In late 2015 the New York Times R&D Labs considered the very question in their post “The Future of News is not an Article”. Understanding what news is, how/when its produced and the ongoing evolution of automated news solutions is crucial to integrating news into a human or quantitative investment processes.
The power of time series data to identify and predict trends cannot be forgotten as we discuss this evolutionary encoding and transformation of large text data sets. From a publishers perspective, the author extends the following thought “Information should accumulate upon itself; documents should have ways of reacting to new reporting or information; and we should consider the consumption behavior of our users as one that takes place at all cadences, not simply as a daily update.” Cumulative data and the compound effects of the data as well as the underlying components of those effects are the driving force behind trend analysis, predictive capability and generating alpha within funds. The transformation of news data into quantified sentiment is not, enough. The ongoing capture, transformation and trending analysis provides the true insight to facilitate action.
As media, traditional news outlets and their publishing tools continue to evolve so too must the financial markets evolve to incorporate these changes – empowering them to leverage every word of data, every phrase of sentiment, every news article as components in their quantitative decision making process and delivering alpha.