The Financial Times has a piece up on a subject I have written about here a number of times, and that has to do with the rise of trading algorithms built around news textual analysis. While this is vastly easier to explain than to actually do profitably — and, to be honest, I have yet to meet anyone who runs a real trading strategy this way — it’s still an interesting augury of where things are going.
Computers are now being used to generate news stories about company earnings results or economic statistics as they are released. And this almost instantaneous information forms a direct feed into other
computers, which trade on the news.The result is a boom in demand from news and information providers such as Reuters, Bloomberg and Thomson Financial for “machine readable newsâ€, which is written in a computer-friendly language of strings of words and numbers without sentences. Computers can trade on such news within milliseconds of receiving it – much faster than a human trader.
“One of the big consumers of news now is a computer,” says Matthew Burkley, senior vice-president of strategy at Thomson Financial.
This will come as no surprise to readers of this site as I’ve written about it lately, most recently here. Mind you, as I say above, this is far harder to do profitably than the FT suggests, and, more importantly, there are far deeper and richer areas to explore for information providers and hedge funds than merely hanging around doing sentiment/keyword analysis on wire stories.
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