Joint work with Heiner Beckmeyer, Ilias Filippou, Stefan Menze and Guofu Zhou

Abstract: The introduction of ChatGPT has changed how humans process textual data. We devise a prompting strategy for ChatGPT to identify and analyze unusual aspects of financial communication, focusing on earnings calls of S&P 500 firms. Utilizing the latest GPT-4-Turbo model, we identify and categorize unusual financial communication across 25 dimensions, which fall into four categories: unusual communication by executives, by financial analysts, unusual content, and technical issues. A significant portion of earnings calls displays unusual financial communication, which correlates with certain firm characteristics and fluctuates with the business cycles. The stock market reacts negatively to unusual communication, with an elevated trading activity. We highlight the potential of large language models like ChatGPT in financial analyses, offering new insights into the interpretation of complex textual data and its economic consequences on market impacts.

Available at SSRN