Information drives trading decisions and the ultimate performance and behavior of financial markets. Finding which information drives what trading decision, and further cascading decisions, is the holy grail of financial markets. This question exists in other areas too and is referred to as causal relationships or causality.
Synechron’s Granger Causality is a powerful Data Science platform is a research app that analyzes pairs of Daily and Inter-Day returns, news, SEC filings (10-K’s, 10-Q’s, 8-K’s), macroeconomic data (CPI, PPI, employment, Treasury Yields), and company fundamentals to discover causal relationships. This is intended as an ad hoc analysis tool during the research processes of traditional buy-side and sell-side research analysts.
HOW WE HELP
Retrieve, transform and analyze historical data sets in real-time
Synechron’s Accelerator for Granger Causality
Downloads and makes available near real-time intraday and end of day prices for analysis
Leverages NLP to read and interpret the latest news and economy-wide macroeconomic data
Calculates the real-time market sentiment of a company and its industry based on an in-depth analysis of real-time and historical information
Computes changes in the sentiment of a company’s management team towards the company’s performance using the company’s regulatory filings
Calculates the causal relationships between any pair of stocks and their various sentiment measures or between stocks and macroeconomic factors irrespective of the time period
/ /THE WORK WE DO
The platform features a unique implementation of the Granger Causality algorithm for identifying causal relationships among time series. Conventional time-series analysis is limited to correlations but with Syn-AI users can identify and quantify causal relationships, enabling the development of trading signals, researching insights, and even the mapping of market structure.
The Google Effect: Google’s return “Granger Causes” the one-day return of Apple Corporation (AAPL). Granger Causality can also be run on sentiment versus stock price; the similarity of subsequent SEC filings and stock price return; and nearly any time series.
Syn-AI Market Structure
Market Structure: Syn-AI’s unique implementation of Granger Causality and capital markets structure research provides a comprehensive and first-of-its kind view of the structure of the equity market.
Synechron’s Artificial Intelligence Granger Causality platform is designed to work on historical data sets. To learn more about the platform and the work we’re doing email us at firstname.lastname@example.org