Grid Dynamics (NASDAQ:GDYN – Get Free Report) posted its quarterly earnings results on Thursday. The company reported $0.04 earnings per share for the quarter, missing the consensus estimate 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 %
GDYN stock traded down $1.09 during midday trading on Thursday, hitting $20.48. 840,228 shares of the company’s stock were exchanged, compared to its average volume of 717,634. Grid Dynamics has a 1-year low of $9.07 and a 1-year high of $24.60. The business has a 50-day simple moving average of $21.58 and a two-hundred day simple moving average of $17.55. The stock has a market capitalization of $1.69 billion, a PE ratio of 682.89 and a beta of 1.01.
Insider Activity
In other news, CFO Anil Doradla sold 3,000 shares of the company’s stock in a transaction that occurred on Monday, December 9th. The shares were sold at an average price of $19.08, for a total value of $57,240.00. Following the transaction, the chief financial officer now directly owns 373,282 shares in the company, valued at approximately $7,122,220.56. This represents a 0.80 % decrease in their position. The sale was disclosed in a legal filing with the SEC, which can be accessed through this hyperlink. Insiders have sold a total of 8,000 shares of company stock valued at $171,780 in the last quarter. Insiders own 7.20% of the company’s stock.
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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