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Sociedad Matriz SAAM S.A (SMSAAM) Fair Value & Analysis

Industrials · CL · Market cap 1.5T CLP

Price149.07 CLP
Fair Value156.73 CLP
Upside+5.1%
Quality93/100
Evidence: High Range 119.85 CLP – 202.82 CLP

Analysis

Sociedad Matriz SAAM S.A (SMSAAM) currently trades at 149.07 CLP, while our model-based Fair Value estimate is 156.73 CLP — implying the stock looks roughly 5.1% undervalued today. We read business quality at 93/100 (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

Sociedad Matriz SAAM S.A., through its subsidiaries, provides tugboat services, air cargo logistics, and real estate rentals services in South America, Central America, and North America. It operates through two segments, Tugboats and Logistics Area. The company offers harbour towage services which assists large vessels with berthing and deberthing upon arrival and in transit to the port. It also provides offshore hydrocarbon loading and unloading and salvage services. In addition, the company offers physical and documentary management of export, import, domestic and bonded warehouse cargo, aircraft ramp, and passenger services. Further, it also provides international air transport association certified courses in dangerous goods handling, aviation safety, and apron operations. Sociedad Matriz SAAM S.A. was founded in 1961 and is headquartered 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.