A lot of people seem to assume that humans are too slow to react to news, but this is definitely not the case. As an example, when the SNB dropped the swiss franc cap earlier this year (one of the biggest financial news stories for years), I know people who had time to read the headline on Bloomberg, look to see where the market was trading, and sell EURCHF within 0.1cents of where it was previously trading. As I watched the market reaction, I'm fairly confident that the other traders reacting were also human. As it was unscheduled, no-one would've been actively anticipating it happening on that day, never mind that minute.
Generally, there are two types of financial news events. First is scheduled, for example unemployment data - here, there are APIs to get the number and place trades, and as a human it is impossible to compete. Similarly, for FOMC statements, there is an API feed which provides objective answers to certain questions about the statement, e.g. "Did any Fed members vote for a rate increase?" Again, computers dominate. The other type of news events are surprises - unscheduled events that people are unprepared for. I'm certainly no NLP expert, but I do watch financial news feeds every day, and I can't imagine it being remotely easy to write a program to filter out the false positives. I've certainly watched a lot of market reactions to headlines, and I can tell that a lot of headlines that people would assume would be easy to write algorithms to trade on, produce market reactions that look far more "human" than the instantaneous reactions to unemployment data or embargoed Fed statements.
Generally, there are two types of financial news events. First is scheduled, for example unemployment data - here, there are APIs to get the number and place trades, and as a human it is impossible to compete. Similarly, for FOMC statements, there is an API feed which provides objective answers to certain questions about the statement, e.g. "Did any Fed members vote for a rate increase?" Again, computers dominate. The other type of news events are surprises - unscheduled events that people are unprepared for. I'm certainly no NLP expert, but I do watch financial news feeds every day, and I can't imagine it being remotely easy to write a program to filter out the false positives. I've certainly watched a lot of market reactions to headlines, and I can tell that a lot of headlines that people would assume would be easy to write algorithms to trade on, produce market reactions that look far more "human" than the instantaneous reactions to unemployment data or embargoed Fed statements.