We apply facial recognition analysis to FOMC press conference videos and quantify one of the most important aspects of nonverbal communication - facial expressions. Using minute-level data, we align our nonverbal communication measure with a set of financial assets to estimate the impact of the...

This paper studies central bank website characteristics of a large set of central banks. We introduce a methodology to systematically derive and quantify these characteristics along the dimensions of textual content, visual presentation, and website performance. We then conduct a survey to...

This paper investigates the characteristics of central bank websites across a large sample of central banks. We systematically derive and quantify these characteristics across three dimensions: text, visual presentation, and website performance. We then conduct a survey to isolate the main...

We study the 'interconnectedness' of stress-tested banks by exploiting how they are mentioned together in the context of financial news. We start by constructing weekly co-occurrence network matrices following Ronnqvist and Sarlin (2015) text-to-network approach. Using the COVID-19 pandemic as...

This paper investigates the ability of Generative Pre-training Transformer (GPT) models to decipher Fedspeak, a term used to describe the technical language used by the Federal Reserve to communicate on monetary policy decisions. We evaluate the ability of GPT models to classify the policy...