BioXcel Therapeutics (NASDAQ:BTAI – Get Free Report) announced its quarterly earnings data on Tuesday. The company reported ($0.21) earnings per share (EPS) for the quarter, topping the consensus estimate of ($0.76) by $0.55, Yahoo Finance reports. The firm had revenue of $1.10 million for the quarter, compared to the consensus estimate of $0.80 million. During the same quarter last year, the business earned ($1.83) earnings per share.
BioXcel Therapeutics Price Performance
Shares of BTAI stock traded down $0.05 during trading hours on Wednesday, reaching $0.91. The stock had a trading volume of 211,409 shares, compared to its average volume of 980,434. The firm has a market capitalization of $34.20 million, a PE ratio of -0.18 and a beta of 0.32. The firm has a 50-day simple moving average of $1.25 and a 200-day simple moving average of $2.23. BioXcel Therapeutics has a twelve month low of $0.89 and a twelve month high of $7.80.
Insider Buying and Selling at BioXcel Therapeutics
In other BioXcel Therapeutics news, CEO Vimal Mehta sold 126,014 shares of the firm’s stock in a transaction that occurred on Tuesday, June 4th. The shares were sold at an average price of $1.63, for a total value of $205,402.82. Following the sale, the chief executive officer now owns 7,811,515 shares in the company, valued at $12,732,769.45. The sale was disclosed in a document filed with the Securities & Exchange Commission, which is available through the SEC website. Insiders sold 128,520 shares of company stock valued at $208,611 in the last ninety days. Company insiders own 35.80% of the company’s stock.
Analysts Set New Price Targets
Check Out Our Latest Stock Report on BTAI
BioXcel Therapeutics Company Profile
BioXcel Therapeutics, Inc, a commercial-stage biopharmaceutical company, engages in utilizing artificial intelligence approaches to develop transformative medicines in neuroscience and immuno-oncology. The company's drug re-innovation approach leverages existing approved drugs and/or clinically validated product candidates together with big data and proprietary machine learning algorithms to identify new therapeutic indices.
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