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Energía Latina S.A (ENLASA) Fair Value & Analysis

Utilities · CL · Market cap 43.8B CLP

Price1,020 CLP
Fair Value1,589 CLP
Upside+55.8%
Quality95/100
Evidence: High Range 1,185 CLP – 1,984 CLP

Fair value as of: Jun 25, 2026

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Analysis

Energía Latina S.A (ENLASA) currently trades at 1,020 CLP, while our model-based Fair Value estimate is 1,589 CLP — implying the stock looks roughly 55.8% undervalued today. We read business quality at 95/100 (high quality), in the Utilities 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

Energía Latina S.A. engages in the generation and sale of electricity in Chile. It operates energy storage solutions and distribution and generation of renewable energy. The company was incorporated in 2005 and is based in Vitacura, Chile.

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Frequently asked questions

Is Energía Latina S.A (ENLASA) undervalued?
As of Jun 25, 2026, our model estimates a fair value of 1,589 CLP versus a price of 1,020 CLP — about +56% (undervalued). Model-based estimate, not financial advice.
What is the fair value of ENLASA?
Our 21-model fair value for Energía Latina S.A is 1,589 CLP (as of Jun 25, 2026), built from audited fundamentals. The current price is 1,020 CLP.
What is the quality score of ENLASA?
Energía Latina S.A has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.