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International Business Machines Corporation (IBM)

NYSE - Nasdaq Real-time price. Currency in USD
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146.9300-0.7300 (-0.4944%)
As of 12:51PM EDT. Market open.
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Previous close147.6600
Bid147.0800 x 100
Ask147.1200 x 100
Day's range146.8800 - 147.8600
52-week range146.7100 - 182.7900
Avg. volume4,389,150
Market cap138.04B
PE ratio (TTM)12.08
EPS (TTM)12.16
Earnings date17 Oct 2017
Dividend & yield6.00 (4.07%)
Ex-dividend date2017-05-08
1y target est159.35
Trade prices are not sourced from all markets
  • Market Realist3 hours ago

    Why IBM’s Earnings Could Fall Going Forward

    International Business Machines (IBM) reported its 2Q17 results on Tuesday, July 18. The company reported falling quarterly profits and sales yet again.

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    For investors in, Inc. (NASDAQ:AMZN), it has been nothing but blue skies. Sure, most investors think of Amazon in terms of its retail business. It offers a universe of goods at seemingly rock-bottom and can’t be beaten prices on its websites. Then there’s Amazon’s rapidly expanding delivery services, which can whisk an increasing number of goods from ink toner to fizzy drinks in a matter of hours to your doorstep with a few clicks on your tablet, laptop or mobile phone.

  • IBM and University of Alberta Publish New Data on Machine Learning Algorithms to Help Predict Schizophrenia
    PR Newswire4 hours ago

    IBM and University of Alberta Publish New Data on Machine Learning Algorithms to Help Predict Schizophrenia

    YORKTOWN, N.Y. and EDMONTON, Alberta, July 21, 2017 /PRNewswire/ -- IBM (NYSE: IBM) scientists and the University of Alberta in Edmonton, Canada, have published new data in Nature's partner journal, Schizophrenia1, demonstrating that AI and machine learning algorithms helped predict instances of schizophrenia with 74% accuracy. This retrospective analysis also showed the technology predicted the severity of specific symptoms in schizophrenia patients with significant correlation, based on correlations between activity observed across different regions of the brain. This pioneering research could also help scientists identify more reliable objective neuroimaging biomarkers that could be used to predict schizophrenia and its severity.