| May 23, 2019
Are you hoarding way too many emails, messages, and files? RavenPack can turn your internal content into alpha.
In this real-world case study, we show how RavenPack’s Artificial Intelligence (AI) platform including its proprietary Natural Language Processing (NLP) engine can transform your own internal digital content (emails, messages, files) into investment insights and trading signals.
Asset management firms store massive amounts of digital content, which largely remains under analysed and untapped. By systematically structuring and enriching this content in real time, we demonstrate that there is incremental alpha to be captured internally, beyond using public sources like news and social media.
In particular, we found that:
The RavenPackText Analytics Engineprovides real-time structured sentiment, relevance and novelty data for entities and events detected in unstructured text from any internal sources including emails, instant messages, documents, contact databases, and more into a single, enriched format tailored specifically for financial applications. RavenPack generates analytics data on over 52,000 public and private companies, top products and services, all major currencies and commodities, financially relevant places and organizations, and key business and political figures. Request a trial today.
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We consider incorporating sentiment signals from news, earnings call transcripts, and insider transactions to
boost the risk-adjusted returns, and revive factor performance.
We find stronger, more predictable market reactions when the words of company executives agree with their actions.
We have gathered 12 insights from 2021 research that can be leveraged in 2022.