Natural Language Processing: Deciphering the Message within the Message – Stock Selection Insights using Corporate Earnings Calls

Abstract: Astute investors have shifted their attention to explore the information content in unstructured data sets to differentiate their source of alpha. In this presentation, we will explore a number of sentiment- and behavioral-based signals using the content from earnings call transcripts via NLP that have historically demonstrated stock selection power in the U.S. market.

Bio: Frank is a Senior Director and a key member of S&P Global Market Intelligence’s Quantamental Research group. His primary focus is to conduct systematic alpha research on global equities with publications on natural language processing, newly discovered stock selection anomalies, event-driven strategies and industry-specific signals. Frank has master’s degrees in Financial Engineering from UCLA Anderson and in Finance from Boston College Carroll, and has undergraduate degrees in Computer Science and Economics from University of California, Davis.