Cyabra (NASDAQ:CYAB) Posts Quarterly Earnings Results, Misses Expectations By $0.01 EPS

Cyabra (NASDAQ:CYAB) issued its quarterly earnings results on Thursday. The company reported ($0.26) earnings per share (EPS) for the quarter, missing the consensus estimate of ($0.25) by ($0.01), Zacks reports.

Cyabra Trading Up 16.5%

Shares of Cyabra stock traded up $0.06 during trading on Thursday, hitting $0.39. 787,925 shares of the stock were exchanged, compared to its average volume of 1,119,730. The company has a market cap of $5.50 million, a PE ratio of -0.13 and a beta of 0.33. The business’s 50-day simple moving average is $0.40. Cyabra has a 12-month low of $0.25 and a 12-month high of $6.20.

Wall Street Analysts Forecast Growth

A number of research firms have issued reports on CYAB. Maxim Group began coverage on shares of Cyabra in a report on Thursday, July 23rd. They set a “buy” rating and a $1.00 target price on the stock. Weiss Ratings initiated coverage on shares of Cyabra in a research note on Friday, July 10th. They issued a “sell (e)” rating for the company. Finally, Zacks Research upgraded Cyabra to a “hold” rating in a research note on Friday, July 24th. One analyst has rated the stock with a Buy rating, one has assigned a Hold rating and one has assigned a Sell rating to the company’s stock. According to data from MarketBeat, the company presently has a consensus rating of “Hold” and a consensus price target of $1.00.

Cyabra Company Profile

Cyabra is a technology company that provides AI-powered solutions designed to help organizations identify and analyze harmful online activity, including disinformation, fake accounts, and coordinated manipulation campaigns across digital platforms. Its software is intended to give businesses and public-sector users visibility into how narratives spread online and how inauthentic behavior may influence public perception.

The company’s platform focuses on detecting threats in social media and other online environments by analyzing public conversation, identifying suspicious profiles, and mapping patterns of influence.