Sigdo Koppers S.A (SK) Fair Value & Analysis
Industrials · CL · Market cap 1.8T CLP
Fair value as of: Jun 25, 2026
Analysis
Sigdo Koppers S.A (SK) currently trades at 1,630 CLP, while our model-based Fair Value estimate is 1,616 CLP — implying the stock looks roughly 0.8% overvalued today. We read business quality at 80/100 (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: medium).
About the company
Sigdo Koppers S.A., together with its subsidiaries, engages in services, industrial, and commercial and automotive businesses internationally. The company provides services including engineering, civil works, electromechanical assembly and execution of works, as well as supply, including transportation to the site and installation; services include storage, storage, loading and unloading of materials and bulk products; and sale and rental of machinery, marketing of supplies, technical and after-sales service. The company also provides equipment and machinery rental services for transportation, agriculture, construction, mining, forestry, and industrial sectors; and explosive grade ammonium nitrate, as well as distributes automobile products. In addition, the company engages in the rock fragmentation business; and production and commercialization of grinding balls and wear elements for mining and industry sectors. Sigdo Koppers S.A. was founded in 1920 and is based in Las Condes, Chile.
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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.