Nebius Group (NASDAQ:NBIS) Shares Down 9% - Should You Sell?

Market Beat
2025.02.23 10:04
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Nebius Group (NASDAQ:NBIS) shares fell 9% during mid-day trading, reaching a low of $41.45 before closing at $42.07. Trading volume was down 35% from average levels. BWS Financial raised its price target from $51 to $60, maintaining a "buy" rating. The company has a market cap of $9.38 billion and a PE ratio of -69.88. Despite the drop, analysts suggest it may be a strategic entry point for investors, although it was not listed among top recommendations by MarketBeat.

Nebius Group N.V. (NASDAQ:NBIS - Get Free Report)'s share price traded down 9% during mid-day trading on Friday . The company traded as low as $41.45 and last traded at $42.07. 8,349,519 shares were traded during mid-day trading, a decline of 35% from the average session volume of 12,839,450 shares. The stock had previously closed at $46.25.

Wall Street Analyst Weigh In

  • Nebius Group: A Strategic Entry Point for Investors?

Separately, BWS Financial increased their price target on shares of Nebius Group from $51.00 to $60.00 and gave the stock a "buy" rating in a report on Friday.

View Our Latest Report on NBIS

Nebius Group Stock Down 13.9 %

  • MarketBeat Week in Review – 02/17 - 02/21

The stock has a market capitalization of $9.38 billion, a PE ratio of -69.88 and a beta of 2.57. The firm has a fifty day moving average price of $34.37.

Nebius Group Company Profile

(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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