We estimate the personal communication risk-premium profile of the U.S. Federal Reserve
(Fed) Chair by measuring a new dataset of the sentiment revealed by their public statements
during their tenure. We analyze the impact of such Fed communications’ sentiment risk on the
uncertainty of the monetary policy, and the market price discovery process of interest rates, in
the aftermath of the Federal Open Market Committee (FOMC) meetings. After controlling for
the evolving state of the economy surrounding the meetings, we find that there is a significant
statistical and economic difference in the communications’ sentiment that is heterogeneous
across Chairs, depending on their personal traits. The sentiment in the Chairs’ communications
plays a role in moderating the potential surprises in the Fed announcements, and it can be
effectively used as a tool for controlling and measuring monetary policy shocks.
JEL classification: G12, G14, G18, G21, G28, G41.
Keywords: Federal Reserve, Monetary Policy,
Communications, Federal Funds Rate, Machine Learning