Torrent Power Limited (TORNTPOWER) Fair Value & Analysis
Utilities · IN · Market cap ₹736B
Analysis
Torrent Power Limited (TORNTPOWER) currently trades at ₹1,455, while our model-based Fair Value estimate is ₹817.60 — implying the stock looks roughly 43.8% 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
Torrent Power Limited, together with its subsidiaries, engages in the generation, renewables, transmission and distribution of electricity in India. The company owns thermal power plants with a generation capacity of 3,092 megawatts; solar power plants with a generation capacity of 2,319 megawatts peak; and wind power plants with a generation capacity of 2,581 megawatts. It also distributes electricity in the cities of Ahmedabad, Gandhinagar, Surat, Dadra and Nagar Haveli, Daman and Diu, Dahej, and Dholera covering an area of 2,050 square kilometers; and operates as a franchisee for electricity distribution in the cities of Bhiwandi, Agra, and Shil-Mumbra-Kalwa covering an area of approximately 1,007 square kilometers. In addition, the company is involved in the manufacture and supply of power cables and ancillary services. The company was incorporated in 2004 and is headquartered in Ahmedabad, India. Torrent Power Limited is a subsidiary of Torrent Investments Limited.
Open the full interactive analysis →
Similar stocks
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.