Can Brazilian Central Bank communication help to predict the yield curve?

This paper investigates whether Brazilian Central Bank communication helps to forecast the yield curve. Our forecast strategy involves two steps: First, we analyze textual Central Bank documents to extract sentiment variables that describe its communication, and then, we include those sentiment variables as additional factors into the dynamic Nelson-Siegel term structure model. We found that sentiment variables contain predictive information for yield curve forecasting. Specifically, when combined with macroeconomic variables, the sentiment variables improve the accuracy of the forecast for short maturities and forecast horizons. In addition, sentiment variables are useful in forecasting for medium and long forecast horizons for all maturities. Besides finding a new source of information to forecast the yield curve, the results indicate that the information provided by Central Bank affects market participants, proving to be a useful tool for monetary policy.