Gustavo Schwenkler (Santa Clara): The Different Networks of Firms Implied by the News

Gustavo Schwenkler: The Different Networks of Firms Implied by the News

Abstract: We use modern natural language processing tools to identify different types of firm linkages from financial news data: financial, competitive, parent subsidiary, and supply chain links. We use these linkages to construct high-frequency & expansive firm networks implied by the news. We show that there is substantial variation in the way in which the news reports about different types of firm linkages. This time variation is predictive of firm-level and aggregate outcomes. Our approach delivers firm network data that are currently unavailable at our level of granularity and time frequency. It opens up avenues for novel research on the transmission of shocks across firms as well as their amplification into aggregate shocks.

Bio: Gustavo Schwenkler is an associate professor of finance at the Santa Clara University Leavey School of Business. His research interests include asset pricing, econometrics, risk management, and derivatives. Gustavo's work has been published in leading peer-reviewed journals, such as the Journal of Financial Economics and the Journal of Econometrics. He is an associate editor at Management Science, the Journal of Business & Economic Statistics, and Digital Finance, and serves in the boards of directors of Cointree and Indicia Labs. Gustavo received his PhD in Management Science and Engineering in 2013 from Stanford University and his diploma in applied mathematics and economics from the University of Cologne. Previously, Gustavo worked at Boston University, Goldman Sachs, and Deutsche Bank.