International Business Machines (NYSE:IBM – Get Free Report) issued its earnings results on Wednesday. The technology company reported $3.92 earnings per share (EPS) for the quarter, beating analysts’ consensus estimates of $3.77 by $0.15, Zacks reports. International Business Machines had a net margin of 10.22% and a return on equity of 40.52%.
International Business Machines Stock Up 1.5 %
IBM traded up $3.47 during trading hours on Wednesday, reaching $229.13. 6,703,071 shares of the stock traded hands, compared to its average volume of 3,835,314. International Business Machines has a fifty-two week low of $162.62 and a fifty-two week high of $239.35. The company has a debt-to-equity ratio of 2.16, a current ratio of 1.06 and a quick ratio of 1.01. The company has a market cap of $211.87 billion, a price-to-earnings ratio of 33.35, a PEG ratio of 4.78 and a beta of 0.74. The firm’s fifty day simple moving average is $224.95 and its two-hundred day simple moving average is $213.44.
Insider Buying and Selling at International Business Machines
In other International Business Machines news, SVP Nickle Jaclyn Lamoreaux sold 3,600 shares of the stock in a transaction on Friday, November 8th. The shares were sold at an average price of $215.20, for a total transaction of $774,720.00. Following the transaction, the senior vice president now directly owns 25,390 shares in the company, valued at $5,463,928. This represents a 12.42 % decrease in their position. The transaction was disclosed in a legal filing with the SEC, which is available through this link. 0.07% of the stock is currently owned by corporate insiders.
Analyst Ratings Changes
About International Business Machines
International Business Machines Corporation, together with its subsidiaries, provides integrated solutions and services worldwide. The company operates through Software, Consulting, Infrastructure, and Financing segments. The Software segment offers a hybrid cloud and AI platforms that allows clients to realize their digital and AI transformations across the applications, data, and environments in which they operate.
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