen cabinets, dish washers, oven, and refrigerators. The company's products are also used for automotive applications, such as in sliding arm rests, under seat and glove box storage, and luggage compartments; and residential applications for living rooms, TV cabinets, bedrooms, closets, cupboards, and restaurants. MARTAS Precision Slide Co.,Ltd was founded in 1996 and is based in New Taipei City, Taiwan.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is MARTAS Precision Slide Co (6705) undervalued?
What is the fair value of 6705?
What is the quality score of 6705?
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.