International Business Machines (NYSE:IBM – Get Free Report) released its quarterly earnings data on Wednesday. The technology company reported $2.30 earnings per share (EPS) for the quarter, beating analysts’ consensus estimates of $2.27 by $0.03, Briefing.com reports. The firm had revenue of $14.97 billion for the quarter, compared to the consensus estimate of $15.08 billion. International Business Machines had a net margin of 13.52% and a return on equity of 40.59%. The company’s quarterly revenue was up 1.5% on a year-over-year basis. During the same period last year, the firm earned $2.20 earnings per share.
International Business Machines Stock Performance
NYSE:IBM opened at $218.28 on Friday. International Business Machines has a twelve month low of $136.33 and a twelve month high of $237.37. The company has a market cap of $200.51 billion, a P/E ratio of 24.72, a P/E/G ratio of 5.21 and a beta of 0.70. The company has a current ratio of 1.12, a quick ratio of 1.08 and a debt-to-equity ratio of 2.20. The company’s 50-day moving average price is $214.67 and its 200-day moving average price is $190.05.
International Business Machines Dividend Announcement
The firm also recently announced a quarterly dividend, which was paid on Tuesday, September 10th. Stockholders of record on Friday, August 9th were issued a dividend of $1.67 per share. This represents a $6.68 dividend on an annualized basis and a dividend yield of 3.06%. The ex-dividend date of this dividend was Friday, August 9th. International Business Machines’s payout ratio is 75.65%.
Analyst Ratings Changes
Get Our Latest Stock Analysis on International Business Machines
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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