Quantamental Indicators on JPMaQS
Explore the full catalogue of indicators available through the J.P. Morgan Macrosynergy Quantamental System, including coverage, frequency, and data access methods.
Table of Contents
Platform Overview
JPMaQS (the J.P. Morgan Macrosynergy Quantamental System) is the institutional-grade data platform that delivers macro-quantamental indicators to investment professionals. Developed through a partnership between Macrosynergy and J.P. Morgan, it provides curated, point-in-time macroeconomic data spanning over 40 countries and more than two decades of history.
The platform is designed for quantitative researchers and systematic portfolio managers who need reliable, bias-free macro data for strategy development and backtesting.
The Data Catalogue
JPMaQS hosts over 1,000 individual indicators organized into thematic categories. Each indicator is documented with its source, construction methodology, publication lag, and revision history. The catalogue is continuously expanded as new data sources become available and new composite indicators are developed.
Indicators range from raw economic releases (such as GDP growth and CPI inflation) to sophisticated composite signals (such as excess labor supply indices and fiscal vulnerability scores). All indicators maintain strict point-in-time discipline.
Country Coverage
The system covers all G10 economies plus a broad set of emerging markets, including major Latin American, Asian, and European economies. Coverage depth varies by country, with the richest data available for the United States, Euro Area, United Kingdom, and Japan.
Access Methods
Data can be accessed through multiple channels: a REST API for programmatic access, bulk data downloads for offline analysis, and direct integration with popular quantitative research platforms. The API supports both real-time data retrieval and historical data reconstruction.
The macrosynergy Python Package
The open-source macrosynergy Python package provides a high-level interface to JPMaQS data, along with tools for data visualization, signal construction, backtesting, and performance analysis. It is the recommended starting point for researchers new to the platform.