RS Metrics recently announced that its global metal inventories datasets, MetalSignals™, are now available to Bloomberg Data License clients through Bloomberg Enterprise Access Point. Datasets from MetalSignals’™ AI-enabled satellite imagery platform allows Bloomberg clients to easily access unique and predictive data to gain insights into global metal inventories of aluminum, copper, iron ore, and zinc. Utilizing the RS Metrics SAAS platform, MetalSignals™ monitors and measures activity at global metal smelter and storage locations, providing timely, granular data about metal stockpiles around the world.
The metals market is a key component of businesses and economies. Through Bloomberg Enterprise Access Point, users can now access MetalSignals™ by RS Metrics and access data for multiple metals through a single website which allows fast integration for modelling and analysis. Data License clients can track the physical flows of metals across the globe and use this data to improve their predictive modelling of equities, currencies, and exchange rates.
By combining computer vision capabilities with rigorous sampling techniques, RS Metrics has honed the underlying machine-learning models that power MetalSignals™ and generates high quality data. Furthermore, MetalSignals™ provides five or more years of historical data on metal stockpiles from over 400 smelters, terminals, and storage facilities around the world with information being updated regularly and delivered as a daily data feed. With additional satellite deployments anticipated for 2019, RS Metrics expects to continue increasing the number of sites and frequency of data availability.
Here is a link to the partner page.
About RS Metrics
Founded in 2010, RS Metrics analyzes and derives data from satellite and aerial imagery to provide fundamental insights, trends and predictive signals for businesses and investors in metals, industrials, retail and commercial real estate. RS Metrics’ proprietary, patented technology platform leverages advanced computer vision and machine learning and a scaled QC workflow to generate high quality, predictive and consumable information. Data is available in easy-to-use end-user applications, signals, and tools, and as daily data feeds for customers with quantitative focus and capabilities. For more information, visit https://rsmetrics.com or contact Maneesh Sagar at msagar(at)rmetrics(dot)com. Follow us on Twitter @RSMetrics, on Linkedin at https://www.linkedin.com/company/rsmetrics/, and on Medium at https://medium.com/@RSMetrics.