Language Analysis of Federal Open Market Committee Minutes

If there were a Superbowl of Finance for equities, it’d definitely be FOMC (Federal Open Market Committee) meetings. Investors and traders from around the world gather and make their decisions on the brink of releasing a statement and following the press conference. Shah, Paturi, and Chava (May 2023) contribute with a new cleaned, tokenized, and labeled open-source dataset for FOMC text analysis of various data categories (meeting minutes, speeches, and press conferences). They also propose a new sequence classification task to classify sentences into different monetary policy stances (hawkish, dovish, and neutral) and show the application of this task by generating a hawkish-dovish classification measure from the trained model that they later use in an interesting trading strategy.

https://quantpedia.com/language-analysis-of-federal-open-market-committee-minutes/