Nebius Group (NASDAQ:NBIS) Trading Down 5.1% – What’s Next?

Nebius Group N.V. (NASDAQ:NBIS)’s stock price traded down 5.1% during mid-day trading on Friday . The company traded as low as $23.83 and last traded at $24.10. 4,049,135 shares changed hands during mid-day trading, a decline of 61% from the average session volume of 10,429,127 shares. The stock had previously closed at $25.41.

Analysts Set New Price Targets

A number of research analysts have recently commented on NBIS shares. DA Davidson initiated coverage on shares of Nebius Group in a research note on Tuesday, February 25th. They set a “buy” rating and a $50.00 price objective for the company. BWS Financial reaffirmed a “buy” rating and set a $60.00 price target on shares of Nebius Group in a research note on Tuesday, March 4th.

Nebius Group Stock Performance

The business’s 50-day moving average price is $33.23. The stock has a market capitalization of $5.25 billion, a PE ratio of -39.14 and a beta of 2.47.

Institutional Trading of Nebius Group

A hedge fund recently bought a new stake in Nebius Group stock. Centaurus Financial Inc. acquired a new position in shares of Nebius Group N.V. (NASDAQ:NBIS) in the 4th quarter, according to its most recent filing with the Securities & Exchange Commission. The fund acquired 343,130 shares of the company’s stock, valued at approximately $9,505,000. Centaurus Financial Inc. owned 0.15% of Nebius Group as of its most recent SEC filing. 21.90% of the stock is owned by hedge funds and other institutional investors.

Nebius Group Company Profile

Nebius Group N.V., a technology company, builds intelligent products and services powered by machine learning and other technologies to help consumers and businesses navigate the online and offline world. The company’s services include Nebius AI, an AI-centric cloud platform that offers infrastructure and computing capability for AI deployment and machine-learning oriented solutions; and Toloka AI that offers generative AI (GenAI) solutions at every stage of the GenAI lifecycle, such as data annotation and generation, model training and fine-tuning, and quality assessment of large language model for accuracy and reliability.