Grid Dynamics (NASDAQ:GDYN – Get Free Report) posted its earnings results on Thursday. The company reported $0.04 earnings per share for the quarter, missing analysts’ consensus estimates of $0.10 by ($0.06), Zacks reports. Grid Dynamics had a return on equity of 0.15% and a net margin of 0.74%. Grid Dynamics updated its FY 2025 guidance to EPS and its Q1 2025 guidance to EPS.
Grid Dynamics Trading Down 5.1 %
NASDAQ GDYN traded down $1.09 during trading on Thursday, hitting $20.48. 839,109 shares of the company’s stock were exchanged, compared to its average volume of 717,363. The company has a market cap of $1.69 billion, a PE ratio of 682.89 and a beta of 1.01. Grid Dynamics has a fifty-two week low of $9.07 and a fifty-two week high of $24.60. The stock’s 50 day moving average price is $21.58 and its two-hundred day moving average price is $17.55.
Insiders Place Their Bets
In other Grid Dynamics news, CFO Anil Doradla sold 3,000 shares of the business’s stock in a transaction dated Monday, December 9th. The stock was sold at an average price of $19.08, for a total transaction of $57,240.00. Following the completion of the transaction, the chief financial officer now owns 373,282 shares of the company’s stock, valued at approximately $7,122,220.56. The trade was a 0.80 % decrease in their ownership of the stock. The sale was disclosed in a legal filing with the Securities & Exchange Commission, which can be accessed through the SEC website. Over the last 90 days, insiders sold 8,000 shares of company stock valued at $171,780. 7.20% of the stock is currently owned by corporate insiders.
Analyst Upgrades and Downgrades
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Grid Dynamics Company Profile
Grid Dynamics Holdings, Inc, together with its subsidiaries, provides technology consulting, platform and product engineering, and analytics services in North America, Europe, and internationally. It offers cloud platform and product engineering services, such as architecting, designing, and building scalable and secure cloud-based platforms and business applications; and AI/machine learning and data platform engineering services that build platforms to facilitate batch and streaming data ingestion, quality governance, orchestration, semantic modeling, observability, and analysis at scale.
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