Absci (NASDAQ:ABSI – Get Free Report) posted its quarterly earnings results on Tuesday. The company reported ($0.25) EPS for the quarter, missing analysts’ consensus estimates of ($0.23) by ($0.02), Zacks reports. Absci had a negative return on equity of 46.56% and a negative net margin of 2,321.56%.
Absci Stock Down 3.9 %
Shares of Absci stock traded down $0.13 during trading on Tuesday, reaching $3.09. 3,885,240 shares of the company traded hands, compared to its average volume of 2,345,240. The company has a debt-to-equity ratio of 0.01, a current ratio of 5.63 and a quick ratio of 5.63. The firm has a market capitalization of $354.33 million, a PE ratio of -3.32 and a beta of 2.09. The company has a 50 day moving average price of $3.87 and a 200-day moving average price of $3.69. Absci has a 1-year low of $2.45 and a 1-year high of $6.72.
Analysts Set New Price Targets
Several brokerages have recently weighed in on ABSI. KeyCorp dropped their price objective on shares of Absci from $6.00 to $5.00 and set an “overweight” rating on the stock in a research report on Wednesday, January 8th. Guggenheim restated a “buy” rating and set a $10.00 price objective on shares of Absci in a research report on Tuesday, December 3rd. Needham & Company LLC started coverage on Absci in a research report on Wednesday, January 22nd. They issued a “buy” rating and a $9.00 target price on the stock. Finally, HC Wainwright reissued a “buy” rating and set a $7.00 price target on shares of Absci in a report on Friday, January 17th. Seven equities research analysts have rated the stock with a buy rating, According to MarketBeat, Absci currently has an average rating of “Buy” and an average price target of $8.57.
About Absci
Absci Corporation operates as a data-first generative artificial intelligence (AI) drug creation company in the United States. The company combines AI with scalable wet lab technologies to create biologics for patients. Its integrated drug creation platform is designed to improve upon traditional biologic drug discovery by using AI to simultaneously optimize multiple drug characteristics that may be important to development and therapeutic benefit.
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