Using textual analysis of earnings conference calls, we quantify firm level risk arising from the reliability of the supply chain from 2002 to 2020. Our proxy for perceived supply chain risk exhibits cross-sectional and time-series variation that aligns with reasonable priors and is...

Disclosure of prudential information on environmental, social and governance (ESG) risks will become mandatory from June, 2022 for large institutions with securities traded on a regulated market of any Member State. This paper tries to assess how prepared European financial institutions are for...

Natural language is a key form of communication in the capital markets. Textual analysis is the application of Natural Language Processing (NLP) to textual data for automated information extraction or measurement. We survey publications in top accounting journals and describe the trend and...

This paper presents a novel technique to perform multilingual sentiment classification of financial documents drawing on methods from computational linguistics. The challenge is to efficiently analyze large volumes of text produced by corporations and companies in various languages to find...

We examine whether empirical results using text-based sentiment of U.S. annual reports depend on the underlying context, within documents, from which sentiment is measured. We construct a clause-level measure of context, showing that sentiment is driven by many different contexts and that...

In this analysis, we investigate ECB communication by analyzing more than 3,800 speeches from 1999 until 2022. The study measures the attention which ECB Council members pay to various implicit and explicit monetary policy objectives. While price stability, according to the Maastricht Treaty, is...