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Ørsted A/S, (ORSTED) Fair Value & Analysis

Utilities · DK · Market cap 217B DKK

Pricekr 149.55
Fair Valuekr 33.25
Upside-77.8%
Quality92/100
Evidence: Medium Range kr 24.93 – kr 41.56

Analysis

Ørsted A/S, (ORSTED) currently trades at kr 149.55, while our model-based Fair Value estimate is kr 33.25 — implying the stock looks roughly 77.8% overvalued today. We read business quality at 92/100 (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: medium).

About the company

Ørsted A/S, together with its subsidiaries, owns, develops, constructs, and operates offshore and onshore wind farms, solar farms, and energy storage and combined heat and power (CHP) plants. It operates through Offshore, Onshore, and Bioenergy & Other segments. The Offshore segment owns, develops, constructs, and operates offshore wind farms in Europe, the United States, and the Asia-Pacific region. The Onshore segment owns, develops, constructs, and operates onshore wind and solar farms in the United States, including integrated storage. The Bioenergy & Other segment generates heat and power and offers ancillary services from CHP plants in Denmark; and optimizes its gas portfolio, as well as manages its Danish and Swedish B2B business. The company was formerly known as DONG Energy A/S and changed its name to Ørsted A/S in November 2017. Ørsted A/S was incorporated in 1972 and is based in Fredericia, Denmark.

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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.