In collaboration with MarketPsych

Leverage Reuters News for predicting commodity prices

Commodity markets respond rapidly to macroeconomic shocks, geopolitical events and shifts in supply.

This whitepaper explores how LSEG’s Real-Time News Service, powered by Reuters, can be transformed into structured sentiment data that supports more accurate short term commodity price forecasting and more responsive risk management strategies.

Drawing on Reuters news data from 2020–2024, this study demonstrates how AI-powered sentiment analysis converts unstructured news into actionable commodity signals. The findings show that sentiment data can enhance price forecasting and improve systematic trading models.

Download the white paper

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Key takeaways:

● Reuters news sentiment shows a measurable relationship with next day commodity returns

● Models using sentiment data delivered approximately 6.4% annualised returns, outperforming a buy and hold approach

● Geopolitical and supply related signals add meaningful insight to crude oil strategies

● Supply focused sentiment models delivered up to 16.2% annualised returns

● Combining sentiment with price data improves forecasting compared to using price data alone

Download the whitepaper to see how sentiment‑driven insights can elevate your commodity forecasting strategies