Nebius Group (NASDAQ:NBIS) Shares Down 7.4% – What’s Next?

Nebius Group N.V. (NASDAQ:NBIS)’s share price traded down 7.4% on Tuesday . The stock traded as low as $26.22 and last traded at $26.21. 3,573,382 shares were traded during trading, a decline of 65% from the average session volume of 10,346,327 shares. The stock had previously closed at $28.29.

Analyst Ratings Changes

NBIS has been the subject of several research reports. BWS Financial reiterated a “buy” rating and issued a $60.00 target price on shares of Nebius Group in a research report on Tuesday, March 4th. DA Davidson started coverage on Nebius Group in a research report on Tuesday, February 25th. They set a “buy” rating and a $50.00 price objective on the stock.

Nebius Group Stock Performance

The firm has a market capitalization of $6.30 billion, a P/E ratio of -47.04 and a beta of 2.47. The company’s fifty day simple moving average is $34.72.

Institutional Investors Weigh In On Nebius Group

A hedge fund recently bought a new stake in Nebius Group stock. Centaurus Financial Inc. bought a new position in Nebius Group N.V. (NASDAQ:NBIS) during the 4th quarter, according to the company in its most recent 13F filing with the Securities & Exchange Commission. The firm bought 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 & Exchange Commission. Institutional investors and hedge funds own 21.90% of the company’s stock.

About Nebius Group

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.