From barley to castor oil, robusta coffee, steel or soybeans, leverage sentiment
indicators on market-moving news.
RavenPack delivers an exceptionally broad
coverage of carefully curated news, social media,
and data sources:
Highly-granular indicators built using proprietary machine learning
deliver a quantitative analysis of sentiment for each entity involved in
detected events, including credit and sustainability risk.
Make data-driven decisions based on a refined view of various aspects
of news and stay ahead of commodities-related narratives.
Trends develop over weeks and months, but only a sophisticated analytical
framework can detect them as they shape. With RavenPack Edge data, you can analyze
co-mentions networks applied to commodities to identify emerging actors and market shifts.
Explore some of the research published on the use of RavenPack for commodities trading:
High inflation has returned in developed markets after decades of lying low. In our latest paper, we show how to build an inflation-based asset allocation strategy using sentiment data and we illustrate that sentiment-based strategies outperform models that depend merely on past observed inflation values.
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