Andino Inversiones Global S.A (MLAIG) Fair Value & Analysis
Industrials · FR · Market cap €61.7M
Fair value as of: Jun 26, 2026
Analysis
Andino Inversiones Global S.A (MLAIG) currently trades at €2.82, while our model-based Fair Value estimate is €4.22 — implying the stock looks roughly 49.6% undervalued today. We read business quality at 80/100 (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: low) — always confirm before acting.
About the company
Andino Inversiones Global S.A. provides airport and port infrastructure, airport, and maritime logistics services in Spain. The company engages in the design, construction, improvement, conservation, and operation of airports. It also provides aircraft ground support, cargo storage terminal, fixed base operator services. In addition, the company is involved in the development and construction, purchase, sale, leasing, and administration of real estate. Further, it provides integrated logistics solutions to the aviation, maritime, and fluvial sectors, including customs agency services, international freight transportation services, handling, and storage, as well as offers shipping agency ship representation, terminal operations, stowage and unstowage, pilotage, and towage services. Additionally, the company provides short- and medium-term facilities, as well as the issuance of warrants and certificates of deposit, factoring, leasing, and other services. Andino Inversiones Global S.A.…
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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.