Parametrica Management Ltd Sells 8,934 Shares of Arbe Robotics Ltd. (NASDAQ:ARBE)

Parametrica Management Ltd lowered its stake in shares of Arbe Robotics Ltd. (NASDAQ:ARBE) by 26.7% during the 4th quarter, according to the company in its most recent filing with the SEC. The fund owned 24,578 shares of the company’s stock after selling 8,934 shares during the quarter. Arbe Robotics accounts for 0.1% of Parametrica Management Ltd’s holdings, making the stock its 29th biggest holding. Parametrica Management Ltd’s holdings in Arbe Robotics were worth $53,000 as of its most recent filing with the SEC.

Separately, Y.D. More Investments Ltd bought a new position in Arbe Robotics in the 3rd quarter valued at $4,337,000. Hedge funds and other institutional investors own 33.42% of the company’s stock.

Arbe Robotics Stock Performance

Arbe Robotics stock traded up $0.01 during mid-day trading on Friday, hitting $1.84. The company’s stock had a trading volume of 28,232 shares, compared to its average volume of 47,067. The company has a 50 day moving average of $1.92 and a 200-day moving average of $1.95. Arbe Robotics Ltd. has a one year low of $1.40 and a one year high of $3.31.

Arbe Robotics (NASDAQ:ARBE) last announced its quarterly earnings data on Thursday, March 7th. The company reported ($0.10) EPS for the quarter, beating the consensus estimate of ($0.11) by $0.01. The company had revenue of $0.35 million for the quarter, compared to the consensus estimate of $4.00 million. Arbe Robotics had a negative return on equity of 69.50% and a negative net margin of 2,959.18%. As a group, analysts expect that Arbe Robotics Ltd. will post -0.3 earnings per share for the current year.

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.