Nebius Group (NASDAQ:NBIS) Stock Price Down 2.1% - Should You Sell?

Market Beat
2025.02.07 23:44

Nebius Group (NASDAQ:NBIS) shares fell 2.1% to $33.78, with trading volume down 82% from average levels. Despite this decline, BWS Financial maintained a "buy" rating and set a price target of $51.00. The company, valued at $8.98 billion, focuses on AI-driven products and services. Analysts suggest the recent stock movement may be an overreaction, while the stock has seen a 10.4% increase recently. Investors are advised to consider other stocks recommended by top analysts before making decisions on Nebius Group.

Nebius Group N.V. (NASDAQ:NBIS - Get Free Report)'s share price dropped 2.1% on Wednesday . The company traded as low as $33.86 and last traded at $33.78. Approximately 1,885,302 shares were traded during trading, a decline of 82% from the average daily volume of 10,476,859 shares. The stock had previously closed at $34.50.

Analyst Ratings Changes

  • Nebius Group: Market Overreaction or Real AI Disruption?

Separately, BWS Financial reiterated a "buy" rating and issued a $51.00 price target on shares of Nebius Group in a report on Tuesday, January 28th.

View Our Latest Stock Analysis on NBIS

Nebius Group Stock Up 10.4 %

  • Nebius Group (NBIS): A Small-Cap Backed by NVIDIA

The firm's fifty day moving average price is $31.74. The company has a market cap of $8.98 billion, a price-to-earnings ratio of -66.89 and a beta of 2.58.

About Nebius Group

(Get Free Report)

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.

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