Turning long-form insight into investable signal. Finance-tuned, ticker-mapped sentiment scores from financial podcasts — capturing sustained market conviction, not just short-term noise.
Context Analytics already quantifies what investors are reading (Quantitative News Feed), disclosing (Corporate Filings Intelligence), and saying (Social Media Sentiment). The Podcast Sentiment Feed closes the loop — adding the final, unmeasured channel of in-depth financial conviction.
With more than 4.5 million podcasts worldwide and nearly 600 million global listeners, podcasts drive sustained institutional opinion over time. Until now, that signal had no infrastructure to extract it.
The same infrastructure that powers our News, Social, and Filings feeds — purpose-built for quantitative trading workflows, not generic brand monitoring.
Every episode is captured end-to-end via Automatic Speech Recognition infrastructure, producing high-accuracy transcripts that feed directly into the sentiment pipeline.
Tickers, people, and organizations are extracted from each transcript and tagged at the mention level, producing structured, time-stamped sentiment data.
Fine-tuned sentiment scoring built on the same NLP infrastructure powering CA's News, Social, and Filings feeds — designed for investment context, not generic monitoring.
Themes organized for strategy and screening — identify recurring narratives and cross-sectional talking points before they appear in mainstream price action.
Backed by 10+ years of historical podcast data for long-horizon backtesting, factor development, and validation of podcast-driven signals over time.
Create specialized feeds targeting CEO interviews, analyst discussions, or specific shows based on keywords, metadata filters, and your research strategy.
Podcast sentiment reveals where conviction is building — making it a natural fit for strategies that benefit from long-form, in-depth financial conversations.
Surface the themes that long-form financial media is converging on before they appear in price action.
Capture sustained conviction from in-depth conversations — a natural complement to fundamental and quant workflows.
Track how companies, executives, and themes are being discussed across the global podcast landscape.
| Capability | Context Analytics | Media Monitoring | Transcription APIs |
|---|---|---|---|
| Finance-Tuned Sentiment | ✓ | ✕ | ✕ |
| Ticker-Level Attribution | ✓ | ✕ | ✕ |
| 10+ Years Historical Data | ✓ | Limited | Limited |
| Quantitative Trading Focus | ✓ | PR Focus | DIY Only |
| Structured Sentiment Data | ✓ | Generic | ✕ |
| Proven NLP Track Record | ✓ | Non-Finance | Raw Data Only |
Our analysts tested podcast-derived sentiment scores against subsequent price performance across U.S. Equities. The results show a measurable signal edge — particularly for longer-horizon strategies where conviction builds ahead of consensus.
Fill out the form to access the full performance study and request a one day sample of both the qualitative and quantitative output from our Podcast Sentiment Analysis Feed.
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