Market research
GEV GE Vernova LLC
NYSE USD Industrials
Latest close
As of 30 Oct 2026
Test a moving-average rule with historical data.
Market facts
- Market cap
- 235B
- P/E ratio
- 23.31
- Analyst target
- 1202.697
- Dividend yield
- 0.1%
- Beta
- 0.97
Profile
Instrument facts
- Exchange
- NYSE
- Currency
- USD
- Sector
- Industrials
- Industry
- Specialty Industrial Machinery
- ISIN
- Not available
- Market cap
- 235B
- P/E ratio
- 23.31
- Analyst target
- 1202.697
- Dividend yield
- 0.1%
- Beta
- 0.97
About
About GE Vernova LLC
GE Vernova Inc., an energy company, engages in the provision of various products and services that generate, transfer, orchestrate, convert, and store electricity in the United States, Europe, Asia, the Middle East, and Africa. The company operates through three segments: Power, Wind, and Electrification. The Power segment designs, manufactures, and services gas, nuclear, hydro, and steam technologies. It serves industrial, government, and other customers. The Wind segment offers wind generation technologies, including onshore and offshore wind turbines and blades. The Electrification segment provides grid solutions; power conversion; electrification software; and solar and storage solutions technologies required for the transmission, distribution, conversion, storage, and orchestration of electricity from point of generation to point of consumption. The company was incorporated in 2023 and is headquartered in Cambridge, Massachusetts.
Research context
GE Vernova LLC appears in PyInvesting’s US Stock catalogue. The price history above describes this recorded instrument; it does not by itself identify a company’s business or establish a continuous investment return.
- Currency
- USD
- Sector
- Industrials
- Industry
- Specialty Industrial Machinery
These are the latest stored catalogue classifications, not a historical classification snapshot. An issuer description, classification effective date or currency may be unavailable. Check the issuer’s own disclosures and the observation dates before using these fields for research.
Review backtest assumptions and evidence before treating a chart or stored history as a research result.
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