Arbe Robotics Ltd. (NASDAQ:ARBE – Free Report) – Research analysts at Roth Capital increased their Q1 2025 earnings per share estimates for shares of Arbe Robotics in a report issued on Sunday, January 12th. Roth Capital analyst S. Desilva now forecasts that the company will earn ($0.09) per share for the quarter, up from their prior forecast of ($0.10). The consensus estimate for Arbe Robotics’ current full-year earnings is ($0.58) per share. Roth Capital also issued estimates for Arbe Robotics’ Q2 2025 earnings at ($0.09) EPS, Q3 2025 earnings at ($0.09) EPS, Q4 2025 earnings at ($0.09) EPS and FY2025 earnings at ($0.35) EPS.
Separately, Maxim Group lowered their price target on Arbe Robotics from $4.00 to $3.00 and set a “buy” rating for the company in a research note on Friday, November 29th.
Arbe Robotics Price Performance
Shares of ARBE stock opened at $3.27 on Wednesday. The stock has a market cap of $263.97 million, a PE ratio of -4.42 and a beta of -0.04. The stock has a 50-day moving average of $2.02 and a 200-day moving average of $2.01. Arbe Robotics has a one year low of $1.39 and a one year high of $5.09.
Institutional Trading of Arbe Robotics
A hedge fund recently raised its stake in Arbe Robotics stock. Ground Swell Capital LLC increased its holdings in shares of Arbe Robotics Ltd. (NASDAQ:ARBE – Free Report) by 114.8% in the third quarter, according to the company in its most recent filing with the SEC. The institutional investor owned 38,024 shares of the company’s stock after purchasing an additional 20,324 shares during the quarter. Ground Swell Capital LLC’s holdings in Arbe Robotics were worth $73,000 as of its most recent filing with the SEC. 33.42% of the stock is owned by institutional investors.
About Arbe Robotics
Arbe Robotics Ltd., a semiconductor company, provides 4D imaging radar solutions for tier 1 automotive suppliers and automotive manufacturers in China, Hong Kong, Sweden, Germany, the United States, Israel, and internationally. It offers 4D imaging radar chipset solutions that address the core issues that have caused autonomous vehicle and autopilot accidents, such as detecting stationary objects, identifying vulnerable road users, operation at poor lighting conditions, and eliminating false alarms without radar ambiguities.
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