Nebius Group (NASDAQ:NBIS) Shares Down 9.1% – What’s Next?

Nebius Group N.V. (NASDAQ:NBIS) traded down 9.1% during mid-day trading on Wednesday . The stock traded as low as $24.43 and last traded at $24.71. 8,348,866 shares were traded during trading, a decline of 19% from the average session volume of 10,302,914 shares. The stock had previously closed at $27.17.

Analyst Ratings Changes

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

Nebius Group Price Performance

The business’s 50 day moving average price is $33.51. The company has a market cap of $5.25 billion, a PE ratio of -39.14 and a beta of 2.47.

Institutional Investors Weigh In On Nebius Group

An institutional investor recently bought a new position in Nebius Group stock. Centaurus Financial Inc. acquired a new position in Nebius Group N.V. (NASDAQ:NBIS) in the fourth quarter, according to its most recent 13F filing with the Securities and Exchange Commission. The fund acquired 343,130 shares of the company’s stock, valued at approximately $9,505,000. Centaurus Financial Inc. owned about 0.15% of Nebius Group as of its most recent filing with the Securities and Exchange Commission. 21.90% of the stock is owned by 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.