You could do some very simple keyword analysis to filter that out, though. When words like "the deal", "in talks to buy", "to acquire", etc. appear, it's a pretty good bet that it has something to do with an acquisition, and also a good bet that volatility will spike.
A lot of people here are saying "I wouldn't bet $2.4M on that false positive rate", but that's not how traders think. You only have to be right more often than you're wrong (or alternatively, very right to offset being wrong a lot more often) - "betting" is exactly what they do for a living. It's pretty much the perfect application for statistical machine learning - users never see how bad your algorithms are, and so it doesn't matter if the quality is worse than a human as long as the speed is better.
Since when do newspapers write about the lack of something happening? That's sort of anti-news, isn't it? I could potentially see them writing something like that as a throwaway sentence in another article about the company, but the phrasing you've quoted is incredibly awkward and would probably never make it into a real news story.
Also, an algorithm doesn't have to be perfect, it merely has to be right more often than it's wrong. So what if you get a few false positives and a couple of your trades blow up? That's why you're managing a portfolio and not dumping your entire assets into a single trade.
When it comes to market speculation, non-news is published quite frequently. Often time it comes in the form of stories that summarize what happened that week.
A lot of people here are saying "I wouldn't bet $2.4M on that false positive rate", but that's not how traders think. You only have to be right more often than you're wrong (or alternatively, very right to offset being wrong a lot more often) - "betting" is exactly what they do for a living. It's pretty much the perfect application for statistical machine learning - users never see how bad your algorithms are, and so it doesn't matter if the quality is worse than a human as long as the speed is better.