CIGN (CIGN) Fair Value & Analysis
Utilities · MX · Market cap 109B MXN
Fair value as of: Jun 24, 2026
Analysis
CIGN (CIGN) currently trades at 38.00 MXN, while our model-based Fair Value estimate is 37.32 MXN — implying the stock looks roughly 1.8% overvalued today. We read business quality at 95/100 (high quality), in the Utilities 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
Companhia Energética de Minas Gerais - CEMIG, through its subsidiaries, engages in the generation, transmission, distribution, and sale of energy in Brazil. As of December 31, 2025, the company operated 32 hydro plants with a total capacity of 4,434 M, 2 wind farms with a total capacity of 71 MW, and 12 photovoltaic power stations with a total capacity of 169 MW; 365,577 miles of distribution lines; and 4,865 miles of transmission lines. It is also involved in the acquisition, transportation, and distribution of gas and its sub products and derivatives; sale and trading of energy; construction, implementation, operation and maintenance of electricity transmission; marketing and intermediation of energy-related business; installation, operation, maintenance and rental of solar plants; and distributed generation, account services, cogeneration, energy efficiency, and supply and storage management activities. The company was incorporated in 1952 and is headquartered in Belo Horizonte, …
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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.