Artificial intelligence and machine learning are changing the ways that capital markets firms understand and analyze data. While natural language processing is a decades-old technology, it’s gaining prominence today. So too is its sibling, natural language generation, which Wall Street firms and technology providers are deploying to improve research and analysis functions.
Pluribus Labs, created two years ago to use AI and machine-learning techniques to extract signals from unstructured data, is one such firm. Everything that Pluribus delivers that’s text-based is built using NLP tools. The Berkeley, Calif.-based vendor uses AI to judge sentiment to predict outcomes and to analyze longer-form communications ? i.e. SEC 10-K or 10-Q or Form 13F and earnings call transcripts.
“We use that sentiment ? and aspects of the discussion that are not necessarily positive/negative sentiment, but more dispersion of opinions/volume of opinions ? to predict outcomes of the market systematically,” says Frank Freitas, founder and CEO of Pluribus. “We try to focus on taking the outcomes of that discussion to predict both volume and volatility in markets. What we want to capture is people saying things about either the security itself, executives that are associated with that entity, products associated with that entity, and then ? based on capturing those right conversation points ? arrive at a view of sentiment that’s based on what real people are saying. That’s where NLP comes in.”
Click here to read the full article.