Joint work with Jörn Debener, Paul F. Hark and Andreas Pfingsten

Abstract: Highly deposit-dependent banks might be strongly negatively affected by the introduction of a central bank digital currency (CBDC). Particularly a retail CBDC, focusing on the use by consumers, may constrain cheap funding and thus erode profits of banks (deposit channel). Our empirical study reveals that stock market reactions of US banks to speeches by US Federal Reserve (FED) executives indicating a CBDC introduction are indeed more negative the more these banks depend on deposits. However, as soon as protection against disintermediation is promised by the FED, e.g., via a non-interest bearing CBDC or a CBDC holding limit per person, we observe positive stock market reactions for highly deposit-dependent banks.

Available at SSRN

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