We construct a communication risk profile of the U.S. Federal Reserve Chair by measuring the sentiment of their public statements during their tenure. Communications' sentiment impact on the interest rates price discovery process by the market after the FOMC meeting is analyzed. The results show that there is a significant difference in the communications' sentiment that is heterogeneous on the personal characteristics, controlling for the economic environment, and that the Chair communications' sentiment plays a role in diminishing the surprise of Federal
JEL classification: G12, G14, G18, G21, G28, G41.
Keywords: Federal Reserve, Monetary Policy, Communications, Federal Funds Rate, Machine Learning