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AI-Powered Alpha: Using Media Signals in Commodity Markets

Discover how real-time global media signals can generate consistent alpha in commodity markets. This white paper reveals how Semantic Visions and AltHub analyzed 120M+ articles across 21 commodities and used machine learning to outperform the Dow Jones Commodity Index by over 16%. Includes performance results, model design, and portfolio insights.

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About this White Paper

Turn media chaos into market clarity.
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Discover how 120+ million global news articles were transformed into precise investment signals for 21 commodities — using machine learning, real-time sentiment, and a proprietary event ontology.

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See the data in action.

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Backtested portfolios built on Semantic Visions’ OSINT data outperformed the Dow Jones Commodity Index by over 16%. Learn how predictive models captured market-moving events before prices reacted.

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Explore a new standard in alt-data analytics.

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This paper walks you through the full data pipeline — from raw news ingestion and sentiment scoring to signal transformation, modeling, and real-world performance validation via AltHub’s QuantLab.

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Who it’s for:

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Quant funds, asset managers, risk officers, and analysts looking to leverage real-time media signals in fast-moving commodity markets.

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Commodity background.

Commodity Highlights: Top Events of the Past 7 Days

This dashboard provides an overview of the past week’s top 5 most traded commodities and significant market trends. It includes article counts and the distribution of events impacting commodities such as Crude Oil, Natural Gas, Coffee, Gold, and Wheat.