The ability to use AI and ML at scale is enabling novel solutions to complex problems once difficult or impossible to solve. One such problem is the identification of statistically significant relationships among large numbers of traditional and alternative time series data sets. Discovering meaningful relationships between security prices and such data as interest rates, news stories, Securities and Exchange Commission Filings (SEC) filings, analyst reports, economic events, corporate events, and alternative events such as weather long has been the foundation for generating meaningful trading and investment decisions.
Synechron’s Artificial Intelligence for Signal Discovery is a powerful Data Science platform that ingests large volumes of structured and unstructured data and uses the latest advancements in parallel computing to provide analysts, traders, portfolio managers, and researchers with a fast, intuitive, and scalable platform for rapidly analyzing massive collections of data and identifying meaningful correlations and Granger Causal relationships among time series. It offers a rich collection of data and a library of ML and Deep Learning algorithms with the ability to add custom data and algorithms via an intuitive user interface (UI).