| Previous close | 147.6600 |
| Open | 147.5900 |
| Bid | 147.0800 x 100 |
| Ask | 147.1200 x 100 |
| Day's range | 146.8800 - 147.8600 |
| 52-week range | 146.7100 - 182.7900 |
| Volume | 3,352,283 |
| Avg. volume | 4,389,150 |
| Market cap | 138.04B |
| Beta | 0.90 |
| PE ratio (TTM) | 12.08 |
| EPS (TTM) | 12.16 |
| Earnings date | 17 Oct 2017 |
| Dividend & yield | 6.00 (4.07%) |
| Ex-dividend date | 2017-05-08 |
| 1y target est | 159.35 |
- Market Realist•3 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.
- InvestorPlace•3 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.
- PR Newswire•4 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.
