I think one of the more promising novelties in finance is the application of “big data” in financial research as well as in practical investment activities. The amount of data that is available in the world today is clearly huge. Most likely this is still just a fraction of the amounts that will be available in five or ten years’ time though. Similarly, the financial usage of (truly) huge data volumes, while definitely taking off already today, is still largely in waiting.
Personally, I have touched upon big data in my own research and, for instance, in the paper News Aggregators, Volatility and the Stock Market I collect news volumes using a certain well-known and web-based news aggregator. While this paper focused on news in English (currently the dominant language for web news) I have also looked at news volumes in Chinese (Mandarin, potentially a future dominant in web news) and the picture is the same, at least for the Hong Kong market; the link between stock volatilities and the amount of news circulating in cyber space is strong.
While my own research collects data from huge “big data” data bases the actual work does no really involve huge data volumes. There are, however, other (often commercial) applications out there that dig much deeper into the mountain of data. One interesting example is hedge funds’ and other traders’ attempts to use Twitter to detect profitable trades seconds before their competitors. To my knowledge, at least one company has entered into a partnership with Twitter to launch trading applications with access to the “Twitter Firehose” of public tweets (the entire stream of messages that flows through the system each day).
The company claims that it has given its users profitable buy/sell signals and if these claims are accurate, I think this is a great testament to the power of Twitter as a real-time news source (including gossip and rumors). One problem, of course, is that in breaking news situations, initial gossip is often wrong. People could also try to fool investors by sending out tweets that are actually false. We have seen some examples of this recently. I am certain, however, that software that learns to differentiate between trustworthy and false messages will be developed and, whether we like it or not, Twitter and other social media phenomena will almost surely be used much more by market participants in the future than they are today.
PS. It should be made very clear that I have never used Twitter myself and I am definitely not a fan of social media in general......