Research That Moves Markets

Our quant research papers quantify how news sentiment drives equity returns and how to extract that signal with precision.

Ten Years of History, One Model

Our newest NLP model re-scored a decade of news: sharper company links, far less noise from boilerplate text, and a stronger signal.
• 300M articlesRe-scored with one model.
• One model since 2016
No spliced history, no model break.
• 94% entity precision
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Up from 87%.
300 million news articles from 2016 to today, all scored by Yukka’s new model.

Not All News Is Signal

Of 241,000+ sources, only 15% carry statistically significant predictive power for equity returns. Filtering to the quality panel increases mean IC from 0.006 to 0.041 with no loss in coverage.
• +0.035 IC boost‍Quality sources vs unfiltered
baseline
• Adaptive signal decay
Each source peaks across distinct forecast horizons
• Regime-aware selection
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Source relevance shifts across market environments

How Sentiment Signals Inflation

Our latest study shows that news-based sentiment provides statistically significant predictive power for U.S. CPI-U.

Adding sentiment to standard autoregressive baselines improves explanatory power and reduces forecast errors, consistent with an expectations-to-prices mechanism.
• +0.15 R² boost
‍Improves accuracy vs baseline
• Expectations channel
News tone captures pricing and demand expectations
• Regime-dependent effects
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Predictive strength varies across inflation cycles
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