908 Devices (NASDAQ:MASS) Announces Quarterly Earnings Results, Beats Estimates By $0.03 EPS

908 Devices (NASDAQ:MASS) posted its quarterly earnings data on Tuesday. The company reported ($0.33) earnings per share (EPS) for the quarter, topping the consensus estimate of ($0.36) by $0.03, Yahoo Finance reports. 908 Devices had a negative return on equity of 20.47% and a negative net margin of 68.57%. The company had revenue of $9.99 million for the quarter, compared to the consensus estimate of $9.29 million. During the same period in the previous year, the business earned ($0.39) EPS. 908 Devices’s revenue for the quarter was up 5.3% compared to the same quarter last year. 908 Devices updated its FY 2024 guidance to EPS.

908 Devices Stock Performance

Shares of NASDAQ MASS traded down $0.19 during trading on Thursday, reaching $5.49. The stock had a trading volume of 68,971 shares, compared to its average volume of 173,780. 908 Devices has a one year low of $4.85 and a one year high of $12.51. The stock has a market cap of $181.06 million, a PE ratio of -5.20 and a beta of 1.02. The firm’s 50 day moving average price is $6.59 and its two-hundred day moving average price is $7.08.

908 Devices Company Profile

908 Devices Inc, a commercial-stage technology company, provides various purpose-built handheld and desktop mass spectrometry devices to interrogate unknown and invisible materials in life sciences research, bioprocessing, pharma/biopharma, forensics, and adjacent markets. The company's products include MX908, a handheld, battery-powered, and Mass Spec device that is designed for rapid analysis of solid, liquid, vapor, and aerosol materials of unknown identity; Rebel, a small desktop analyzer that provides real-time information on the extracellular environment in bioprocesses; and Maverick, an optical in-line analyzer that offers real-time monitoring and control of multiple bioprocess parameters, including glucose, lactate, and total biomass in mammalian cell cultures, as well as provides process fingerprint data to support large-scale efforts in predictive bioprocess modeling.