The leading alternative dataset for geopolitical risk is now available for purchase on the Bloomberg Enterprise Access Point
Predata uncovers predictive behavior by applying machine learning techniques to online activity
Predata is the leading predictive analytics company for anticipating geopolitical risk. With alternative data and machine learning, we quantify meaningful online behavior to help anticipate events around the world.
Using a patented methodology, Predata analyzes web traffic metadata to isolate research interest from professionals and academics, distinguishing superficial media coverage from well-informed concern. By selecting audiences and content that reveal a clear intentional narrative, we derive time-series signals to quantify topics and risks that would otherwise defy measurement. As leading indicators of where interest and market activity may be headed, our signals enable customers to focus attention on salient tail risks.
Generally, Predata’s signals represent web traffic as multivariate time series with dimensions for language, browser platform, and time of day. Each dimension, and the interplay between them, is an opportunity to isolate more relevant audiences to your topic of interest.
Our dataset is now available on Bloomberg Enterprise Access Point
Predata offers thousands of signals for over 160 countries, as well as for asset classes such as major currencies and commodities.
Each signal is a summarized index of risk, calculated from thousands of data points curated from a wide range of online sources. The data is delivered daily with coverage going back to January 2010.
Signals quantify key market factors and have been constructed to reflect the consistent way issues arise across topics related to the economy, government, security and society.
Bloomberg eliminates costly and lengthy procurement processes, speeding up time to value and enabling easy integration to existing systems.
With Bloomberg Enterprise Access Point, a web-based platform powered by Hypermedia API, data is delivered in Clean and Tidy, machine readable formats which facilitates easy ingestion and reduces data wrangling costs.
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