Arbe Robotics FY2024 EPS Forecast Boosted by Roth Capital

Arbe Robotics Ltd. (NASDAQ:ARBE) – Equities researchers at Roth Capital boosted their FY2024 earnings per share (EPS) estimates for Arbe Robotics in a report issued on Wednesday, November 6th. Roth Capital analyst S. Desilva now forecasts that the company will post earnings per share of ($0.52) for the year, up from their previous forecast of ($0.54). The consensus estimate for Arbe Robotics’ current full-year earnings is ($0.52) per share. Roth Capital also issued estimates for Arbe Robotics’ Q4 2024 earnings at ($0.09) EPS, Q1 2025 earnings at ($0.09) EPS, Q2 2025 earnings at ($0.09) EPS, Q3 2025 earnings at ($0.09) EPS, Q4 2025 earnings at ($0.08) EPS and FY2025 earnings at ($0.35) EPS.

Arbe Robotics Stock Performance

Shares of NASDAQ:ARBE opened at $1.78 on Monday. The stock has a market capitalization of $143.69 million, a price-to-earnings ratio of -2.53 and a beta of -0.03. The stock’s 50-day simple moving average is $1.92 and its two-hundred day simple moving average is $1.94. Arbe Robotics has a 52-week low of $1.40 and a 52-week high of $2.57.

Institutional Inflows and Outflows

Several institutional investors and hedge funds have recently bought and sold shares of ARBE. Ground Swell Capital LLC purchased a new position in Arbe Robotics in the second quarter worth about $34,000. PEAK6 Investments LLC purchased a new position in Arbe Robotics in the first quarter worth about $319,000. Finally, M&G Plc purchased a new position in Arbe Robotics in the first quarter worth about $7,439,000. 33.42% of the stock is owned by hedge funds and other 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.