Short Interest in Cemtrex, Inc. (NASDAQ:CETX) Increases By 24.6%

Cemtrex, Inc. (NASDAQ:CETX) was the target of a large increase in short interest in July. As of July 15th, there was short interest totalling 277,700 shares, an increase of 24.6% from the June 30th total of 222,900 shares. Based on an average trading volume of 2,440,000 shares, the short-interest ratio is currently 0.1 days. Approximately 1.7% of the shares of the stock are short sold.

Analysts Set New Price Targets

Separately, StockNews.com began coverage on shares of Cemtrex in a research report on Tuesday, July 23rd. They set a “hold” rating on the stock.

Cemtrex Price Performance

NASDAQ:CETX remained flat at $0.20 on Friday. 627,549 shares of the company’s stock were exchanged, compared to its average volume of 709,757. Cemtrex has a 52-week low of $0.19 and a 52-week high of $7.42. The company has a quick ratio of 1.16, a current ratio of 1.57 and a debt-to-equity ratio of 4.18. The stock’s fifty day simple moving average is $0.28 and its two-hundred day simple moving average is $2.12.

Cemtrex (NASDAQ:CETX) last released its quarterly earnings results on Tuesday, May 14th. The industrial products company reported ($1.46) EPS for the quarter. The firm had revenue of $17.16 million during the quarter. Cemtrex had a negative net margin of 7.64% and a negative return on equity of 74.68%. During the same quarter in the previous year, the business posted ($0.75) EPS.

Cemtrex Company Profile

Cemtrex, Inc operates as a technology company in the United States and internationally. It operates through Security, Industrial Services, and Cemtrex Corporate segments. The company offers browser-based video monitoring and analytics-based recognition systems, cameras, servers, and access control systems for security and surveillance in industrial and commercial facilities, federal prisons, hospitals, universities, schools, and federal and state government offices; and provides critical security and video surveillance solutions utilizing artificial intelligence based data algorithms.