Data Product Overview

Descartes Labs' daily soybean meal price forecasts provide procurement or trading professionals with early insight into supply and demand factors that affect agricultural market prices and volatility. Derived from a 20+ petabyte lake of cleansed geospatial data, the forecasts evaluate a vast array of predictive features across the following categories:  

• Weather and climate phenomena
• Crop health, yield, and harvesting
• Supply chain logistics, freight, and shipping
• Government statistics and public data
• Macro, energy, and other market data  

The result is a sophisticated ensemble of models built using over ten years of historical data.  

This sample contains CBOT soybean meal price forecasts for the second, third, or fourth back-month futures contract at two forecast horizons in the future: ten and thirty market days.  

Use Cases

Procurement

• Reduce costs of direct procurement purchasing/hedging operations
• Mitigate physical and pricing risk exposure to commodities and their derived ingredients
• Gain an alternative view of the markets that can be used to generate significant cost savings (over traditional benchmarks) and reduce volatility-induced price risk  

Trading

• Generate alpha in volatile markets that experience frequent regime transitions due to a variety of temporally influential drivers
• Incorporate geospatial intelligence into existing fundamental and technical analysis
• Leverage proprietary price forecasts to complement existing strategies  

Metadata

This listing contains sample price forecasts for the soybean meal futures contract traded on the CME Group’s CBOT exchange. For each day in the historical sample epoch, a forecast of the open price of the then-current second, third, or fourth back-month futures contract (depending on forecast horizon) is provided at two forecast horizons in the future: ten and thirty market days.  

The sample contains one .csv file for each of the 10-day and 30-day forecast horizons. Each file contains a time-series with each row representing a date and the following columnar data (by date): model run date, forecast/target date, front-month futures contract as of run date, futures contract forecasted, and forecasted price at target date.  

The data set is updated quarterly (according to the calendar year) and includes data for the most recently elapsed quarter. For example, on June 17, 2022, the .csv files in the data set will contain data up to March 31, 2022.  

Need Help?

If you have questions about our products, contact us at support@descarteslabs.com.  

Who We Are

Descartes Labs is a technology company that automates the analysis of geospatial data to help organizations answer key questions about the physical world. With our SaaS platform, we enable the analysis of earth observation data at scale, providing services and solutions across commodity sourcing and forecasting, resource exploration, and climate resilience, while also supporting diverse federal government efforts to gather, analyze, and provide actionable insights from geospatial data. Descartes Labs has over 120 employees and is headquartered in Santa Fe, New Mexico.

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