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International Business Machines Corporation (IBM)


NYSE - Nasdaq Real Time Price. Currency in USD
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147.18-0.48 (-0.33%)
As of 12:42PM EDT. Market open.
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Previous Close147.66
Open147.59
Bid147.14 x 200
Ask147.16 x 300
Day's Range146.88 - 147.86
52 Week Range146.71 - 182.79
Volume3,260,838
Avg. Volume4,389,150
Market Cap138.28B
Beta0.90
PE Ratio (TTM)12.10
EPS (TTM)12.16
Earnings DateOct 17, 2017
Dividend & Yield6.00 (4.07%)
Ex-Dividend Date2017-05-08
1y Target Est159.35
Trade prices are not sourced from all markets
  • Market Realist2 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.

  • Amazon.com, Inc. (AMZN) Stock Faces Danger in the Cloud
    InvestorPlace3 hours ago

    Amazon.com, Inc. (AMZN) Stock Faces Danger in the Cloud

    For investors in Amazon.com, 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.